From da5b86981f97b1443dd5e8040266ec413c890b12 Mon Sep 17 00:00:00 2001 From: "Anqi (Anthony) Tang" Date: Fri, 27 Mar 2026 23:24:49 +0800 Subject: [PATCH 1/9] remove: delete obsolete docs Troubleshooting and checklist docs are no longer needed. --- ...mount_permission_troubleshooting_prompt.md | 44 ----------- .../windows-installer-regression-checklist.md | 73 ------------------- 2 files changed, 117 deletions(-) delete mode 100644 docs/cowork_mount_permission_troubleshooting_prompt.md delete mode 100644 docs/windows-installer-regression-checklist.md diff --git a/docs/cowork_mount_permission_troubleshooting_prompt.md b/docs/cowork_mount_permission_troubleshooting_prompt.md deleted file mode 100644 index f1b0d652..00000000 --- a/docs/cowork_mount_permission_troubleshooting_prompt.md +++ /dev/null @@ -1,44 +0,0 @@ -# Cowork 目录权限异常排障提示词（复用模板） - -你是本项目的排障助手，请按“先复现、再定位、后修复、最后验证”的顺序，排查 `cowork` 模式下目录写权限异常问题。 - -## 背景 -- 项目：`openagent` -- 典型场景：用户在 `cowork` 模式选择 Windows 工作目录后，第一次创建目录成功；继续进入该目录再创建子目录失败，报 `Permission denied`。 -- 目标：确认是挂载状态丢失/误清理导致，还是用户目录本身无权限，并给出可验证修复。 - -## 重点怀疑点（优先检查） -1. WSL session 挂载点是否真实挂载（不是空目录占位）。 -2. `PATCH /api/sessions/{id}` 同路径重挂载时，是否发生“恢复后又被清理”的逻辑回归。 -3. `mount_working_dir()` 的同路径分支是否错误执行了旧挂载点清理。 - -## 执行步骤 -1. 检查后端健康：`GET /health` 必须 `ok`。 -2. 创建 cowork warm session（带 `working_dir`）。 -3. 在 session 用户下执行两级目录创建，确认首次成功。 -4. 人为卸载该 session 的挂载点（模拟异常），复现 `Permission denied`。 -5. 调用 `PATCH /api/sessions/{id}` 传入同 `working_dir` 触发自愈。 -6. 用 `findmnt` 校验挂载是否恢复，再次执行两级目录创建。 -7. 给出结论：恢复成功/失败，并附关键证据（命令输出与日志片段）。 - -## 关键判定标准 -- **异常态**：挂载点权限显示 `drwxr-xr-x root root` 且 `findmnt` 无结果，session 用户写入失败。 -- **恢复态**：`findmnt` 命中目标路径，目录权限回到可写（常见 `drwxrwxrwx`），session 用户可连续创建父/子目录。 - -## 本次问题已验证的根因线索 -- 同路径自愈重挂载后，末尾“清理旧挂载点”逻辑可能把当前刚恢复的挂载再次 `umount/rmdir`，导致后续二级目录创建失败。 -- 修复方向：仅在“切换到不同 target”时清理旧挂载点；同 target 自愈时禁止清理当前挂载路径。 - -## 修复后回归要求 -1. 正常路径：首次创建目录成功。 -2. 异常注入：强制卸载后创建失败（证明复现有效）。 -3. 自愈路径：`PATCH` 后挂载恢复成功。 -4. 结果验证：恢复后再次创建父/子目录成功。 -5. 前端体验：挂载进行中显示明显 loading，不是仅按钮置灰。 - -## 输出格式要求（给排障者） -- 先给“结论一句话”。 -- 再给“证据三条”（健康、挂载、写入结果）。 -- 再给“修复点与文件路径”。 -- 最后给“可复用命令清单”。 - diff --git a/docs/windows-installer-regression-checklist.md b/docs/windows-installer-regression-checklist.md deleted file mode 100644 index c72c92a2..00000000 --- a/docs/windows-installer-regression-checklist.md +++ /dev/null @@ -1,73 +0,0 @@ -# Windows Installer Regression Checklist (No-WSL Machine) - -## 0. Test Environment -- Fresh Windows 10/11 x64 machine (no OpenAgent, no WSL distro). -- Verify: - - `wsl --status` shows not installed or unavailable. - - `wsl -l -v` has no `openagent` distro. - -## 1. Install App -- Run `OpenAgent-0.0.1-win-x64.exe`. -- Open OpenAgent -> Settings -> Sandbox. -- Expected: - - App launches normally. - - No crash on Sandbox page. - -## 2. Assisted WSL Install (First-time) -- Click VM setup / Retry on `VM Engine`. -- Expected: - - If WSL missing: clear guided message appears. - - App attempts assisted install (with clear status text). - - If system needs reboot, UI explicitly asks reboot. - -## 3. Reboot Required Path -- If prompted, reboot Windows. -- Re-open OpenAgent -> Sandbox. -- Click Retry again. -- Expected: - - `VM Instance` eventually becomes `Ready`. - - No `exit 4294967295` generic toast without guidance. - -## 4. VM Dependencies Install -- Click install for `VM System Dependencies`. -- Expected: - - Progress steps update continuously. - - Failure (if any) includes actionable reason. - - Success ends with green/ready state. - -## 5. Cowork Functional Smoke Test -- Set cowork folder to a writable path, e.g. `D:\code\agentTest`. -- In chat: - - Create folder `sport`. - - Then create `sport\basketball`. -- Expected: - - Both operations succeed. - - No false "current directory not writable" error. - -## 6. Non-Technical User UX Check -- Trigger BIOS/virtualization-disabled scenario (or validate copy via mocked error). -- Expected: - - Error includes clear next steps: - - Enable virtualization in BIOS (Intel VT-x / AMD SVM). - - Save BIOS and reboot. - - Retry in app. - - Language is understandable for non-technical users. - -## 7. Log Collection (On Failure) -- Collect: - - OpenAgent backend logs. - - Sandbox setup UI log panel output. - - `wsl --status` - - `wsl -l -v` -- Record exact toast error text and timestamp. - -## 8. Release Gate (Pass Criteria) -- Must pass: - - App install + launch. - - WSL guided install path. - - Reboot path. - - VM Instance ready. - - VM dependencies ready. - - Cowork nested directory creation. -- Block release if any of above fails. - From 82b81e6efd3e0075bfab973821d945afb658d9ce Mon Sep 17 00:00:00 2001 From: "Anqi (Anthony) Tang" Date: Fri, 27 Mar 2026 23:26:52 +0800 Subject: [PATCH 2/9] feat(ui): rebrand HexAgent to ClawWork in all user-facing text MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Rename the display brand name across the frontend UI — page title, sidebar, welcome screens, onboarding wizard, and Electron error dialog. Internal package names, storage keys, and code identifiers unchanged. --- libs/hexagent_demo/electron/main.js | 2 +- libs/hexagent_demo/frontend/index.html | 2 +- .../frontend/src/components/OnboardingWizard.tsx | 14 +++++++------- .../frontend/src/components/Sidebar.tsx | 2 +- .../frontend/src/components/WelcomeScreen.tsx | 4 ++-- 5 files changed, 12 insertions(+), 12 deletions(-) diff --git a/libs/hexagent_demo/electron/main.js b/libs/hexagent_demo/electron/main.js index b65a9061..f7a5cf5e 100644 --- a/libs/hexagent_demo/electron/main.js +++ b/libs/hexagent_demo/electron/main.js @@ -454,7 +454,7 @@ app.whenReady().then(async () => { } catch (err) { console.error("Failed to start backend:", err); dialog.showErrorBox( - "HexAgent - Failed to Start", + "ClawWork - Failed to Start", `The backend server could not be started.\n\n${err.message}` ); app.quit(); diff --git a/libs/hexagent_demo/frontend/index.html b/libs/hexagent_demo/frontend/index.html index 6b14c1ce..82bb44df 100644 --- a/libs/hexagent_demo/frontend/index.html +++ b/libs/hexagent_demo/frontend/index.html @@ -4,7 +4,7 @@ - HexAgent + ClawWork
diff --git a/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx b/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx index e7aeebd8..3fe832f0 100644 --- a/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx +++ b/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx @@ -345,13 +345,13 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting
-

HexAgent

+

ClawWork

-

Powered by HexAgent harness

+

Powered by ClawWork harness

- +

Compute environments

- HexAgent uses sandboxed environments to run code safely. E2B is required for Chat mode. + ClawWork uses sandboxed environments to run code safely. E2B is required for Chat mode.

@@ -979,7 +979,7 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting {vmUsable && vmPhase3 !== "done" && (

- System dependencies install in the background — you can continue using HexAgent while it runs. + System dependencies install in the background — you can continue using ClawWork while it runs.

)}
@@ -1054,7 +1054,7 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting to tools like Python, Node.js, LaTeX, LibreOffice, and more.

- The installation runs in the background — you can start using HexAgent immediately. + The installation runs in the background — you can start using ClawWork immediately.

diff --git a/libs/hexagent_demo/frontend/src/components/Sidebar.tsx b/libs/hexagent_demo/frontend/src/components/Sidebar.tsx index 467d5790..ae2ac144 100644 --- a/libs/hexagent_demo/frontend/src/components/Sidebar.tsx +++ b/libs/hexagent_demo/frontend/src/components/Sidebar.tsx @@ -149,7 +149,7 @@ export default function Sidebar({ onNewConversation, onOpenSettings, onOpenSearc
HexAgent - HexAgent + ClawWork
- ))} -
+ + {mode === "chat" ? "Chat" : "Cowork"} + {isMac ? "⇧⌘" : "Ctrl+Shift+"}{idx + 1} + + + ))} + + )} {hasMessages && (
diff --git a/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx b/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx index 3fe832f0..7a884be7 100644 --- a/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx +++ b/libs/hexagent_demo/frontend/src/components/OnboardingWizard.tsx @@ -158,8 +158,6 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting const [showFetchKey, setShowFetchKey] = useState(false); // ── Step 4: Compute ── - const [e2bKey, setE2bKey] = useState(""); - const [showE2bKey, setShowE2bKey] = useState(false); // VM setup — shared with Settings via VMSetupProvider (single source of truth) const vm = useVMSetup(); @@ -313,7 +311,8 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting fetch_api_key: fetchKey, }, sandbox: { - e2b_api_key: e2bKey, + e2b_api_key: "", + chat_enabled: false, }, }; @@ -845,7 +844,7 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting

Compute environments

- ClawWork uses sandboxed environments to run code safely. E2B is required for Chat mode. + ClawWork uses sandboxed environments to run code safely.

@@ -853,42 +852,13 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting {error &&
{error}
}
- {/* E2B for Chat mode */} -
-
- -
- E2B Sandbox - Chat mode -
-
-

- Cloud sandbox for safe code execution (required). Get a free key at e2b.dev -

-
- -
- setE2bKey(e.target.value)} - placeholder="e2b_..." - /> - -
-
-
- {/* VM for Cowork mode */}
Virtual Machine - Cowork mode + Required

@@ -1001,6 +971,7 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting )}

+
{/* Skip confirmation popup */} @@ -1009,9 +980,6 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting
e.stopPropagation()}>

Are you sure you want to skip?

    - {!e2bKey.trim() && ( -
  • Without an E2B API key, Chat mode will not be available.
    • - )} {vmSupported && !vmUsable && !vmSkipped && (
  • Without a Virtual Machine, Cowork mode will not be available.
    • )} @@ -1077,9 +1045,8 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting )} {(() => { - const hasE2b = !!e2bKey.trim(); const vmReady = vmUsable || vmSkipped || vmSupported === false; - const canProceed = hasE2b && vmReady; + const canProceed = vmReady; const anyVmRunning = vmPhase1 === "running" || vmPhase2 === "running" || vmPhase3 === "running"; const needsDepsPrompt = canProceed && vmUsable && vmPhase3 !== "done" && vmPhase3 !== "running"; const handleNext = () => { @@ -1157,13 +1124,6 @@ export default function OnboardingWizard({ open, onComplete, settings, onSetting {fetchProvider ? fetchProvider.charAt(0).toUpperCase() + fetchProvider.slice(1) : "Skipped"}
-
- - E2B Sandbox - - {e2bKey ? "Configured" : "Skipped"} - -
Virtual Machine diff --git a/libs/hexagent_demo/frontend/src/components/SettingsModal.tsx b/libs/hexagent_demo/frontend/src/components/SettingsModal.tsx index 9ab9392e..7dbb5bc6 100644 --- a/libs/hexagent_demo/frontend/src/components/SettingsModal.tsx +++ b/libs/hexagent_demo/frontend/src/components/SettingsModal.tsx @@ -1742,66 +1742,17 @@ function SandboxTab({ config, onConfigChange }: ConfigTabProps) { const coreError = phase1 === "error" || phase2 === "error"; const phase1NeedsRestart = /restart windows|重启.*windows|重启.*电脑|reboot/i.test(phase1Error || ""); + const chatEnabled = !!config.sandbox.chat_enabled; + return (
- {/* ── E2B Sandbox (Chat mode) ── */} -
-
-
-
-
- E2B Sandbox - Chat mode -
- Cloud sandbox — runs agent code remotely via E2B -
- - {e2bConfigured - ? <> Configured - : <> Not configured} - -
-
-
- -
- { - onConfigChange((prev) => ({ - ...prev, - sandbox: { ...prev.sandbox, e2b_api_key: e.target.value }, - })); - }} - /> - -
-
-
-
- - {/* ── Virtual Machine (Cowork mode) ── */} + {/* ── Virtual Machine ── */}
Virtual Machine - Cowork mode {vmPlatformLabel}
Local VM sandbox — runs agent code securely on your machine @@ -2016,6 +1967,72 @@ function SandboxTab({ config, onConfigChange }: ConfigTabProps) { )}
+ + {/* ── Chat Mode (legacy) ── */} +
+
+
+
+
+ Chat Mode + Optional +
+ Cloud sandbox via E2B — runs agent code remotely +
+ +
+ {chatEnabled && ( +
+
+ +

Get a free key at e2b.dev

+
+ { + onConfigChange((prev) => ({ + ...prev, + sandbox: { ...prev.sandbox, e2b_api_key: e.target.value }, + })); + }} + /> + +
+
+ {!e2bConfigured && ( +

+ An E2B API key is required to use Chat mode. +

+ )} +
+ )} +
); } diff --git a/libs/hexagent_demo/frontend/src/store.ts b/libs/hexagent_demo/frontend/src/store.ts index 6e946d7f..3ad04d72 100644 --- a/libs/hexagent_demo/frontend/src/store.ts +++ b/libs/hexagent_demo/frontend/src/store.ts @@ -67,7 +67,7 @@ export const initialState: AppState = { selectedModelId: "", selectedMode: (() => { const m = window.location.pathname.match(/^\/(chat|cowork)/); - return (m ? m[1] : "chat") as ConversationMode; + return (m ? m[1] : "cowork") as ConversationMode; })(), lastActiveByMode: { chat: null, cowork: null }, notifications: [], From 360482000d9e4212f9c9f7a97de536c57d287466 Mon Sep 17 00:00:00 2001 From: "Anqi (Anthony) Tang" Date: Sat, 28 Mar 2026 00:05:36 +0800 Subject: [PATCH 4/9] feat(ui): replace sidebar logo with ClawWork brand icon Swap the old favicon SVG for the new uniai.png brand logo in the sidebar header. --- .../frontend/src/assets/brand-logo.png | Bin 0 -> 63764 bytes .../frontend/src/components/Sidebar.tsx | 4 ++-- 2 files changed, 2 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zr#gEbjee-o^L@G5-oo80SjT8Q@dqi6@QqbIZOD7(JD9=wjGN+O4QHQ7<4K_u5`F>s3y zPLio4e&W)ok(lR>E&U0>KIN`_$2zs3M%DO+@e$~E5cub+G{Na7;8tPS>t!fJzlzp4 zrj39f8X=D8|Ni{RA$oV^y{=^6w)&>D(3pl@+st!;%dt3&_Lzx8{Ri7R)|O?n&7>P_ zPonyS_|ODH+=fPfEnU#Y^sV=Xxp+^YW$S}j1rjhxPmg?h`TsXR)@u-7^scTi6obi# QkbplWc{RB@8H>>W1)5)W$N&HU literal 0 HcmV?d00001 diff --git a/libs/hexagent_demo/frontend/src/components/Sidebar.tsx b/libs/hexagent_demo/frontend/src/components/Sidebar.tsx index ae2ac144..dc04bc7d 100644 --- a/libs/hexagent_demo/frontend/src/components/Sidebar.tsx +++ b/libs/hexagent_demo/frontend/src/components/Sidebar.tsx @@ -1,5 +1,5 @@ import { useState, useCallback, useEffect, useRef } from "react"; -import faviconSvg from "../assets/favicon.svg"; +import brandLogo from "../assets/brand-logo.png"; import { Plus, Search, MoreHorizontal, Trash2, Pencil, Settings, PanelLeft } from "lucide-react"; import { useAppContext } from "../store"; import { deleteConversation } from "../api"; @@ -148,7 +148,7 @@ export default function Sidebar({ onNewConversation, onOpenSettings, onOpenSearc (outside the sliding aside). On wide screens it's static inside the clip. */}
- HexAgent + ClawWork ClawWork
+ +
+ +
+ + +
+

Parameters

+ + +
+ +
+ + 5000 +
+
+ + +
+ +
+ + 0.5 +
+
+ + +
+ +
+ + 0.005 +
+
+ + +
+ +
+ + 8 +
+
+
+ + +
+

Colors

+ + +
+ +
+ + #d97757 +
+
+ + +
+ +
+ + #6a9bcc +
+
+ + +
+ +
+ + #788c5d +
+
+
+ + +
+

Actions

+
+ +
+
+
+ + +
+
+
Initializing generative art...
+
+
+ + + + + diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/LICENSE.txt b/libs/hexagent_demo/backend/skills/examples/mcp-builder/LICENSE.txt new file mode 100644 index 00000000..d6456956 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/LICENSE.txt @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK). +description_zh: "MCP 服务器开发指南，集成外部 API 和服务" +description_en: "Guide for creating MCP servers to integrate external APIs and services" +version: 1.0.0 +license: Complete terms in LICENSE.txt +metadata: + author: codebuddy + url: https://www.codebuddy.cn/docs/ide/Features/Skills +--- + +# MCP Server Development Guide + +## Overview + +Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks. + +--- + +# Process + +## 🚀 High-Level Workflow + +Creating a high-quality MCP server involves four main phases: + +### Phase 1: Deep Research and Planning + +#### 1.1 Understand Modern MCP Design + +**API Coverage vs. Workflow Tools:** +Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage. + +**Tool Naming and Discoverability:** +Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., `github_create_issue`, `github_list_repos`) and action-oriented naming. + +**Context Management:** +Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently. + +**Actionable Error Messages:** +Error messages should guide agents toward solutions with specific suggestions and next steps. + +#### 1.2 Study MCP Protocol Documentation + +**Navigate the MCP specification:** + +Start with the sitemap to find relevant pages: `https://modelcontextprotocol.io/sitemap.xml` + +Then fetch specific pages with `.md` suffix for markdown format (e.g., `https://modelcontextprotocol.io/specification/draft.md`). + +Key pages to review: +- Specification overview and architecture +- Transport mechanisms (streamable HTTP, stdio) +- Tool, resource, and prompt definitions + +#### 1.3 Study Framework Documentation + +**Recommended stack:** +- **Language**: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code, benefiting from its broad usage, static typing and good linting tools) +- **Transport**: Streamable HTTP for remote servers, using stateless JSON (simpler to scale and maintain, as opposed to stateful sessions and streaming responses). stdio for local servers. + +**Load framework documentation:** + +- **MCP Best Practices**: [📋 View Best Practices](./reference/mcp_best_practices.md) - Core guidelines + +**For TypeScript (recommended):** +- **TypeScript SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md` +- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - TypeScript patterns and examples + +**For Python:** +- **Python SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` +- [🐍 Python Guide](./reference/python_mcp_server.md) - Python patterns and examples + +#### 1.4 Plan Your Implementation + +**Understand the API:** +Review the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed. + +**Tool Selection:** +Prioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations. + +--- + +### Phase 2: Implementation + +#### 2.1 Set Up Project Structure + +See language-specific guides for project setup: +- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - Project structure, package.json, tsconfig.json +- [🐍 Python Guide](./reference/python_mcp_server.md) - Module organization, dependencies + +#### 2.2 Implement Core Infrastructure + +Create shared utilities: +- API client with authentication +- Error handling helpers +- Response formatting (JSON/Markdown) +- Pagination support + +#### 2.3 Implement Tools + +For each tool: + +**Input Schema:** +- Use Zod (TypeScript) or Pydantic (Python) +- Include constraints and clear descriptions +- Add examples in field descriptions + +**Output Schema:** +- Define `outputSchema` where possible for structured data +- Use `structuredContent` in tool responses (TypeScript SDK feature) +- Helps clients understand and process tool outputs + +**Tool Description:** +- Concise summary of functionality +- Parameter descriptions +- Return type schema + +**Implementation:** +- Async/await for I/O operations +- Proper error handling with actionable messages +- Support pagination where applicable +- Return both text content and structured data when using modern SDKs + +**Annotations:** +- `readOnlyHint`: true/false +- `destructiveHint`: true/false +- `idempotentHint`: true/false +- `openWorldHint`: true/false + +--- + +### Phase 3: Review and Test + +#### 3.1 Code Quality + +Review for: +- No duplicated code (DRY principle) +- Consistent error handling +- Full type coverage +- Clear tool descriptions + +#### 3.2 Build and Test + +**TypeScript:** +- Run `npm run build` to verify compilation +- Test with MCP Inspector: `npx @modelcontextprotocol/inspector` + +**Python:** +- Verify syntax: `python -m py_compile your_server.py` +- Test with MCP Inspector + +See language-specific guides for detailed testing approaches and quality checklists. + +--- + +### Phase 4: Create Evaluations + +After implementing your MCP server, create comprehensive evaluations to test its effectiveness. + +**Load [✅ Evaluation Guide](./reference/evaluation.md) for complete evaluation guidelines.** + +#### 4.1 Understand Evaluation Purpose + +Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions. + +#### 4.2 Create 10 Evaluation Questions + +To create effective evaluations, follow the process outlined in the evaluation guide: + +1. **Tool Inspection**: List available tools and understand their capabilities +2. **Content Exploration**: Use READ-ONLY operations to explore available data +3. **Question Generation**: Create 10 complex, realistic questions +4. **Answer Verification**: Solve each question yourself to verify answers + +#### 4.3 Evaluation Requirements + +Ensure each question is: +- **Independent**: Not dependent on other questions +- **Read-only**: Only non-destructive operations required +- **Complex**: Requiring multiple tool calls and deep exploration +- **Realistic**: Based on real use cases humans would care about +- **Verifiable**: Single, clear answer that can be verified by string comparison +- **Stable**: Answer won't change over time + +#### 4.4 Output Format + +Create an XML file with this structure: + +```xml + + + Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat? + 3 + + + +``` + +--- + +# Reference Files + +## 📚 Documentation Library + +Load these resources as needed during development: + +### Core MCP Documentation (Load First) +- **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix +- [📋 MCP Best Practices](./reference/mcp_best_practices.md) - Universal MCP guidelines including: + - Server and tool naming conventions + - Response format guidelines (JSON vs Markdown) + - Pagination best practices + - Transport selection (streamable HTTP vs stdio) + - Security and error handling standards + +### SDK Documentation (Load During Phase 1/2) +- **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` +- **TypeScript SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md` + +### Language-Specific Implementation Guides (Load During Phase 2) +- [🐍 Python Implementation Guide](./reference/python_mcp_server.md) - Complete Python/FastMCP guide with: + - Server initialization patterns + - Pydantic model examples + - Tool registration with `@mcp.tool` + - Complete working examples + - Quality checklist + +- [⚡ TypeScript Implementation Guide](./reference/node_mcp_server.md) - Complete TypeScript guide with: + - Project structure + - Zod schema patterns + - Tool registration with `server.registerTool` + - Complete working examples + - Quality checklist + +### Evaluation Guide (Load During Phase 4) +- [✅ Evaluation Guide](./reference/evaluation.md) - Complete evaluation creation guide with: + - Question creation guidelines + - Answer verification strategies + - XML format specifications + - Example questions and answers + - Running an evaluation with the provided scripts diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/evaluation.md b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/evaluation.md new file mode 100644 index 00000000..1beeb205 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/evaluation.md @@ -0,0 +1,602 @@ +# MCP Server Evaluation Guide + +## Overview + +This document provides guidance on creating comprehensive evaluations for MCP servers. Evaluations test whether LLMs can effectively use your MCP server to answer realistic, complex questions using only the tools provided. + +--- + +## Quick Reference + +### Evaluation Requirements +- Create 10 human-readable questions +- Questions must be READ-ONLY, INDEPENDENT, NON-DESTRUCTIVE +- Each question requires multiple tool calls (potentially dozens) +- Answers must be single, verifiable values +- Answers must be STABLE (won't change over time) + +### Output Format +```xml + + + Your question here + Single verifiable answer + + +``` + +--- + +## Purpose of Evaluations + +The measure of quality of an MCP server is NOT how well or comprehensively the server implements tools, but how well these implementations (input/output schemas, docstrings/descriptions, functionality) enable LLMs with no other context and access ONLY to the MCP servers to answer realistic and difficult questions. + +## Evaluation Overview + +Create 10 human-readable questions requiring ONLY READ-ONLY, INDEPENDENT, NON-DESTRUCTIVE, and IDEMPOTENT operations to answer. Each question should be: +- Realistic +- Clear and concise +- Unambiguous +- Complex, requiring potentially dozens of tool calls or steps +- Answerable with a single, verifiable value that you identify in advance + +## Question Guidelines + +### Core Requirements + +1. **Questions MUST be independent** + - Each question should NOT depend on the answer to any other question + - Should not assume prior write operations from processing another question + +2. **Questions MUST require ONLY NON-DESTRUCTIVE AND IDEMPOTENT tool use** + - Should not instruct or require modifying state to arrive at the correct answer + +3. **Questions must be REALISTIC, CLEAR, CONCISE, and COMPLEX** + - Must require another LLM to use multiple (potentially dozens of) tools or steps to answer + +### Complexity and Depth + +4. **Questions must require deep exploration** + - Consider multi-hop questions requiring multiple sub-questions and sequential tool calls + - Each step should benefit from information found in previous questions + +5. **Questions may require extensive paging** + - May need paging through multiple pages of results + - May require querying old data (1-2 years out-of-date) to find niche information + - The questions must be DIFFICULT + +6. **Questions must require deep understanding** + - Rather than surface-level knowledge + - May pose complex ideas as True/False questions requiring evidence + - May use multiple-choice format where LLM must search different hypotheses + +7. **Questions must not be solvable with straightforward keyword search** + - Do not include specific keywords from the target content + - Use synonyms, related concepts, or paraphrases + - Require multiple searches, analyzing multiple related items, extracting context, then deriving the answer + +### Tool Testing + +8. **Questions should stress-test tool return values** + - May elicit tools returning large JSON objects or lists, overwhelming the LLM + - Should require understanding multiple modalities of data: + - IDs and names + - Timestamps and datetimes (months, days, years, seconds) + - File IDs, names, extensions, and mimetypes + - URLs, GIDs, etc. + - Should probe the tool's ability to return all useful forms of data + +9. **Questions should MOSTLY reflect real human use cases** + - The kinds of information retrieval tasks that HUMANS assisted by an LLM would care about + +10. **Questions may require dozens of tool calls** + - This challenges LLMs with limited context + - Encourages MCP server tools to reduce information returned + +11. **Include ambiguous questions** + - May be ambiguous OR require difficult decisions on which tools to call + - Force the LLM to potentially make mistakes or misinterpret + - Ensure that despite AMBIGUITY, there is STILL A SINGLE VERIFIABLE ANSWER + +### Stability + +12. **Questions must be designed so the answer DOES NOT CHANGE** + - Do not ask questions that rely on "current state" which is dynamic + - For example, do not count: + - Number of reactions to a post + - Number of replies to a thread + - Number of members in a channel + +13. **DO NOT let the MCP server RESTRICT the kinds of questions you create** + - Create challenging and complex questions + - Some may not be solvable with the available MCP server tools + - Questions may require specific output formats (datetime vs. epoch time, JSON vs. MARKDOWN) + - Questions may require dozens of tool calls to complete + +## Answer Guidelines + +### Verification + +1. **Answers must be VERIFIABLE via direct string comparison** + - If the answer can be re-written in many formats, clearly specify the output format in the QUESTION + - Examples: "Use YYYY/MM/DD.", "Respond True or False.", "Answer A, B, C, or D and nothing else." + - Answer should be a single VERIFIABLE value such as: + - User ID, user name, display name, first name, last name + - Channel ID, channel name + - Message ID, string + - URL, title + - Numerical quantity + - Timestamp, datetime + - Boolean (for True/False questions) + - Email address, phone number + - File ID, file name, file extension + - Multiple choice answer + - Answers must not require special formatting or complex, structured output + - Answer will be verified using DIRECT STRING COMPARISON + +### Readability + +2. **Answers should generally prefer HUMAN-READABLE formats** + - Examples: names, first name, last name, datetime, file name, message string, URL, yes/no, true/false, a/b/c/d + - Rather than opaque IDs (though IDs are acceptable) + - The VAST MAJORITY of answers should be human-readable + +### Stability + +3. **Answers must be STABLE/STATIONARY** + - Look at old content (e.g., conversations that have ended, projects that have launched, questions answered) + - Create QUESTIONS based on "closed" concepts that will always return the same answer + - Questions may ask to consider a fixed time window to insulate from non-stationary answers + - Rely on context UNLIKELY to change + - Example: if finding a paper name, be SPECIFIC enough so answer is not confused with papers published later + +4. **Answers must be CLEAR and UNAMBIGUOUS** + - Questions must be designed so there is a single, clear answer + - Answer can be derived from using the MCP server tools + +### Diversity + +5. **Answers must be DIVERSE** + - Answer should be a single VERIFIABLE value in diverse modalities and formats + - User concept: user ID, user name, display name, first name, last name, email address, phone number + - Channel concept: channel ID, channel name, channel topic + - Message concept: message ID, message string, timestamp, month, day, year + +6. **Answers must NOT be complex structures** + - Not a list of values + - Not a complex object + - Not a list of IDs or strings + - Not natural language text + - UNLESS the answer can be straightforwardly verified using DIRECT STRING COMPARISON + - And can be realistically reproduced + - It should be unlikely that an LLM would return the same list in any other order or format + +## Evaluation Process + +### Step 1: Documentation Inspection + +Read the documentation of the target API to understand: +- Available endpoints and functionality +- If ambiguity exists, fetch additional information from the web +- Parallelize this step AS MUCH AS POSSIBLE +- Ensure each subagent is ONLY examining documentation from the file system or on the web + +### Step 2: Tool Inspection + +List the tools available in the MCP server: +- Inspect the MCP server directly +- Understand input/output schemas, docstrings, and descriptions +- WITHOUT calling the tools themselves at this stage + +### Step 3: Developing Understanding + +Repeat steps 1 & 2 until you have a good understanding: +- Iterate multiple times +- Think about the kinds of tasks you want to create +- Refine your understanding +- At NO stage should you READ the code of the MCP server implementation itself +- Use your intuition and understanding to create reasonable, realistic, but VERY challenging tasks + +### Step 4: Read-Only Content Inspection + +After understanding the API and tools, USE the MCP server tools: +- Inspect content using READ-ONLY and NON-DESTRUCTIVE operations ONLY +- Goal: identify specific content (e.g., users, channels, messages, projects, tasks) for creating realistic questions +- Should NOT call any tools that modify state +- Will NOT read the code of the MCP server implementation itself +- Parallelize this step with individual sub-agents pursuing independent explorations +- Ensure each subagent is only performing READ-ONLY, NON-DESTRUCTIVE, and IDEMPOTENT operations +- BE CAREFUL: SOME TOOLS may return LOTS OF DATA which would cause you to run out of CONTEXT +- Make INCREMENTAL, SMALL, AND TARGETED tool calls for exploration +- In all tool call requests, use the `limit` parameter to limit results (<10) +- Use pagination + +### Step 5: Task Generation + +After inspecting the content, create 10 human-readable questions: +- An LLM should be able to answer these with the MCP server +- Follow all question and answer guidelines above + +## Output Format + +Each QA pair consists of a question and an answer. The output should be an XML file with this structure: + +```xml + + + Find the project created in Q2 2024 with the highest number of completed tasks. What is the project name? + Website Redesign + + + Search for issues labeled as "bug" that were closed in March 2024. Which user closed the most issues? Provide their username. + sarah_dev + + + Look for pull requests that modified files in the /api directory and were merged between January 1 and January 31, 2024. How many different contributors worked on these PRs? + 7 + + + Find the repository with the most stars that was created before 2023. What is the repository name? + data-pipeline + + +``` + +## Evaluation Examples + +### Good Questions + +**Example 1: Multi-hop question requiring deep exploration (GitHub MCP)** +```xml + + Find the repository that was archived in Q3 2023 and had previously been the most forked project in the organization. What was the primary programming language used in that repository? + Python + +``` + +This question is good because: +- Requires multiple searches to find archived repositories +- Needs to identify which had the most forks before archival +- Requires examining repository details for the language +- Answer is a simple, verifiable value +- Based on historical (closed) data that won't change + +**Example 2: Requires understanding context without keyword matching (Project Management MCP)** +```xml + + Locate the initiative focused on improving customer onboarding that was completed in late 2023. The project lead created a retrospective document after completion. What was the lead's role title at that time? + Product Manager + +``` + +This question is good because: +- Doesn't use specific project name ("initiative focused on improving customer onboarding") +- Requires finding completed projects from specific timeframe +- Needs to identify the project lead and their role +- Requires understanding context from retrospective documents +- Answer is human-readable and stable +- Based on completed work (won't change) + +**Example 3: Complex aggregation requiring multiple steps (Issue Tracker MCP)** +```xml + + Among all bugs reported in January 2024 that were marked as critical priority, which assignee resolved the highest percentage of their assigned bugs within 48 hours? Provide the assignee's username. + alex_eng + +``` + +This question is good because: +- Requires filtering bugs by date, priority, and status +- Needs to group by assignee and calculate resolution rates +- Requires understanding timestamps to determine 48-hour windows +- Tests pagination (potentially many bugs to process) +- Answer is a single username +- Based on historical data from specific time period + +**Example 4: Requires synthesis across multiple data types (CRM MCP)** +```xml + + Find the account that upgraded from the Starter to Enterprise plan in Q4 2023 and had the highest annual contract value. What industry does this account operate in? + Healthcare + +``` + +This question is good because: +- Requires understanding subscription tier changes +- Needs to identify upgrade events in specific timeframe +- Requires comparing contract values +- Must access account industry information +- Answer is simple and verifiable +- Based on completed historical transactions + +### Poor Questions + +**Example 1: Answer changes over time** +```xml + + How many open issues are currently assigned to the engineering team? + 47 + +``` + +This question is poor because: +- The answer will change as issues are created, closed, or reassigned +- Not based on stable/stationary data +- Relies on "current state" which is dynamic + +**Example 2: Too easy with keyword search** +```xml + + Find the pull request with title "Add authentication feature" and tell me who created it. + developer123 + +``` + +This question is poor because: +- Can be solved with a straightforward keyword search for exact title +- Doesn't require deep exploration or understanding +- No synthesis or analysis needed + +**Example 3: Ambiguous answer format** +```xml + + List all the repositories that have Python as their primary language. + repo1, repo2, repo3, data-pipeline, ml-tools + +``` + +This question is poor because: +- Answer is a list that could be returned in any order +- Difficult to verify with direct string comparison +- LLM might format differently (JSON array, comma-separated, newline-separated) +- Better to ask for a specific aggregate (count) or superlative (most stars) + +## Verification Process + +After creating evaluations: + +1. **Examine the XML file** to understand the schema +2. **Load each task instruction** and in parallel using the MCP server and tools, identify the correct answer by attempting to solve the task YOURSELF +3. **Flag any operations** that require WRITE or DESTRUCTIVE operations +4. **Accumulate all CORRECT answers** and replace any incorrect answers in the document +5. **Remove any ``** that require WRITE or DESTRUCTIVE operations + +Remember to parallelize solving tasks to avoid running out of context, then accumulate all answers and make changes to the file at the end. + +## Tips for Creating Quality Evaluations + +1. **Think Hard and Plan Ahead** before generating tasks +2. **Parallelize Where Opportunity Arises** to speed up the process and manage context +3. **Focus on Realistic Use Cases** that humans would actually want to accomplish +4. **Create Challenging Questions** that test the limits of the MCP server's capabilities +5. **Ensure Stability** by using historical data and closed concepts +6. **Verify Answers** by solving the questions yourself using the MCP server tools +7. **Iterate and Refine** based on what you learn during the process + +--- + +# Running Evaluations + +After creating your evaluation file, you can use the provided evaluation harness to test your MCP server. + +## Setup + +1. **Install Dependencies** + + ```bash + pip install -r scripts/requirements.txt + ``` + + Or install manually: + ```bash + pip install anthropic mcp + ``` + +2. **Set API Key** + + ```bash + export ANTHROPIC_API_KEY=your_api_key_here + ``` + +## Evaluation File Format + +Evaluation files use XML format with `` elements: + +```xml + + + Find the project created in Q2 2024 with the highest number of completed tasks. What is the project name? + Website Redesign + + + Search for issues labeled as "bug" that were closed in March 2024. Which user closed the most issues? Provide their username. + sarah_dev + + +``` + +## Running Evaluations + +The evaluation script (`scripts/evaluation.py`) supports three transport types: + +**Important:** +- **stdio transport**: The evaluation script automatically launches and manages the MCP server process for you. Do not run the server manually. +- **sse/http transports**: You must start the MCP server separately before running the evaluation. The script connects to the already-running server at the specified URL. + +### 1. Local STDIO Server + +For locally-run MCP servers (script launches the server automatically): + +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a my_mcp_server.py \ + evaluation.xml +``` + +With environment variables: +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a my_mcp_server.py \ + -e API_KEY=abc123 \ + -e DEBUG=true \ + evaluation.xml +``` + +### 2. Server-Sent Events (SSE) + +For SSE-based MCP servers (you must start the server first): + +```bash +python scripts/evaluation.py \ + -t sse \ + -u https://example.com/mcp \ + -H "Authorization: Bearer token123" \ + -H "X-Custom-Header: value" \ + evaluation.xml +``` + +### 3. HTTP (Streamable HTTP) + +For HTTP-based MCP servers (you must start the server first): + +```bash +python scripts/evaluation.py \ + -t http \ + -u https://example.com/mcp \ + -H "Authorization: Bearer token123" \ + evaluation.xml +``` + +## Command-Line Options + +``` +usage: evaluation.py [-h] [-t {stdio,sse,http}] [-m MODEL] [-c COMMAND] + [-a ARGS [ARGS ...]] [-e ENV [ENV ...]] [-u URL] + [-H HEADERS [HEADERS ...]] [-o OUTPUT] + eval_file + +positional arguments: + eval_file Path to evaluation XML file + +optional arguments: + -h, --help Show help message + -t, --transport Transport type: stdio, sse, or http (default: stdio) + -m, --model Claude model to use (default: claude-3-7-sonnet-20250219) + -o, --output Output file for report (default: print to stdout) + +stdio options: + -c, --command Command to run MCP server (e.g., python, node) + -a, --args Arguments for the command (e.g., server.py) + -e, --env Environment variables in KEY=VALUE format + +sse/http options: + -u, --url MCP server URL + -H, --header HTTP headers in 'Key: Value' format +``` + +## Output + +The evaluation script generates a detailed report including: + +- **Summary Statistics**: + - Accuracy (correct/total) + - Average task duration + - Average tool calls per task + - Total tool calls + +- **Per-Task Results**: + - Prompt and expected response + - Actual response from the agent + - Whether the answer was correct (✅/❌) + - Duration and tool call details + - Agent's summary of its approach + - Agent's feedback on the tools + +### Save Report to File + +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a my_server.py \ + -o evaluation_report.md \ + evaluation.xml +``` + +## Complete Example Workflow + +Here's a complete example of creating and running an evaluation: + +1. **Create your evaluation file** (`my_evaluation.xml`): + +```xml + + + Find the user who created the most issues in January 2024. What is their username? + alice_developer + + + Among all pull requests merged in Q1 2024, which repository had the highest number? Provide the repository name. + backend-api + + + Find the project that was completed in December 2023 and had the longest duration from start to finish. How many days did it take? + 127 + + +``` + +2. **Install dependencies**: + +```bash +pip install -r scripts/requirements.txt +export ANTHROPIC_API_KEY=your_api_key +``` + +3. **Run evaluation**: + +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a github_mcp_server.py \ + -e GITHUB_TOKEN=ghp_xxx \ + -o github_eval_report.md \ + my_evaluation.xml +``` + +4. **Review the report** in `github_eval_report.md` to: + - See which questions passed/failed + - Read the agent's feedback on your tools + - Identify areas for improvement + - Iterate on your MCP server design + +## Troubleshooting + +### Connection Errors + +If you get connection errors: +- **STDIO**: Verify the command and arguments are correct +- **SSE/HTTP**: Check the URL is accessible and headers are correct +- Ensure any required API keys are set in environment variables or headers + +### Low Accuracy + +If many evaluations fail: +- Review the agent's feedback for each task +- Check if tool descriptions are clear and comprehensive +- Verify input parameters are well-documented +- Consider whether tools return too much or too little data +- Ensure error messages are actionable + +### Timeout Issues + +If tasks are timing out: +- Use a more capable model (e.g., `claude-3-7-sonnet-20250219`) +- Check if tools are returning too much data +- Verify pagination is working correctly +- Consider simplifying complex questions diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/mcp_best_practices.md b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/mcp_best_practices.md new file mode 100644 index 00000000..b9d343cc --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/mcp_best_practices.md @@ -0,0 +1,249 @@ +# MCP Server Best Practices + +## Quick Reference + +### Server Naming +- **Python**: `{service}_mcp` (e.g., `slack_mcp`) +- **Node/TypeScript**: `{service}-mcp-server` (e.g., `slack-mcp-server`) + +### Tool Naming +- Use snake_case with service prefix +- Format: `{service}_{action}_{resource}` +- Example: `slack_send_message`, `github_create_issue` + +### Response Formats +- Support both JSON and Markdown formats +- JSON for programmatic processing +- Markdown for human readability + +### Pagination +- Always respect `limit` parameter +- Return `has_more`, `next_offset`, `total_count` +- Default to 20-50 items + +### Transport +- **Streamable HTTP**: For remote servers, multi-client scenarios +- **stdio**: For local integrations, command-line tools +- Avoid SSE (deprecated in favor of streamable HTTP) + +--- + +## Server Naming Conventions + +Follow these standardized naming patterns: + +**Python**: Use format `{service}_mcp` (lowercase with underscores) +- Examples: `slack_mcp`, `github_mcp`, `jira_mcp` + +**Node/TypeScript**: Use format `{service}-mcp-server` (lowercase with hyphens) +- Examples: `slack-mcp-server`, `github-mcp-server`, `jira-mcp-server` + +The name should be general, descriptive of the service being integrated, easy to infer from the task description, and without version numbers. + +--- + +## Tool Naming and Design + +### Tool Naming + +1. **Use snake_case**: `search_users`, `create_project`, `get_channel_info` +2. **Include service prefix**: Anticipate that your MCP server may be used alongside other MCP servers + - Use `slack_send_message` instead of just `send_message` + - Use `github_create_issue` instead of just `create_issue` +3. **Be action-oriented**: Start with verbs (get, list, search, create, etc.) +4. **Be specific**: Avoid generic names that could conflict with other servers + +### Tool Design + +- Tool descriptions must narrowly and unambiguously describe functionality +- Descriptions must precisely match actual functionality +- Provide tool annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) +- Keep tool operations focused and atomic + +--- + +## Response Formats + +All tools that return data should support multiple formats: + +### JSON Format (`response_format="json"`) +- Machine-readable structured data +- Include all available fields and metadata +- Consistent field names and types +- Use for programmatic processing + +### Markdown Format (`response_format="markdown"`, typically default) +- Human-readable formatted text +- Use headers, lists, and formatting for clarity +- Convert timestamps to human-readable format +- Show display names with IDs in parentheses +- Omit verbose metadata + +--- + +## Pagination + +For tools that list resources: + +- **Always respect the `limit` parameter** +- **Implement pagination**: Use `offset` or cursor-based pagination +- **Return pagination metadata**: Include `has_more`, `next_offset`/`next_cursor`, `total_count` +- **Never load all results into memory**: Especially important for large datasets +- **Default to reasonable limits**: 20-50 items is typical + +Example pagination response: +```json +{ + "total": 150, + "count": 20, + "offset": 0, + "items": [...], + "has_more": true, + "next_offset": 20 +} +``` + +--- + +## Transport Options + +### Streamable HTTP + +**Best for**: Remote servers, web services, multi-client scenarios + +**Characteristics**: +- Bidirectional communication over HTTP +- Supports multiple simultaneous clients +- Can be deployed as a web service +- Enables server-to-client notifications + +**Use when**: +- Serving multiple clients simultaneously +- Deploying as a cloud service +- Integration with web applications + +### stdio + +**Best for**: Local integrations, command-line tools + +**Characteristics**: +- Standard input/output stream communication +- Simple setup, no network configuration needed +- Runs as a subprocess of the client + +**Use when**: +- Building tools for local development environments +- Integrating with desktop applications +- Single-user, single-session scenarios + +**Note**: stdio servers should NOT log to stdout (use stderr for logging) + +### Transport Selection + +| Criterion | stdio | Streamable HTTP | +|-----------|-------|-----------------| +| **Deployment** | Local | Remote | +| **Clients** | Single | Multiple | +| **Complexity** | Low | Medium | +| **Real-time** | No | Yes | + +--- + +## Security Best Practices + +### Authentication and Authorization + +**OAuth 2.1**: +- Use secure OAuth 2.1 with certificates from recognized authorities +- Validate access tokens before processing requests +- Only accept tokens specifically intended for your server + +**API Keys**: +- Store API keys in environment variables, never in code +- Validate keys on server startup +- Provide clear error messages when authentication fails + +### Input Validation + +- Sanitize file paths to prevent directory traversal +- Validate URLs and external identifiers +- Check parameter sizes and ranges +- Prevent command injection in system calls +- Use schema validation (Pydantic/Zod) for all inputs + +### Error Handling + +- Don't expose internal errors to clients +- Log security-relevant errors server-side +- Provide helpful but not revealing error messages +- Clean up resources after errors + +### DNS Rebinding Protection + +For streamable HTTP servers running locally: +- Enable DNS rebinding protection +- Validate the `Origin` header on all incoming connections +- Bind to `127.0.0.1` rather than `0.0.0.0` + +--- + +## Tool Annotations + +Provide annotations to help clients understand tool behavior: + +| Annotation | Type | Default | Description | +|-----------|------|---------|-------------| +| `readOnlyHint` | boolean | false | Tool does not modify its environment | +| `destructiveHint` | boolean | true | Tool may perform destructive updates | +| `idempotentHint` | boolean | false | Repeated calls with same args have no additional effect | +| `openWorldHint` | boolean | true | Tool interacts with external entities | + +**Important**: Annotations are hints, not security guarantees. Clients should not make security-critical decisions based solely on annotations. + +--- + +## Error Handling + +- Use standard JSON-RPC error codes +- Report tool errors within result objects (not protocol-level errors) +- Provide helpful, specific error messages with suggested next steps +- Don't expose internal implementation details +- Clean up resources properly on errors + +Example error handling: +```typescript +try { + const result = performOperation(); + return { content: [{ type: "text", text: result }] }; +} catch (error) { + return { + isError: true, + content: [{ + type: "text", + text: `Error: ${error.message}. Try using filter='active_only' to reduce results.` + }] + }; +} +``` + +--- + +## Testing Requirements + +Comprehensive testing should cover: + +- **Functional testing**: Verify correct execution with valid/invalid inputs +- **Integration testing**: Test interaction with external systems +- **Security testing**: Validate auth, input sanitization, rate limiting +- **Performance testing**: Check behavior under load, timeouts +- **Error handling**: Ensure proper error reporting and cleanup + +--- + +## Documentation Requirements + +- Provide clear documentation of all tools and capabilities +- Include working examples (at least 3 per major feature) +- Document security considerations +- Specify required permissions and access levels +- Document rate limits and performance characteristics diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/node_mcp_server.md b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/node_mcp_server.md new file mode 100644 index 00000000..bc5561d4 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/node_mcp_server.md @@ -0,0 +1,970 @@ +# Node/TypeScript MCP Server Implementation Guide + +## Overview + +This document provides Node/TypeScript-specific best practices and examples for implementing MCP servers using the MCP TypeScript SDK. It covers project structure, server setup, tool registration patterns, input validation with Zod, error handling, and complete working examples. + +--- + +## Quick Reference + +### Key Imports +```typescript +import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; +import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js"; +import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; +import express from "express"; +import { z } from "zod"; +``` + +### Server Initialization +```typescript +const server = new McpServer({ + name: "service-mcp-server", + version: "1.0.0" +}); +``` + +### Tool Registration Pattern +```typescript +server.registerTool( + "tool_name", + { + title: "Tool Display Name", + description: "What the tool does", + inputSchema: { param: z.string() }, + outputSchema: { result: z.string() } + }, + async ({ param }) => { + const output = { result: `Processed: ${param}` }; + return { + content: [{ type: "text", text: JSON.stringify(output) }], + structuredContent: output // Modern pattern for structured data + }; + } +); +``` + +--- + +## MCP TypeScript SDK + +The official MCP TypeScript SDK provides: +- `McpServer` class for server initialization +- `registerTool` method for tool registration +- Zod schema integration for runtime input validation +- Type-safe tool handler implementations + +**IMPORTANT - Use Modern APIs Only:** +- **DO use**: `server.registerTool()`, `server.registerResource()`, `server.registerPrompt()` +- **DO NOT use**: Old deprecated APIs such as `server.tool()`, `server.setRequestHandler(ListToolsRequestSchema, ...)`, or manual handler registration +- The `register*` methods provide better type safety, automatic schema handling, and are the recommended approach + +See the MCP SDK documentation in the references for complete details. + +## Server Naming Convention + +Node/TypeScript MCP servers must follow this naming pattern: +- **Format**: `{service}-mcp-server` (lowercase with hyphens) +- **Examples**: `github-mcp-server`, `jira-mcp-server`, `stripe-mcp-server` + +The name should be: +- General (not tied to specific features) +- Descriptive of the service/API being integrated +- Easy to infer from the task description +- Without version numbers or dates + +## Project Structure + +Create the following structure for Node/TypeScript MCP servers: + +``` +{service}-mcp-server/ +├── package.json +├── tsconfig.json +├── README.md +├── src/ +│ ├── index.ts # Main entry point with McpServer initialization +│ ├── types.ts # TypeScript type definitions and interfaces +│ ├── tools/ # Tool implementations (one file per domain) +│ ├── services/ # API clients and shared utilities +│ ├── schemas/ # Zod validation schemas +│ └── constants.ts # Shared constants (API_URL, CHARACTER_LIMIT, etc.) +└── dist/ # Built JavaScript files (entry point: dist/index.js) +``` + +## Tool Implementation + +### Tool Naming + +Use snake_case for tool names (e.g., "search_users", "create_project", "get_channel_info") with clear, action-oriented names. + +**Avoid Naming Conflicts**: Include the service context to prevent overlaps: +- Use "slack_send_message" instead of just "send_message" +- Use "github_create_issue" instead of just "create_issue" +- Use "asana_list_tasks" instead of just "list_tasks" + +### Tool Structure + +Tools are registered using the `registerTool` method with the following requirements: +- Use Zod schemas for runtime input validation and type safety +- The `description` field must be explicitly provided - JSDoc comments are NOT automatically extracted +- Explicitly provide `title`, `description`, `inputSchema`, and `annotations` +- The `inputSchema` must be a Zod schema object (not a JSON schema) +- Type all parameters and return values explicitly + +```typescript +import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; +import { z } from "zod"; + +const server = new McpServer({ + name: "example-mcp", + version: "1.0.0" +}); + +// Zod schema for input validation +const UserSearchInputSchema = z.object({ + query: z.string() + .min(2, "Query must be at least 2 characters") + .max(200, "Query must not exceed 200 characters") + .describe("Search string to match against names/emails"), + limit: z.number() + .int() + .min(1) + .max(100) + .default(20) + .describe("Maximum results to return"), + offset: z.number() + .int() + .min(0) + .default(0) + .describe("Number of results to skip for pagination"), + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format: 'markdown' for human-readable or 'json' for machine-readable") +}).strict(); + +// Type definition from Zod schema +type UserSearchInput = z.infer; + +server.registerTool( + "example_search_users", + { + title: "Search Example Users", + description: `Search for users in the Example system by name, email, or team. + +This tool searches across all user profiles in the Example platform, supporting partial matches and various search filters. It does NOT create or modify users, only searches existing ones. + +Args: + - query (string): Search string to match against names/emails + - limit (number): Maximum results to return, between 1-100 (default: 20) + - offset (number): Number of results to skip for pagination (default: 0) + - response_format ('markdown' | 'json'): Output format (default: 'markdown') + +Returns: + For JSON format: Structured data with schema: + { + "total": number, // Total number of matches found + "count": number, // Number of results in this response + "offset": number, // Current pagination offset + "users": [ + { + "id": string, // User ID (e.g., "U123456789") + "name": string, // Full name (e.g., "John Doe") + "email": string, // Email address + "team": string, // Team name (optional) + "active": boolean // Whether user is active + } + ], + "has_more": boolean, // Whether more results are available + "next_offset": number // Offset for next page (if has_more is true) + } + +Examples: + - Use when: "Find all marketing team members" -> params with query="team:marketing" + - Use when: "Search for John's account" -> params with query="john" + - Don't use when: You need to create a user (use example_create_user instead) + +Error Handling: + - Returns "Error: Rate limit exceeded" if too many requests (429 status) + - Returns "No users found matching ''" if search returns empty`, + inputSchema: UserSearchInputSchema, + annotations: { + readOnlyHint: true, + destructiveHint: false, + idempotentHint: true, + openWorldHint: true + } + }, + async (params: UserSearchInput) => { + try { + // Input validation is handled by Zod schema + // Make API request using validated parameters + const data = await makeApiRequest( + "users/search", + "GET", + undefined, + { + q: params.query, + limit: params.limit, + offset: params.offset + } + ); + + const users = data.users || []; + const total = data.total || 0; + + if (!users.length) { + return { + content: [{ + type: "text", + text: `No users found matching '${params.query}'` + }] + }; + } + + // Prepare structured output + const output = { + total, + count: users.length, + offset: params.offset, + users: users.map((user: any) => ({ + id: user.id, + name: user.name, + email: user.email, + ...(user.team ? { team: user.team } : {}), + active: user.active ?? true + })), + has_more: total > params.offset + users.length, + ...(total > params.offset + users.length ? { + next_offset: params.offset + users.length + } : {}) + }; + + // Format text representation based on requested format + let textContent: string; + if (params.response_format === ResponseFormat.MARKDOWN) { + const lines = [`# User Search Results: '${params.query}'`, "", + `Found ${total} users (showing ${users.length})`, ""]; + for (const user of users) { + lines.push(`## ${user.name} (${user.id})`); + lines.push(`- **Email**: ${user.email}`); + if (user.team) lines.push(`- **Team**: ${user.team}`); + lines.push(""); + } + textContent = lines.join("\n"); + } else { + textContent = JSON.stringify(output, null, 2); + } + + return { + content: [{ type: "text", text: textContent }], + structuredContent: output // Modern pattern for structured data + }; + } catch (error) { + return { + content: [{ + type: "text", + text: handleApiError(error) + }] + }; + } + } +); +``` + +## Zod Schemas for Input Validation + +Zod provides runtime type validation: + +```typescript +import { z } from "zod"; + +// Basic schema with validation +const CreateUserSchema = z.object({ + name: z.string() + .min(1, "Name is required") + .max(100, "Name must not exceed 100 characters"), + email: z.string() + .email("Invalid email format"), + age: z.number() + .int("Age must be a whole number") + .min(0, "Age cannot be negative") + .max(150, "Age cannot be greater than 150") +}).strict(); // Use .strict() to forbid extra fields + +// Enums +enum ResponseFormat { + MARKDOWN = "markdown", + JSON = "json" +} + +const SearchSchema = z.object({ + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format") +}); + +// Optional fields with defaults +const PaginationSchema = z.object({ + limit: z.number() + .int() + .min(1) + .max(100) + .default(20) + .describe("Maximum results to return"), + offset: z.number() + .int() + .min(0) + .default(0) + .describe("Number of results to skip") +}); +``` + +## Response Format Options + +Support multiple output formats for flexibility: + +```typescript +enum ResponseFormat { + MARKDOWN = "markdown", + JSON = "json" +} + +const inputSchema = z.object({ + query: z.string(), + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format: 'markdown' for human-readable or 'json' for machine-readable") +}); +``` + +**Markdown format**: +- Use headers, lists, and formatting for clarity +- Convert timestamps to human-readable format +- Show display names with IDs in parentheses +- Omit verbose metadata +- Group related information logically + +**JSON format**: +- Return complete, structured data suitable for programmatic processing +- Include all available fields and metadata +- Use consistent field names and types + +## Pagination Implementation + +For tools that list resources: + +```typescript +const ListSchema = z.object({ + limit: z.number().int().min(1).max(100).default(20), + offset: z.number().int().min(0).default(0) +}); + +async function listItems(params: z.infer) { + const data = await apiRequest(params.limit, params.offset); + + const response = { + total: data.total, + count: data.items.length, + offset: params.offset, + items: data.items, + has_more: data.total > params.offset + data.items.length, + next_offset: data.total > params.offset + data.items.length + ? params.offset + data.items.length + : undefined + }; + + return JSON.stringify(response, null, 2); +} +``` + +## Character Limits and Truncation + +Add a CHARACTER_LIMIT constant to prevent overwhelming responses: + +```typescript +// At module level in constants.ts +export const CHARACTER_LIMIT = 25000; // Maximum response size in characters + +async function searchTool(params: SearchInput) { + let result = generateResponse(data); + + // Check character limit and truncate if needed + if (result.length > CHARACTER_LIMIT) { + const truncatedData = data.slice(0, Math.max(1, data.length / 2)); + response.data = truncatedData; + response.truncated = true; + response.truncation_message = + `Response truncated from ${data.length} to ${truncatedData.length} items. ` + + `Use 'offset' parameter or add filters to see more results.`; + result = JSON.stringify(response, null, 2); + } + + return result; +} +``` + +## Error Handling + +Provide clear, actionable error messages: + +```typescript +import axios, { AxiosError } from "axios"; + +function handleApiError(error: unknown): string { + if (error instanceof AxiosError) { + if (error.response) { + switch (error.response.status) { + case 404: + return "Error: Resource not found. Please check the ID is correct."; + case 403: + return "Error: Permission denied. You don't have access to this resource."; + case 429: + return "Error: Rate limit exceeded. Please wait before making more requests."; + default: + return `Error: API request failed with status ${error.response.status}`; + } + } else if (error.code === "ECONNABORTED") { + return "Error: Request timed out. Please try again."; + } + } + return `Error: Unexpected error occurred: ${error instanceof Error ? error.message : String(error)}`; +} +``` + +## Shared Utilities + +Extract common functionality into reusable functions: + +```typescript +// Shared API request function +async function makeApiRequest( + endpoint: string, + method: "GET" | "POST" | "PUT" | "DELETE" = "GET", + data?: any, + params?: any +): Promise { + try { + const response = await axios({ + method, + url: `${API_BASE_URL}/${endpoint}`, + data, + params, + timeout: 30000, + headers: { + "Content-Type": "application/json", + "Accept": "application/json" + } + }); + return response.data; + } catch (error) { + throw error; + } +} +``` + +## Async/Await Best Practices + +Always use async/await for network requests and I/O operations: + +```typescript +// Good: Async network request +async function fetchData(resourceId: string): Promise { + const response = await axios.get(`${API_URL}/resource/${resourceId}`); + return response.data; +} + +// Bad: Promise chains +function fetchData(resourceId: string): Promise { + return axios.get(`${API_URL}/resource/${resourceId}`) + .then(response => response.data); // Harder to read and maintain +} +``` + +## TypeScript Best Practices + +1. **Use Strict TypeScript**: Enable strict mode in tsconfig.json +2. **Define Interfaces**: Create clear interface definitions for all data structures +3. **Avoid `any`**: Use proper types or `unknown` instead of `any` +4. **Zod for Runtime Validation**: Use Zod schemas to validate external data +5. **Type Guards**: Create type guard functions for complex type checking +6. **Error Handling**: Always use try-catch with proper error type checking +7. **Null Safety**: Use optional chaining (`?.`) and nullish coalescing (`??`) + +```typescript +// Good: Type-safe with Zod and interfaces +interface UserResponse { + id: string; + name: string; + email: string; + team?: string; + active: boolean; +} + +const UserSchema = z.object({ + id: z.string(), + name: z.string(), + email: z.string().email(), + team: z.string().optional(), + active: z.boolean() +}); + +type User = z.infer; + +async function getUser(id: string): Promise { + const data = await apiCall(`/users/${id}`); + return UserSchema.parse(data); // Runtime validation +} + +// Bad: Using any +async function getUser(id: string): Promise { + return await apiCall(`/users/${id}`); // No type safety +} +``` + +## Package Configuration + +### package.json + +```json +{ + "name": "{service}-mcp-server", + "version": "1.0.0", + "description": "MCP server for {Service} API integration", + "type": "module", + "main": "dist/index.js", + "scripts": { + "start": "node dist/index.js", + "dev": "tsx watch src/index.ts", + "build": "tsc", + "clean": "rm -rf dist" + }, + "engines": { + "node": ">=18" + }, + "dependencies": { + "@modelcontextprotocol/sdk": "^1.6.1", + "axios": "^1.7.9", + "zod": "^3.23.8" + }, + "devDependencies": { + "@types/node": "^22.10.0", + "tsx": "^4.19.2", + "typescript": "^5.7.2" + } +} +``` + +### tsconfig.json + +```json +{ + "compilerOptions": { + "target": "ES2022", + "module": "Node16", + "moduleResolution": "Node16", + "lib": ["ES2022"], + "outDir": "./dist", + "rootDir": "./src", + "strict": true, + "esModuleInterop": true, + "skipLibCheck": true, + "forceConsistentCasingInFileNames": true, + "declaration": true, + "declarationMap": true, + "sourceMap": true, + "allowSyntheticDefaultImports": true + }, + "include": ["src/**/*"], + "exclude": ["node_modules", "dist"] +} +``` + +## Complete Example + +```typescript +#!/usr/bin/env node +/** + * MCP Server for Example Service. + * + * This server provides tools to interact with Example API, including user search, + * project management, and data export capabilities. + */ + +import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; +import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; +import { z } from "zod"; +import axios, { AxiosError } from "axios"; + +// Constants +const API_BASE_URL = "https://api.example.com/v1"; +const CHARACTER_LIMIT = 25000; + +// Enums +enum ResponseFormat { + MARKDOWN = "markdown", + JSON = "json" +} + +// Zod schemas +const UserSearchInputSchema = z.object({ + query: z.string() + .min(2, "Query must be at least 2 characters") + .max(200, "Query must not exceed 200 characters") + .describe("Search string to match against names/emails"), + limit: z.number() + .int() + .min(1) + .max(100) + .default(20) + .describe("Maximum results to return"), + offset: z.number() + .int() + .min(0) + .default(0) + .describe("Number of results to skip for pagination"), + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format: 'markdown' for human-readable or 'json' for machine-readable") +}).strict(); + +type UserSearchInput = z.infer; + +// Shared utility functions +async function makeApiRequest( + endpoint: string, + method: "GET" | "POST" | "PUT" | "DELETE" = "GET", + data?: any, + params?: any +): Promise { + try { + const response = await axios({ + method, + url: `${API_BASE_URL}/${endpoint}`, + data, + params, + timeout: 30000, + headers: { + "Content-Type": "application/json", + "Accept": "application/json" + } + }); + return response.data; + } catch (error) { + throw error; + } +} + +function handleApiError(error: unknown): string { + if (error instanceof AxiosError) { + if (error.response) { + switch (error.response.status) { + case 404: + return "Error: Resource not found. Please check the ID is correct."; + case 403: + return "Error: Permission denied. You don't have access to this resource."; + case 429: + return "Error: Rate limit exceeded. Please wait before making more requests."; + default: + return `Error: API request failed with status ${error.response.status}`; + } + } else if (error.code === "ECONNABORTED") { + return "Error: Request timed out. Please try again."; + } + } + return `Error: Unexpected error occurred: ${error instanceof Error ? error.message : String(error)}`; +} + +// Create MCP server instance +const server = new McpServer({ + name: "example-mcp", + version: "1.0.0" +}); + +// Register tools +server.registerTool( + "example_search_users", + { + title: "Search Example Users", + description: `[Full description as shown above]`, + inputSchema: UserSearchInputSchema, + annotations: { + readOnlyHint: true, + destructiveHint: false, + idempotentHint: true, + openWorldHint: true + } + }, + async (params: UserSearchInput) => { + // Implementation as shown above + } +); + +// Main function +// For stdio (local): +async function runStdio() { + if (!process.env.EXAMPLE_API_KEY) { + console.error("ERROR: EXAMPLE_API_KEY environment variable is required"); + process.exit(1); + } + + const transport = new StdioServerTransport(); + await server.connect(transport); + console.error("MCP server running via stdio"); +} + +// For streamable HTTP (remote): +async function runHTTP() { + if (!process.env.EXAMPLE_API_KEY) { + console.error("ERROR: EXAMPLE_API_KEY environment variable is required"); + process.exit(1); + } + + const app = express(); + app.use(express.json()); + + app.post('/mcp', async (req, res) => { + const transport = new StreamableHTTPServerTransport({ + sessionIdGenerator: undefined, + enableJsonResponse: true + }); + res.on('close', () => transport.close()); + await server.connect(transport); + await transport.handleRequest(req, res, req.body); + }); + + const port = parseInt(process.env.PORT || '3000'); + app.listen(port, () => { + console.error(`MCP server running on http://localhost:${port}/mcp`); + }); +} + +// Choose transport based on environment +const transport = process.env.TRANSPORT || 'stdio'; +if (transport === 'http') { + runHTTP().catch(error => { + console.error("Server error:", error); + process.exit(1); + }); +} else { + runStdio().catch(error => { + console.error("Server error:", error); + process.exit(1); + }); +} +``` + +--- + +## Advanced MCP Features + +### Resource Registration + +Expose data as resources for efficient, URI-based access: + +```typescript +import { ResourceTemplate } from "@modelcontextprotocol/sdk/types.js"; + +// Register a resource with URI template +server.registerResource( + { + uri: "file://documents/{name}", + name: "Document Resource", + description: "Access documents by name", + mimeType: "text/plain" + }, + async (uri: string) => { + // Extract parameter from URI + const match = uri.match(/^file:\/\/documents\/(.+)$/); + if (!match) { + throw new Error("Invalid URI format"); + } + + const documentName = match[1]; + const content = await loadDocument(documentName); + + return { + contents: [{ + uri, + mimeType: "text/plain", + text: content + }] + }; + } +); + +// List available resources dynamically +server.registerResourceList(async () => { + const documents = await getAvailableDocuments(); + return { + resources: documents.map(doc => ({ + uri: `file://documents/${doc.name}`, + name: doc.name, + mimeType: "text/plain", + description: doc.description + })) + }; +}); +``` + +**When to use Resources vs Tools:** +- **Resources**: For data access with simple URI-based parameters +- **Tools**: For complex operations requiring validation and business logic +- **Resources**: When data is relatively static or template-based +- **Tools**: When operations have side effects or complex workflows + +### Transport Options + +The TypeScript SDK supports two main transport mechanisms: + +#### Streamable HTTP (Recommended for Remote Servers) + +```typescript +import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js"; +import express from "express"; + +const app = express(); +app.use(express.json()); + +app.post('/mcp', async (req, res) => { + // Create new transport for each request (stateless, prevents request ID collisions) + const transport = new StreamableHTTPServerTransport({ + sessionIdGenerator: undefined, + enableJsonResponse: true + }); + + res.on('close', () => transport.close()); + + await server.connect(transport); + await transport.handleRequest(req, res, req.body); +}); + +app.listen(3000); +``` + +#### stdio (For Local Integrations) + +```typescript +import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; + +const transport = new StdioServerTransport(); +await server.connect(transport); +``` + +**Transport selection:** +- **Streamable HTTP**: Web services, remote access, multiple clients +- **stdio**: Command-line tools, local development, subprocess integration + +### Notification Support + +Notify clients when server state changes: + +```typescript +// Notify when tools list changes +server.notification({ + method: "notifications/tools/list_changed" +}); + +// Notify when resources change +server.notification({ + method: "notifications/resources/list_changed" +}); +``` + +Use notifications sparingly - only when server capabilities genuinely change. + +--- + +## Code Best Practices + +### Code Composability and Reusability + +Your implementation MUST prioritize composability and code reuse: + +1. **Extract Common Functionality**: + - Create reusable helper functions for operations used across multiple tools + - Build shared API clients for HTTP requests instead of duplicating code + - Centralize error handling logic in utility functions + - Extract business logic into dedicated functions that can be composed + - Extract shared markdown or JSON field selection & formatting functionality + +2. **Avoid Duplication**: + - NEVER copy-paste similar code between tools + - If you find yourself writing similar logic twice, extract it into a function + - Common operations like pagination, filtering, field selection, and formatting should be shared + - Authentication/authorization logic should be centralized + +## Building and Running + +Always build your TypeScript code before running: + +```bash +# Build the project +npm run build + +# Run the server +npm start + +# Development with auto-reload +npm run dev +``` + +Always ensure `npm run build` completes successfully before considering the implementation complete. + +## Quality Checklist + +Before finalizing your Node/TypeScript MCP server implementation, ensure: + +### Strategic Design +- [ ] Tools enable complete workflows, not just API endpoint wrappers +- [ ] Tool names reflect natural task subdivisions +- [ ] Response formats optimize for agent context efficiency +- [ ] Human-readable identifiers used where appropriate +- [ ] Error messages guide agents toward correct usage + +### Implementation Quality +- [ ] FOCUSED IMPLEMENTATION: Most important and valuable tools implemented +- [ ] All tools registered using `registerTool` with complete configuration +- [ ] All tools include `title`, `description`, `inputSchema`, and `annotations` +- [ ] Annotations correctly set (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) +- [ ] All tools use Zod schemas for runtime input validation with `.strict()` enforcement +- [ ] All Zod schemas have proper constraints and descriptive error messages +- [ ] All tools have comprehensive descriptions with explicit input/output types +- [ ] Descriptions include return value examples and complete schema documentation +- [ ] Error messages are clear, actionable, and educational + +### TypeScript Quality +- [ ] TypeScript interfaces are defined for all data structures +- [ ] Strict TypeScript is enabled in tsconfig.json +- [ ] No use of `any` type - use `unknown` or proper types instead +- [ ] All async functions have explicit Promise return types +- [ ] Error handling uses proper type guards (e.g., `axios.isAxiosError`, `z.ZodError`) + +### Advanced Features (where applicable) +- [ ] Resources registered for appropriate data endpoints +- [ ] Appropriate transport configured (stdio or streamable HTTP) +- [ ] Notifications implemented for dynamic server capabilities +- [ ] Type-safe with SDK interfaces + +### Project Configuration +- [ ] Package.json includes all necessary dependencies +- [ ] Build script produces working JavaScript in dist/ directory +- [ ] Main entry point is properly configured as dist/index.js +- [ ] Server name follows format: `{service}-mcp-server` +- [ ] tsconfig.json properly configured with strict mode + +### Code Quality +- [ ] Pagination is properly implemented where applicable +- [ ] Large responses check CHARACTER_LIMIT constant and truncate with clear messages +- [ ] Filtering options are provided for potentially large result sets +- [ ] All network operations handle timeouts and connection errors gracefully +- [ ] Common functionality is extracted into reusable functions +- [ ] Return types are consistent across similar operations + +### Testing and Build +- [ ] `npm run build` completes successfully without errors +- [ ] dist/index.js created and executable +- [ ] Server runs: `node dist/index.js --help` +- [ ] All imports resolve correctly +- [ ] Sample tool calls work as expected diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/python_mcp_server.md b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/python_mcp_server.md new file mode 100644 index 00000000..a8332ff3 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/reference/python_mcp_server.md @@ -0,0 +1,719 @@ +# Python MCP Server Implementation Guide + +## Overview + +This document provides Python-specific best practices and examples for implementing MCP servers using the MCP Python SDK. It covers server setup, tool registration patterns, input validation with Pydantic, error handling, and complete working examples. + +--- + +## Quick Reference + +### Key Imports +```python +from mcp.server.fastmcp import FastMCP +from pydantic import BaseModel, Field, field_validator, ConfigDict +from typing import Optional, List, Dict, Any +from enum import Enum +import httpx +``` + +### Server Initialization +```python +mcp = FastMCP("service_mcp") +``` + +### Tool Registration Pattern +```python +@mcp.tool(name="tool_name", annotations={...}) +async def tool_function(params: InputModel) -> str: + # Implementation + pass +``` + +--- + +## MCP Python SDK and FastMCP + +The official MCP Python SDK provides FastMCP, a high-level framework for building MCP servers. It provides: +- Automatic description and inputSchema generation from function signatures and docstrings +- Pydantic model integration for input validation +- Decorator-based tool registration with `@mcp.tool` + +**For complete SDK documentation, use WebFetch to load:** +`https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` + +## Server Naming Convention + +Python MCP servers must follow this naming pattern: +- **Format**: `{service}_mcp` (lowercase with underscores) +- **Examples**: `github_mcp`, `jira_mcp`, `stripe_mcp` + +The name should be: +- General (not tied to specific features) +- Descriptive of the service/API being integrated +- Easy to infer from the task description +- Without version numbers or dates + +## Tool Implementation + +### Tool Naming + +Use snake_case for tool names (e.g., "search_users", "create_project", "get_channel_info") with clear, action-oriented names. + +**Avoid Naming Conflicts**: Include the service context to prevent overlaps: +- Use "slack_send_message" instead of just "send_message" +- Use "github_create_issue" instead of just "create_issue" +- Use "asana_list_tasks" instead of just "list_tasks" + +### Tool Structure with FastMCP + +Tools are defined using the `@mcp.tool` decorator with Pydantic models for input validation: + +```python +from pydantic import BaseModel, Field, ConfigDict +from mcp.server.fastmcp import FastMCP + +# Initialize the MCP server +mcp = FastMCP("example_mcp") + +# Define Pydantic model for input validation +class ServiceToolInput(BaseModel): + '''Input model for service tool operation.''' + model_config = ConfigDict( + str_strip_whitespace=True, # Auto-strip whitespace from strings + validate_assignment=True, # Validate on assignment + extra='forbid' # Forbid extra fields + ) + + param1: str = Field(..., description="First parameter description (e.g., 'user123', 'project-abc')", min_length=1, max_length=100) + param2: Optional[int] = Field(default=None, description="Optional integer parameter with constraints", ge=0, le=1000) + tags: Optional[List[str]] = Field(default_factory=list, description="List of tags to apply", max_items=10) + +@mcp.tool( + name="service_tool_name", + annotations={ + "title": "Human-Readable Tool Title", + "readOnlyHint": True, # Tool does not modify environment + "destructiveHint": False, # Tool does not perform destructive operations + "idempotentHint": True, # Repeated calls have no additional effect + "openWorldHint": False # Tool does not interact with external entities + } +) +async def service_tool_name(params: ServiceToolInput) -> str: + '''Tool description automatically becomes the 'description' field. + + This tool performs a specific operation on the service. It validates all inputs + using the ServiceToolInput Pydantic model before processing. + + Args: + params (ServiceToolInput): Validated input parameters containing: + - param1 (str): First parameter description + - param2 (Optional[int]): Optional parameter with default + - tags (Optional[List[str]]): List of tags + + Returns: + str: JSON-formatted response containing operation results + ''' + # Implementation here + pass +``` + +## Pydantic v2 Key Features + +- Use `model_config` instead of nested `Config` class +- Use `field_validator` instead of deprecated `validator` +- Use `model_dump()` instead of deprecated `dict()` +- Validators require `@classmethod` decorator +- Type hints are required for validator methods + +```python +from pydantic import BaseModel, Field, field_validator, ConfigDict + +class CreateUserInput(BaseModel): + model_config = ConfigDict( + str_strip_whitespace=True, + validate_assignment=True + ) + + name: str = Field(..., description="User's full name", min_length=1, max_length=100) + email: str = Field(..., description="User's email address", pattern=r'^[\w\.-]+@[\w\.-]+\.\w+$') + age: int = Field(..., description="User's age", ge=0, le=150) + + @field_validator('email') + @classmethod + def validate_email(cls, v: str) -> str: + if not v.strip(): + raise ValueError("Email cannot be empty") + return v.lower() +``` + +## Response Format Options + +Support multiple output formats for flexibility: + +```python +from enum import Enum + +class ResponseFormat(str, Enum): + '''Output format for tool responses.''' + MARKDOWN = "markdown" + JSON = "json" + +class UserSearchInput(BaseModel): + query: str = Field(..., description="Search query") + response_format: ResponseFormat = Field( + default=ResponseFormat.MARKDOWN, + description="Output format: 'markdown' for human-readable or 'json' for machine-readable" + ) +``` + +**Markdown format**: +- Use headers, lists, and formatting for clarity +- Convert timestamps to human-readable format (e.g., "2024-01-15 10:30:00 UTC" instead of epoch) +- Show display names with IDs in parentheses (e.g., "@john.doe (U123456)") +- Omit verbose metadata (e.g., show only one profile image URL, not all sizes) +- Group related information logically + +**JSON format**: +- Return complete, structured data suitable for programmatic processing +- Include all available fields and metadata +- Use consistent field names and types + +## Pagination Implementation + +For tools that list resources: + +```python +class ListInput(BaseModel): + limit: Optional[int] = Field(default=20, description="Maximum results to return", ge=1, le=100) + offset: Optional[int] = Field(default=0, description="Number of results to skip for pagination", ge=0) + +async def list_items(params: ListInput) -> str: + # Make API request with pagination + data = await api_request(limit=params.limit, offset=params.offset) + + # Return pagination info + response = { + "total": data["total"], + "count": len(data["items"]), + "offset": params.offset, + "items": data["items"], + "has_more": data["total"] > params.offset + len(data["items"]), + "next_offset": params.offset + len(data["items"]) if data["total"] > params.offset + len(data["items"]) else None + } + return json.dumps(response, indent=2) +``` + +## Error Handling + +Provide clear, actionable error messages: + +```python +def _handle_api_error(e: Exception) -> str: + '''Consistent error formatting across all tools.''' + if isinstance(e, httpx.HTTPStatusError): + if e.response.status_code == 404: + return "Error: Resource not found. Please check the ID is correct." + elif e.response.status_code == 403: + return "Error: Permission denied. You don't have access to this resource." + elif e.response.status_code == 429: + return "Error: Rate limit exceeded. Please wait before making more requests." + return f"Error: API request failed with status {e.response.status_code}" + elif isinstance(e, httpx.TimeoutException): + return "Error: Request timed out. Please try again." + return f"Error: Unexpected error occurred: {type(e).__name__}" +``` + +## Shared Utilities + +Extract common functionality into reusable functions: + +```python +# Shared API request function +async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict: + '''Reusable function for all API calls.''' + async with httpx.AsyncClient() as client: + response = await client.request( + method, + f"{API_BASE_URL}/{endpoint}", + timeout=30.0, + **kwargs + ) + response.raise_for_status() + return response.json() +``` + +## Async/Await Best Practices + +Always use async/await for network requests and I/O operations: + +```python +# Good: Async network request +async def fetch_data(resource_id: str) -> dict: + async with httpx.AsyncClient() as client: + response = await client.get(f"{API_URL}/resource/{resource_id}") + response.raise_for_status() + return response.json() + +# Bad: Synchronous request +def fetch_data(resource_id: str) -> dict: + response = requests.get(f"{API_URL}/resource/{resource_id}") # Blocks + return response.json() +``` + +## Type Hints + +Use type hints throughout: + +```python +from typing import Optional, List, Dict, Any + +async def get_user(user_id: str) -> Dict[str, Any]: + data = await fetch_user(user_id) + return {"id": data["id"], "name": data["name"]} +``` + +## Tool Docstrings + +Every tool must have comprehensive docstrings with explicit type information: + +```python +async def search_users(params: UserSearchInput) -> str: + ''' + Search for users in the Example system by name, email, or team. + + This tool searches across all user profiles in the Example platform, + supporting partial matches and various search filters. It does NOT + create or modify users, only searches existing ones. + + Args: + params (UserSearchInput): Validated input parameters containing: + - query (str): Search string to match against names/emails (e.g., "john", "@example.com", "team:marketing") + - limit (Optional[int]): Maximum results to return, between 1-100 (default: 20) + - offset (Optional[int]): Number of results to skip for pagination (default: 0) + + Returns: + str: JSON-formatted string containing search results with the following schema: + + Success response: + { + "total": int, # Total number of matches found + "count": int, # Number of results in this response + "offset": int, # Current pagination offset + "users": [ + { + "id": str, # User ID (e.g., "U123456789") + "name": str, # Full name (e.g., "John Doe") + "email": str, # Email address (e.g., "john@example.com") + "team": str # Team name (e.g., "Marketing") - optional + } + ] + } + + Error response: + "Error: " or "No users found matching ''" + + Examples: + - Use when: "Find all marketing team members" -> params with query="team:marketing" + - Use when: "Search for John's account" -> params with query="john" + - Don't use when: You need to create a user (use example_create_user instead) + - Don't use when: You have a user ID and need full details (use example_get_user instead) + + Error Handling: + - Input validation errors are handled by Pydantic model + - Returns "Error: Rate limit exceeded" if too many requests (429 status) + - Returns "Error: Invalid API authentication" if API key is invalid (401 status) + - Returns formatted list of results or "No users found matching 'query'" + ''' +``` + +## Complete Example + +See below for a complete Python MCP server example: + +```python +#!/usr/bin/env python3 +''' +MCP Server for Example Service. + +This server provides tools to interact with Example API, including user search, +project management, and data export capabilities. +''' + +from typing import Optional, List, Dict, Any +from enum import Enum +import httpx +from pydantic import BaseModel, Field, field_validator, ConfigDict +from mcp.server.fastmcp import FastMCP + +# Initialize the MCP server +mcp = FastMCP("example_mcp") + +# Constants +API_BASE_URL = "https://api.example.com/v1" + +# Enums +class ResponseFormat(str, Enum): + '''Output format for tool responses.''' + MARKDOWN = "markdown" + JSON = "json" + +# Pydantic Models for Input Validation +class UserSearchInput(BaseModel): + '''Input model for user search operations.''' + model_config = ConfigDict( + str_strip_whitespace=True, + validate_assignment=True + ) + + query: str = Field(..., description="Search string to match against names/emails", min_length=2, max_length=200) + limit: Optional[int] = Field(default=20, description="Maximum results to return", ge=1, le=100) + offset: Optional[int] = Field(default=0, description="Number of results to skip for pagination", ge=0) + response_format: ResponseFormat = Field(default=ResponseFormat.MARKDOWN, description="Output format") + + @field_validator('query') + @classmethod + def validate_query(cls, v: str) -> str: + if not v.strip(): + raise ValueError("Query cannot be empty or whitespace only") + return v.strip() + +# Shared utility functions +async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict: + '''Reusable function for all API calls.''' + async with httpx.AsyncClient() as client: + response = await client.request( + method, + f"{API_BASE_URL}/{endpoint}", + timeout=30.0, + **kwargs + ) + response.raise_for_status() + return response.json() + +def _handle_api_error(e: Exception) -> str: + '''Consistent error formatting across all tools.''' + if isinstance(e, httpx.HTTPStatusError): + if e.response.status_code == 404: + return "Error: Resource not found. Please check the ID is correct." + elif e.response.status_code == 403: + return "Error: Permission denied. You don't have access to this resource." + elif e.response.status_code == 429: + return "Error: Rate limit exceeded. Please wait before making more requests." + return f"Error: API request failed with status {e.response.status_code}" + elif isinstance(e, httpx.TimeoutException): + return "Error: Request timed out. Please try again." + return f"Error: Unexpected error occurred: {type(e).__name__}" + +# Tool definitions +@mcp.tool( + name="example_search_users", + annotations={ + "title": "Search Example Users", + "readOnlyHint": True, + "destructiveHint": False, + "idempotentHint": True, + "openWorldHint": True + } +) +async def example_search_users(params: UserSearchInput) -> str: + '''Search for users in the Example system by name, email, or team. + + [Full docstring as shown above] + ''' + try: + # Make API request using validated parameters + data = await _make_api_request( + "users/search", + params={ + "q": params.query, + "limit": params.limit, + "offset": params.offset + } + ) + + users = data.get("users", []) + total = data.get("total", 0) + + if not users: + return f"No users found matching '{params.query}'" + + # Format response based on requested format + if params.response_format == ResponseFormat.MARKDOWN: + lines = [f"# User Search Results: '{params.query}'", ""] + lines.append(f"Found {total} users (showing {len(users)})") + lines.append("") + + for user in users: + lines.append(f"## {user['name']} ({user['id']})") + lines.append(f"- **Email**: {user['email']}") + if user.get('team'): + lines.append(f"- **Team**: {user['team']}") + lines.append("") + + return "\n".join(lines) + + else: + # Machine-readable JSON format + import json + response = { + "total": total, + "count": len(users), + "offset": params.offset, + "users": users + } + return json.dumps(response, indent=2) + + except Exception as e: + return _handle_api_error(e) + +if __name__ == "__main__": + mcp.run() +``` + +--- + +## Advanced FastMCP Features + +### Context Parameter Injection + +FastMCP can automatically inject a `Context` parameter into tools for advanced capabilities like logging, progress reporting, resource reading, and user interaction: + +```python +from mcp.server.fastmcp import FastMCP, Context + +mcp = FastMCP("example_mcp") + +@mcp.tool() +async def advanced_search(query: str, ctx: Context) -> str: + '''Advanced tool with context access for logging and progress.''' + + # Report progress for long operations + await ctx.report_progress(0.25, "Starting search...") + + # Log information for debugging + await ctx.log_info("Processing query", {"query": query, "timestamp": datetime.now()}) + + # Perform search + results = await search_api(query) + await ctx.report_progress(0.75, "Formatting results...") + + # Access server configuration + server_name = ctx.fastmcp.name + + return format_results(results) + +@mcp.tool() +async def interactive_tool(resource_id: str, ctx: Context) -> str: + '''Tool that can request additional input from users.''' + + # Request sensitive information when needed + api_key = await ctx.elicit( + prompt="Please provide your API key:", + input_type="password" + ) + + # Use the provided key + return await api_call(resource_id, api_key) +``` + +**Context capabilities:** +- `ctx.report_progress(progress, message)` - Report progress for long operations +- `ctx.log_info(message, data)` / `ctx.log_error()` / `ctx.log_debug()` - Logging +- `ctx.elicit(prompt, input_type)` - Request input from users +- `ctx.fastmcp.name` - Access server configuration +- `ctx.read_resource(uri)` - Read MCP resources + +### Resource Registration + +Expose data as resources for efficient, template-based access: + +```python +@mcp.resource("file://documents/{name}") +async def get_document(name: str) -> str: + '''Expose documents as MCP resources. + + Resources are useful for static or semi-static data that doesn't + require complex parameters. They use URI templates for flexible access. + ''' + document_path = f"./docs/{name}" + with open(document_path, "r") as f: + return f.read() + +@mcp.resource("config://settings/{key}") +async def get_setting(key: str, ctx: Context) -> str: + '''Expose configuration as resources with context.''' + settings = await load_settings() + return json.dumps(settings.get(key, {})) +``` + +**When to use Resources vs Tools:** +- **Resources**: For data access with simple parameters (URI templates) +- **Tools**: For complex operations with validation and business logic + +### Structured Output Types + +FastMCP supports multiple return types beyond strings: + +```python +from typing import TypedDict +from dataclasses import dataclass +from pydantic import BaseModel + +# TypedDict for structured returns +class UserData(TypedDict): + id: str + name: str + email: str + +@mcp.tool() +async def get_user_typed(user_id: str) -> UserData: + '''Returns structured data - FastMCP handles serialization.''' + return {"id": user_id, "name": "John Doe", "email": "john@example.com"} + +# Pydantic models for complex validation +class DetailedUser(BaseModel): + id: str + name: str + email: str + created_at: datetime + metadata: Dict[str, Any] + +@mcp.tool() +async def get_user_detailed(user_id: str) -> DetailedUser: + '''Returns Pydantic model - automatically generates schema.''' + user = await fetch_user(user_id) + return DetailedUser(**user) +``` + +### Lifespan Management + +Initialize resources that persist across requests: + +```python +from contextlib import asynccontextmanager + +@asynccontextmanager +async def app_lifespan(): + '''Manage resources that live for the server's lifetime.''' + # Initialize connections, load config, etc. + db = await connect_to_database() + config = load_configuration() + + # Make available to all tools + yield {"db": db, "config": config} + + # Cleanup on shutdown + await db.close() + +mcp = FastMCP("example_mcp", lifespan=app_lifespan) + +@mcp.tool() +async def query_data(query: str, ctx: Context) -> str: + '''Access lifespan resources through context.''' + db = ctx.request_context.lifespan_state["db"] + results = await db.query(query) + return format_results(results) +``` + +### Transport Options + +FastMCP supports two main transport mechanisms: + +```python +# stdio transport (for local tools) - default +if __name__ == "__main__": + mcp.run() + +# Streamable HTTP transport (for remote servers) +if __name__ == "__main__": + mcp.run(transport="streamable_http", port=8000) +``` + +**Transport selection:** +- **stdio**: Command-line tools, local integrations, subprocess execution +- **Streamable HTTP**: Web services, remote access, multiple clients + +--- + +## Code Best Practices + +### Code Composability and Reusability + +Your implementation MUST prioritize composability and code reuse: + +1. **Extract Common Functionality**: + - Create reusable helper functions for operations used across multiple tools + - Build shared API clients for HTTP requests instead of duplicating code + - Centralize error handling logic in utility functions + - Extract business logic into dedicated functions that can be composed + - Extract shared markdown or JSON field selection & formatting functionality + +2. **Avoid Duplication**: + - NEVER copy-paste similar code between tools + - If you find yourself writing similar logic twice, extract it into a function + - Common operations like pagination, filtering, field selection, and formatting should be shared + - Authentication/authorization logic should be centralized + +### Python-Specific Best Practices + +1. **Use Type Hints**: Always include type annotations for function parameters and return values +2. **Pydantic Models**: Define clear Pydantic models for all input validation +3. **Avoid Manual Validation**: Let Pydantic handle input validation with constraints +4. **Proper Imports**: Group imports (standard library, third-party, local) +5. **Error Handling**: Use specific exception types (httpx.HTTPStatusError, not generic Exception) +6. **Async Context Managers**: Use `async with` for resources that need cleanup +7. **Constants**: Define module-level constants in UPPER_CASE + +## Quality Checklist + +Before finalizing your Python MCP server implementation, ensure: + +### Strategic Design +- [ ] Tools enable complete workflows, not just API endpoint wrappers +- [ ] Tool names reflect natural task subdivisions +- [ ] Response formats optimize for agent context efficiency +- [ ] Human-readable identifiers used where appropriate +- [ ] Error messages guide agents toward correct usage + +### Implementation Quality +- [ ] FOCUSED IMPLEMENTATION: Most important and valuable tools implemented +- [ ] All tools have descriptive names and documentation +- [ ] Return types are consistent across similar operations +- [ ] Error handling is implemented for all external calls +- [ ] Server name follows format: `{service}_mcp` +- [ ] All network operations use async/await +- [ ] Common functionality is extracted into reusable functions +- [ ] Error messages are clear, actionable, and educational +- [ ] Outputs are properly validated and formatted + +### Tool Configuration +- [ ] All tools implement 'name' and 'annotations' in the decorator +- [ ] Annotations correctly set (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) +- [ ] All tools use Pydantic BaseModel for input validation with Field() definitions +- [ ] All Pydantic Fields have explicit types and descriptions with constraints +- [ ] All tools have comprehensive docstrings with explicit input/output types +- [ ] Docstrings include complete schema structure for dict/JSON returns +- [ ] Pydantic models handle input validation (no manual validation needed) + +### Advanced Features (where applicable) +- [ ] Context injection used for logging, progress, or elicitation +- [ ] Resources registered for appropriate data endpoints +- [ ] Lifespan management implemented for persistent connections +- [ ] Structured output types used (TypedDict, Pydantic models) +- [ ] Appropriate transport configured (stdio or streamable HTTP) + +### Code Quality +- [ ] File includes proper imports including Pydantic imports +- [ ] Pagination is properly implemented where applicable +- [ ] Filtering options are provided for potentially large result sets +- [ ] All async functions are properly defined with `async def` +- [ ] HTTP client usage follows async patterns with proper context managers +- [ ] Type hints are used throughout the code +- [ ] Constants are defined at module level in UPPER_CASE + +### Testing +- [ ] Server runs successfully: `python your_server.py --help` +- [ ] All imports resolve correctly +- [ ] Sample tool calls work as expected +- [ ] Error scenarios handled gracefully diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/connections.py b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/connections.py new file mode 100644 index 00000000..ffcd0da3 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/connections.py @@ -0,0 +1,151 @@ +"""Lightweight connection handling for MCP servers.""" + +from abc import ABC, abstractmethod +from contextlib import AsyncExitStack +from typing import Any + +from mcp import ClientSession, StdioServerParameters +from mcp.client.sse import sse_client +from mcp.client.stdio import stdio_client +from mcp.client.streamable_http import streamablehttp_client + + +class MCPConnection(ABC): + """Base class for MCP server connections.""" + + def __init__(self): + self.session = None + self._stack = None + + @abstractmethod + def _create_context(self): + """Create the connection context based on connection type.""" + + async def __aenter__(self): + """Initialize MCP server connection.""" + self._stack = AsyncExitStack() + await self._stack.__aenter__() + + try: + ctx = self._create_context() + result = await self._stack.enter_async_context(ctx) + + if len(result) == 2: + read, write = result + elif len(result) == 3: + read, write, _ = result + else: + raise ValueError(f"Unexpected context result: {result}") + + session_ctx = ClientSession(read, write) + self.session = await self._stack.enter_async_context(session_ctx) + await self.session.initialize() + return self + except BaseException: + await self._stack.__aexit__(None, None, None) + raise + + async def __aexit__(self, exc_type, exc_val, exc_tb): + """Clean up MCP server connection resources.""" + if self._stack: + await self._stack.__aexit__(exc_type, exc_val, exc_tb) + self.session = None + self._stack = None + + async def list_tools(self) -> list[dict[str, Any]]: + """Retrieve available tools from the MCP server.""" + response = await self.session.list_tools() + return [ + { + "name": tool.name, + "description": tool.description, + "input_schema": tool.inputSchema, + } + for tool in response.tools + ] + + async def call_tool(self, tool_name: str, arguments: dict[str, Any]) -> Any: + """Call a tool on the MCP server with provided arguments.""" + result = await self.session.call_tool(tool_name, arguments=arguments) + return result.content + + +class MCPConnectionStdio(MCPConnection): + """MCP connection using standard input/output.""" + + def __init__(self, command: str, args: list[str] = None, env: dict[str, str] = None): + super().__init__() + self.command = command + self.args = args or [] + self.env = env + + def _create_context(self): + return stdio_client( + StdioServerParameters(command=self.command, args=self.args, env=self.env) + ) + + +class MCPConnectionSSE(MCPConnection): + """MCP connection using Server-Sent Events.""" + + def __init__(self, url: str, headers: dict[str, str] = None): + super().__init__() + self.url = url + self.headers = headers or {} + + def _create_context(self): + return sse_client(url=self.url, headers=self.headers) + + +class MCPConnectionHTTP(MCPConnection): + """MCP connection using Streamable HTTP.""" + + def __init__(self, url: str, headers: dict[str, str] = None): + super().__init__() + self.url = url + self.headers = headers or {} + + def _create_context(self): + return streamablehttp_client(url=self.url, headers=self.headers) + + +def create_connection( + transport: str, + command: str = None, + args: list[str] = None, + env: dict[str, str] = None, + url: str = None, + headers: dict[str, str] = None, +) -> MCPConnection: + """Factory function to create the appropriate MCP connection. + + Args: + transport: Connection type ("stdio", "sse", or "http") + command: Command to run (stdio only) + args: Command arguments (stdio only) + env: Environment variables (stdio only) + url: Server URL (sse and http only) + headers: HTTP headers (sse and http only) + + Returns: + MCPConnection instance + """ + transport = transport.lower() + + if transport == "stdio": + if not command: + raise ValueError("Command is required for stdio transport") + return MCPConnectionStdio(command=command, args=args, env=env) + + elif transport == "sse": + if not url: + raise ValueError("URL is required for sse transport") + return MCPConnectionSSE(url=url, headers=headers) + + elif transport in ["http", "streamable_http", "streamable-http"]: + if not url: + raise ValueError("URL is required for http transport") + return MCPConnectionHTTP(url=url, headers=headers) + + else: + raise ValueError(f"Unsupported transport type: {transport}. Use 'stdio', 'sse', or 'http'") diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/evaluation.py b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/evaluation.py new file mode 100644 index 00000000..41778569 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/evaluation.py @@ -0,0 +1,373 @@ +"""MCP Server Evaluation Harness + +This script evaluates MCP servers by running test questions against them using Claude. +""" + +import argparse +import asyncio +import json +import re +import sys +import time +import traceback +import xml.etree.ElementTree as ET +from pathlib import Path +from typing import Any + +from anthropic import Anthropic + +from connections import create_connection + +EVALUATION_PROMPT = """You are an AI assistant with access to tools. + +When given a task, you MUST: +1. Use the available tools to complete the task +2. Provide summary of each step in your approach, wrapped in tags +3. Provide feedback on the tools provided, wrapped in tags +4. Provide your final response, wrapped in tags + +Summary Requirements: +- In your tags, you must explain: + - The steps you took to complete the task + - Which tools you used, in what order, and why + - The inputs you provided to each tool + - The outputs you received from each tool + - A summary for how you arrived at the response + +Feedback Requirements: +- In your tags, provide constructive feedback on the tools: + - Comment on tool names: Are they clear and descriptive? + - Comment on input parameters: Are they well-documented? Are required vs optional parameters clear? + - Comment on descriptions: Do they accurately describe what the tool does? + - Comment on any errors encountered during tool usage: Did the tool fail to execute? Did the tool return too many tokens? + - Identify specific areas for improvement and explain WHY they would help + - Be specific and actionable in your suggestions + +Response Requirements: +- Your response should be concise and directly address what was asked +- Always wrap your final response in tags +- If you cannot solve the task return NOT_FOUND +- For numeric responses, provide just the number +- For IDs, provide just the ID +- For names or text, provide the exact text requested +- Your response should go last""" + + +def parse_evaluation_file(file_path: Path) -> list[dict[str, Any]]: + """Parse XML evaluation file with qa_pair elements.""" + try: + tree = ET.parse(file_path) + root = tree.getroot() + evaluations = [] + + for qa_pair in root.findall(".//qa_pair"): + question_elem = qa_pair.find("question") + answer_elem = qa_pair.find("answer") + + if question_elem is not None and answer_elem is not None: + evaluations.append({ + "question": (question_elem.text or "").strip(), + "answer": (answer_elem.text or "").strip(), + }) + + return evaluations + except Exception as e: + print(f"Error parsing evaluation file {file_path}: {e}") + return [] + + +def extract_xml_content(text: str, tag: str) -> str | None: + """Extract content from XML tags.""" + pattern = rf"<{tag}>(.*?)" + matches = re.findall(pattern, text, re.DOTALL) + return matches[-1].strip() if matches else None + + +async def agent_loop( + client: Anthropic, + model: str, + question: str, + tools: list[dict[str, Any]], + connection: Any, +) -> tuple[str, dict[str, Any]]: + """Run the agent loop with MCP tools.""" + messages = [{"role": "user", "content": question}] + + response = await asyncio.to_thread( + client.messages.create, + model=model, + max_tokens=4096, + system=EVALUATION_PROMPT, + messages=messages, + tools=tools, + ) + + messages.append({"role": "assistant", "content": response.content}) + + tool_metrics = {} + + while response.stop_reason == "tool_use": + tool_use = next(block for block in response.content if block.type == "tool_use") + tool_name = tool_use.name + tool_input = tool_use.input + + tool_start_ts = time.time() + try: + tool_result = await connection.call_tool(tool_name, tool_input) + tool_response = json.dumps(tool_result) if isinstance(tool_result, (dict, list)) else str(tool_result) + except Exception as e: + tool_response = f"Error executing tool {tool_name}: {str(e)}\n" + tool_response += traceback.format_exc() + tool_duration = time.time() - tool_start_ts + + if tool_name not in tool_metrics: + tool_metrics[tool_name] = {"count": 0, "durations": []} + tool_metrics[tool_name]["count"] += 1 + tool_metrics[tool_name]["durations"].append(tool_duration) + + messages.append({ + "role": "user", + "content": [{ + "type": "tool_result", + "tool_use_id": tool_use.id, + "content": tool_response, + }] + }) + + response = await asyncio.to_thread( + client.messages.create, + model=model, + max_tokens=4096, + system=EVALUATION_PROMPT, + messages=messages, + tools=tools, + ) + messages.append({"role": "assistant", "content": response.content}) + + response_text = next( + (block.text for block in response.content if hasattr(block, "text")), + None, + ) + return response_text, tool_metrics + + +async def evaluate_single_task( + client: Anthropic, + model: str, + qa_pair: dict[str, Any], + tools: list[dict[str, Any]], + connection: Any, + task_index: int, +) -> dict[str, Any]: + """Evaluate a single QA pair with the given tools.""" + start_time = time.time() + + print(f"Task {task_index + 1}: Running task with question: {qa_pair['question']}") + response, tool_metrics = await agent_loop(client, model, qa_pair["question"], tools, connection) + + response_value = extract_xml_content(response, "response") + summary = extract_xml_content(response, "summary") + feedback = extract_xml_content(response, "feedback") + + duration_seconds = time.time() - start_time + + return { + "question": qa_pair["question"], + "expected": qa_pair["answer"], + "actual": response_value, + "score": int(response_value == qa_pair["answer"]) if response_value else 0, + "total_duration": duration_seconds, + "tool_calls": tool_metrics, + "num_tool_calls": sum(len(metrics["durations"]) for metrics in tool_metrics.values()), + "summary": summary, + "feedback": feedback, + } + + +REPORT_HEADER = """ +# Evaluation Report + +## Summary + +- **Accuracy**: {correct}/{total} ({accuracy:.1f}%) +- **Average Task Duration**: {average_duration_s:.2f}s +- **Average Tool Calls per Task**: {average_tool_calls:.2f} +- **Total Tool Calls**: {total_tool_calls} + +--- +""" + +TASK_TEMPLATE = """ +### Task {task_num} + +**Question**: {question} +**Ground Truth Answer**: `{expected_answer}` +**Actual Answer**: `{actual_answer}` +**Correct**: {correct_indicator} +**Duration**: {total_duration:.2f}s +**Tool Calls**: {tool_calls} + +**Summary** +{summary} + +**Feedback** +{feedback} + +--- +""" + + +async def run_evaluation( + eval_path: Path, + connection: Any, + model: str = "claude-3-7-sonnet-20250219", +) -> str: + """Run evaluation with MCP server tools.""" + print("🚀 Starting Evaluation") + + client = Anthropic() + + tools = await connection.list_tools() + print(f"📋 Loaded {len(tools)} tools from MCP server") + + qa_pairs = parse_evaluation_file(eval_path) + print(f"📋 Loaded {len(qa_pairs)} evaluation tasks") + + results = [] + for i, qa_pair in enumerate(qa_pairs): + print(f"Processing task {i + 1}/{len(qa_pairs)}") + result = await evaluate_single_task(client, model, qa_pair, tools, connection, i) + results.append(result) + + correct = sum(r["score"] for r in results) + accuracy = (correct / len(results)) * 100 if results else 0 + average_duration_s = sum(r["total_duration"] for r in results) / len(results) if results else 0 + average_tool_calls = sum(r["num_tool_calls"] for r in results) / len(results) if results else 0 + total_tool_calls = sum(r["num_tool_calls"] for r in results) + + report = REPORT_HEADER.format( + correct=correct, + total=len(results), + accuracy=accuracy, + average_duration_s=average_duration_s, + average_tool_calls=average_tool_calls, + total_tool_calls=total_tool_calls, + ) + + report += "".join([ + TASK_TEMPLATE.format( + task_num=i + 1, + question=qa_pair["question"], + expected_answer=qa_pair["answer"], + actual_answer=result["actual"] or "N/A", + correct_indicator="✅" if result["score"] else "❌", + total_duration=result["total_duration"], + tool_calls=json.dumps(result["tool_calls"], indent=2), + summary=result["summary"] or "N/A", + feedback=result["feedback"] or "N/A", + ) + for i, (qa_pair, result) in enumerate(zip(qa_pairs, results)) + ]) + + return report + + +def parse_headers(header_list: list[str]) -> dict[str, str]: + """Parse header strings in format 'Key: Value' into a dictionary.""" + headers = {} + if not header_list: + return headers + + for header in header_list: + if ":" in header: + key, value = header.split(":", 1) + headers[key.strip()] = value.strip() + else: + print(f"Warning: Ignoring malformed header: {header}") + return headers + + +def parse_env_vars(env_list: list[str]) -> dict[str, str]: + """Parse environment variable strings in format 'KEY=VALUE' into a dictionary.""" + env = {} + if not env_list: + return env + + for env_var in env_list: + if "=" in env_var: + key, value = env_var.split("=", 1) + env[key.strip()] = value.strip() + else: + print(f"Warning: Ignoring malformed environment variable: {env_var}") + return env + + +async def main(): + parser = argparse.ArgumentParser( + description="Evaluate MCP servers using test questions", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + # Evaluate a local stdio MCP server + python evaluation.py -t stdio -c python -a my_server.py eval.xml + + # Evaluate an SSE MCP server + python evaluation.py -t sse -u https://example.com/mcp -H "Authorization: Bearer token" eval.xml + + # Evaluate an HTTP MCP server with custom model + python evaluation.py -t http -u https://example.com/mcp -m claude-3-5-sonnet-20241022 eval.xml + """, + ) + + parser.add_argument("eval_file", type=Path, help="Path to evaluation XML file") + parser.add_argument("-t", "--transport", choices=["stdio", "sse", "http"], default="stdio", help="Transport type (default: stdio)") + parser.add_argument("-m", "--model", default="claude-3-7-sonnet-20250219", help="Claude model to use (default: claude-3-7-sonnet-20250219)") + + stdio_group = parser.add_argument_group("stdio options") + stdio_group.add_argument("-c", "--command", help="Command to run MCP server (stdio only)") + stdio_group.add_argument("-a", "--args", nargs="+", help="Arguments for the command (stdio only)") + stdio_group.add_argument("-e", "--env", nargs="+", help="Environment variables in KEY=VALUE format (stdio only)") + + remote_group = parser.add_argument_group("sse/http options") + remote_group.add_argument("-u", "--url", help="MCP server URL (sse/http only)") + remote_group.add_argument("-H", "--header", nargs="+", dest="headers", help="HTTP headers in 'Key: Value' format (sse/http only)") + + parser.add_argument("-o", "--output", type=Path, help="Output file for evaluation report (default: stdout)") + + args = parser.parse_args() + + if not args.eval_file.exists(): + print(f"Error: Evaluation file not found: {args.eval_file}") + sys.exit(1) + + headers = parse_headers(args.headers) if args.headers else None + env_vars = parse_env_vars(args.env) if args.env else None + + try: + connection = create_connection( + transport=args.transport, + command=args.command, + args=args.args, + env=env_vars, + url=args.url, + headers=headers, + ) + except ValueError as e: + print(f"Error: {e}") + sys.exit(1) + + print(f"🔗 Connecting to MCP server via {args.transport}...") + + async with connection: + print("✅ Connected successfully") + report = await run_evaluation(args.eval_file, connection, args.model) + + if args.output: + args.output.write_text(report) + print(f"\n✅ Report saved to {args.output}") + else: + print("\n" + report) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/example_evaluation.xml b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/example_evaluation.xml new file mode 100644 index 00000000..41e4459b --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/example_evaluation.xml @@ -0,0 +1,22 @@ + + + Calculate the compound interest on $10,000 invested at 5% annual interest rate, compounded monthly for 3 years. What is the final amount in dollars (rounded to 2 decimal places)? + 11614.72 + + + A projectile is launched at a 45-degree angle with an initial velocity of 50 m/s. Calculate the total distance (in meters) it has traveled from the launch point after 2 seconds, assuming g=9.8 m/s². Round to 2 decimal places. + 87.25 + + + A sphere has a volume of 500 cubic meters. Calculate its surface area in square meters. Round to 2 decimal places. + 304.65 + + + Calculate the population standard deviation of this dataset: [12, 15, 18, 22, 25, 30, 35]. Round to 2 decimal places. + 7.61 + + + Calculate the pH of a solution with a hydrogen ion concentration of 3.5 × 10^-5 M. Round to 2 decimal places. + 4.46 + + diff --git a/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/requirements.txt b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/requirements.txt new file mode 100644 index 00000000..e73e5d1e --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/mcp-builder/scripts/requirements.txt @@ -0,0 +1,2 @@ +anthropic>=0.39.0 +mcp>=1.1.0 diff --git a/libs/hexagent_demo/backend/skills/examples/pdf/LICENSE.txt b/libs/hexagent_demo/backend/skills/examples/pdf/LICENSE.txt new file mode 100644 index 00000000..13e25df8 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/pdf/LICENSE.txt @@ -0,0 +1,201 @@ +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. 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Prefer visual review: render PDF pages to PNGs and inspect them. + - Use `pdftoppm` if available. + - If unavailable, install Poppler or ask the user to review the output locally. +2. Use `reportlab` to generate PDFs when creating new documents. +3. Use `pdfplumber` (or `pypdf`) for text extraction and quick checks; do not rely on it for layout fidelity. +4. After each meaningful update, re-render pages and verify alignment, spacing, and legibility. + +## Temp and output conventions +- Use `tmp/pdfs/` for intermediate files; delete when done. +- Write final artifacts under `output/pdf/` when working in this repo. +- Keep filenames stable and descriptive. + +## Dependencies (install if missing) +Prefer `uv` for dependency management. + +Python packages: +``` +uv pip install reportlab pdfplumber pypdf +``` +If `uv` is unavailable: +``` +python3 -m pip install reportlab pdfplumber pypdf +``` +System tools (for rendering): +``` +# macOS (Homebrew) +brew install poppler + +# Ubuntu/Debian +sudo apt-get install -y poppler-utils +``` + +If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally. + +## Environment +No required environment variables. + +## Rendering command +``` +pdftoppm -png $INPUT_PDF $OUTPUT_PREFIX +``` + +## Quality expectations +- Maintain polished visual design: consistent typography, spacing, margins, and section hierarchy. +- Avoid rendering issues: clipped text, overlapping elements, broken tables, black squares, or unreadable glyphs. +- Charts, tables, and images must be sharp, aligned, and clearly labeled. +- Use ASCII hyphens only. Avoid U+2011 (non-breaking hyphen) and other Unicode dashes. +- Citations and references must be human-readable; never leave tool tokens or placeholder strings. + +## Final checks +- Do not deliver until the latest PNG inspection shows zero visual or formatting defects. +- Confirm headers/footers, page numbering, and section transitions look polished. +- Keep intermediate files organized or remove them after final approval. diff --git a/libs/hexagent_demo/backend/skills/examples/pdf/agents/openai.yaml b/libs/hexagent_demo/backend/skills/examples/pdf/agents/openai.yaml new file mode 100644 index 00000000..fe2876a6 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/pdf/agents/openai.yaml @@ -0,0 +1,5 @@ +interface: + display_name: "PDF Skill" + short_description: "Create, edit, and review PDFs" + icon_large: "./assets/pdf.png" + default_prompt: "Create, edit, or review this PDF and summarize the key output or changes." diff --git a/libs/hexagent_demo/backend/skills/examples/pdf/assets/pdf.png b/libs/hexagent_demo/backend/skills/examples/pdf/assets/pdf.png new file mode 100644 index 0000000000000000000000000000000000000000..dd16ba283f6056cfe99cc3d36612d3b8cd79e00d GIT binary patch literal 1312 zcmeAS@N?(olHy`uVBq!ia0vp^DIm``W z$lZxy-8q?;Kn_c~qpu?a!^VE@KZ&eB?p9A1$B+ufw{!RVi#UoLzyD5d!2}6Ysoskj zJ-oMOtXOL%=8(u-&tf7H5Pb1+fP*iushC+nhKLvQ#R(jWQ6COpkYTy8xA^{y#-}%$ zt!K>q`|gw7Nj3I2j%D^|sz0ZtKiiYV!)fqC#X-^OfPi8`hk$_#hlCOfk04VU2cvUK z12*BsE|P(F?<_fWNhtK%wT`m#lPdq-&K9||-~G!M$%}{Gr>NUp_vcx>)3WQ?^Qk=1 zQ{-#|*n{_$&fden*Tp<9K(0Wog;mDSZ`HKK*-HdmqoptYUiV*@O-9}6&`e3L<;zcs zE^o<*@OsYebgU|QA>qiZ zb+l{3sYgnoVd0!|4w_*tErn|*N*`Di2Jvb+>kA za(S;^a^dd1jO1>#~z9$Eu1Q{k8fqp`wIuZ&)+yF_j8h&`3aMmXJbk@yDegV zE{&^}efuOfTUDRq#ik$Utu!k<-F6B&O$yoR9b*=}ydw4U*FK)PSYre^qKxEYzF1jx ztc&;m8(EsY`r+rx=WIXjvo3!T^X;3_e6HC$1^!>v&XSZ^@w+(g`nhb;uSKsmpL@Ra zdX;RAZtmm9C35Y;!YkjGa@L&Sy0>@nwTBPe&V8M4AHFH-*Kf`B4z~Q360)}UA{OkO z+hm@<;>vCBdykL5O1u8<-vpccyQ`-+ZO@1McnsXq2_YL1iiyYc@rXHBB;`Qfy z@xGJN0lF>Dli%@fAdo679+mSlu*RLztcVC~9-Z^jj(b#C&X*>Kr&a(+TImdIg z<0pr8tt=ZSM3p#pTu9!|#;HrSs--^YT3FR4_c3CS={JXn*>}t3`_z&AS-Eb^4lC>AD%YM{ca~>|?ue z;ME1s(-#633faVazdpfn^T;ZJT1M9ik6uO1dGmLjdFZ(+x8tsyj~=ZzF(@$cOA}r$ zA0BAElwG#2Z++3i!%5eFK5sXu`ZuL2f@NE#n!VGv$H({F(b^300 lines), include a table of contents + +**Domain organization**: When a skill supports multiple domains/frameworks, organize by variant: +``` +cloud-deploy/ +├── SKILL.md (workflow + selection) +└── references/ + ├── aws.md + ├── gcp.md + └── azure.md +``` +Claude reads only the relevant reference file. + +#### Principle of Lack of Surprise + +This goes without saying, but skills must not contain malware, exploit code, or any content that could compromise system security. A skill's contents should not surprise the user in their intent if described. Don't go along with requests to create misleading skills or skills designed to facilitate unauthorized access, data exfiltration, or other malicious activities. Things like a "roleplay as an XYZ" are OK though. + +#### Writing Patterns + +Prefer using the imperative form in instructions. + +**Defining output formats** - You can do it like this: +```markdown +## Report structure +ALWAYS use this exact template: +# [Title] +## Executive summary +## Key findings +## Recommendations +``` + +**Examples pattern** - It's useful to include examples. You can format them like this (but if "Input" and "Output" are in the examples you might want to deviate a little): +```markdown +## Commit message format +**Example 1:** +Input: Added user authentication with JWT tokens +Output: feat(auth): implement JWT-based authentication +``` + +### Writing Style + +Try to explain to the model why things are important in lieu of heavy-handed musty MUSTs. Use theory of mind and try to make the skill general and not super-narrow to specific examples. Start by writing a draft and then look at it with fresh eyes and improve it. + +### Test Cases + +After writing the skill draft, come up with 2-3 realistic test prompts — the kind of thing a real user would actually say. Share them with the user: [you don't have to use this exact language] "Here are a few test cases I'd like to try. Do these look right, or do you want to add more?" Then run them. + +Save test cases to `evals/evals.json`. Don't write assertions yet — just the prompts. You'll draft assertions in the next step while the runs are in progress. + +```json +{ + "skill_name": "example-skill", + "evals": [ + { + "id": 1, + "prompt": "User's task prompt", + "expected_output": "Description of expected result", + "files": [] + } + ] +} +``` + +See `references/schemas.md` for the full schema (including the `assertions` field, which you'll add later). + +## Running and evaluating test cases + +This section is one continuous sequence — don't stop partway through. Do NOT use `/skill-test` or any other testing skill. + +Put results in `-workspace/` as a sibling to the skill directory. Within the workspace, organize results by iteration (`iteration-1/`, `iteration-2/`, etc.) and within that, each test case gets a directory (`eval-0/`, `eval-1/`, etc.). Don't create all of this upfront — just create directories as you go. + +### Step 1: Spawn all runs (with-skill AND baseline) in the same turn + +For each test case, spawn two subagents in the same turn — one with the skill, one without. This is important: don't spawn the with-skill runs first and then come back for baselines later. Launch everything at once so it all finishes around the same time. + +**With-skill run:** + +``` +Execute this task: +- Skill path: +- Task: +- Input files: +- Save outputs to: /iteration-/eval-/with_skill/outputs/ +- Outputs to save: +``` + +**Baseline run** (same prompt, but the baseline depends on context): +- **Creating a new skill**: no skill at all. Same prompt, no skill path, save to `without_skill/outputs/`. +- **Improving an existing skill**: the old version. Before editing, snapshot the skill (`cp -r /skill-snapshot/`), then point the baseline subagent at the snapshot. Save to `old_skill/outputs/`. + +Write an `eval_metadata.json` for each test case (assertions can be empty for now). Give each eval a descriptive name based on what it's testing — not just "eval-0". Use this name for the directory too. If this iteration uses new or modified eval prompts, create these files for each new eval directory — don't assume they carry over from previous iterations. + +```json +{ + "eval_id": 0, + "eval_name": "descriptive-name-here", + "prompt": "The user's task prompt", + "assertions": [] +} +``` + +### Step 2: While runs are in progress, draft assertions + +Don't just wait for the runs to finish — you can use this time productively. Draft quantitative assertions for each test case and explain them to the user. If assertions already exist in `evals/evals.json`, review them and explain what they check. + +Good assertions are objectively verifiable and have descriptive names — they should read clearly in the benchmark viewer so someone glancing at the results immediately understands what each one checks. Subjective skills (writing style, design quality) are better evaluated qualitatively — don't force assertions onto things that need human judgment. + +Update the `eval_metadata.json` files and `evals/evals.json` with the assertions once drafted. Also explain to the user what they'll see in the viewer — both the qualitative outputs and the quantitative benchmark. + +### Step 3: As runs complete, capture timing data + +When each subagent task completes, you receive a notification containing `total_tokens` and `duration_ms`. Save this data immediately to `timing.json` in the run directory: + +```json +{ + "total_tokens": 84852, + "duration_ms": 23332, + "total_duration_seconds": 23.3 +} +``` + +This is the only opportunity to capture this data — it comes through the task notification and isn't persisted elsewhere. Process each notification as it arrives rather than trying to batch them. + +### Step 4: Grade, aggregate, and launch the viewer + +Once all runs are done: + +1. **Grade each run** — spawn a grader subagent (or grade inline) that reads `agents/grader.md` and evaluates each assertion against the outputs. Save results to `grading.json` in each run directory. The grading.json expectations array must use the fields `text`, `passed`, and `evidence` (not `name`/`met`/`details` or other variants) — the viewer depends on these exact field names. For assertions that can be checked programmatically, write and run a script rather than eyeballing it — scripts are faster, more reliable, and can be reused across iterations. + +2. **Aggregate into benchmark** — run the aggregation script from the skill-creator directory: + ```bash + python -m scripts.aggregate_benchmark /iteration-N --skill-name + ``` + This produces `benchmark.json` and `benchmark.md` with pass_rate, time, and tokens for each configuration, with mean ± stddev and the delta. If generating benchmark.json manually, see `references/schemas.md` for the exact schema the viewer expects. +Put each with_skill version before its baseline counterpart. + +3. **Do an analyst pass** — read the benchmark data and surface patterns the aggregate stats might hide. See `agents/analyzer.md` (the "Analyzing Benchmark Results" section) for what to look for — things like assertions that always pass regardless of skill (non-discriminating), high-variance evals (possibly flaky), and time/token tradeoffs. + +4. **Launch the viewer** with both qualitative outputs and quantitative data: + ```bash + nohup python /eval-viewer/generate_review.py \ + /iteration-N \ + --skill-name "my-skill" \ + --benchmark /iteration-N/benchmark.json \ + > /dev/null 2>&1 & + VIEWER_PID=$! + ``` + For iteration 2+, also pass `--previous-workspace /iteration-`. + + **Cowork / headless environments:** If `webbrowser.open()` is not available or the environment has no display, use `--static ` to write a standalone HTML file instead of starting a server. Feedback will be downloaded as a `feedback.json` file when the user clicks "Submit All Reviews". After download, copy `feedback.json` into the workspace directory for the next iteration to pick up. + +Note: please use generate_review.py to create the viewer; there's no need to write custom HTML. + +5. **Tell the user** something like: "I've opened the results in your browser. There are two tabs — 'Outputs' lets you click through each test case and leave feedback, 'Benchmark' shows the quantitative comparison. When you're done, come back here and let me know." + +### What the user sees in the viewer + +The "Outputs" tab shows one test case at a time: +- **Prompt**: the task that was given +- **Output**: the files the skill produced, rendered inline where possible +- **Previous Output** (iteration 2+): collapsed section showing last iteration's output +- **Formal Grades** (if grading was run): collapsed section showing assertion pass/fail +- **Feedback**: a textbox that auto-saves as they type +- **Previous Feedback** (iteration 2+): their comments from last time, shown below the textbox + +The "Benchmark" tab shows the stats summary: pass rates, timing, and token usage for each configuration, with per-eval breakdowns and analyst observations. + +Navigation is via prev/next buttons or arrow keys. When done, they click "Submit All Reviews" which saves all feedback to `feedback.json`. + +### Step 5: Read the feedback + +When the user tells you they're done, read `feedback.json`: + +```json +{ + "reviews": [ + {"run_id": "eval-0-with_skill", "feedback": "the chart is missing axis labels", "timestamp": "..."}, + {"run_id": "eval-1-with_skill", "feedback": "", "timestamp": "..."}, + {"run_id": "eval-2-with_skill", "feedback": "perfect, love this", "timestamp": "..."} + ], + "status": "complete" +} +``` + +Empty feedback means the user thought it was fine. Focus your improvements on the test cases where the user had specific complaints. + +Kill the viewer server when you're done with it: + +```bash +kill $VIEWER_PID 2>/dev/null +``` + +--- + +## Improving the skill + +This is the heart of the loop. You've run the test cases, the user has reviewed the results, and now you need to make the skill better based on their feedback. + +### How to think about improvements + +1. **Generalize from the feedback.** The big picture thing that's happening here is that we're trying to create skills that can be used a million times (maybe literally, maybe even more who knows) across many different prompts. Here you and the user are iterating on only a few examples over and over again because it helps move faster. The user knows these examples in and out and it's quick for them to assess new outputs. But if the skill you and the user are codeveloping works only for those examples, it's useless. Rather than put in fiddly overfitty changes, or oppressively constrictive MUSTs, if there's some stubborn issue, you might try branching out and using different metaphors, or recommending different patterns of working. It's relatively cheap to try and maybe you'll land on something great. + +2. **Keep the prompt lean.** Remove things that aren't pulling their weight. Make sure to read the transcripts, not just the final outputs — if it looks like the skill is making the model waste a bunch of time doing things that are unproductive, you can try getting rid of the parts of the skill that are making it do that and seeing what happens. + +3. **Explain the why.** Try hard to explain the **why** behind everything you're asking the model to do. Today's LLMs are *smart*. They have good theory of mind and when given a good harness can go beyond rote instructions and really make things happen. Even if the feedback from the user is terse or frustrated, try to actually understand the task and why the user is writing what they wrote, and what they actually wrote, and then transmit this understanding into the instructions. If you find yourself writing ALWAYS or NEVER in all caps, or using super rigid structures, that's a yellow flag — if possible, reframe and explain the reasoning so that the model understands why the thing you're asking for is important. That's a more humane, powerful, and effective approach. + +4. **Look for repeated work across test cases.** Read the transcripts from the test runs and notice if the subagents all independently wrote similar helper scripts or took the same multi-step approach to something. If all 3 test cases resulted in the subagent writing a `create_docx.py` or a `build_chart.py`, that's a strong signal the skill should bundle that script. Write it once, put it in `scripts/`, and tell the skill to use it. This saves every future invocation from reinventing the wheel. + +This task is pretty important (we are trying to create billions a year in economic value here!) and your thinking time is not the blocker; take your time and really mull things over. I'd suggest writing a draft revision and then looking at it anew and making improvements. Really do your best to get into the head of the user and understand what they want and need. + +### The iteration loop + +After improving the skill: + +1. Apply your improvements to the skill +2. Rerun all test cases into a new `iteration-/` directory, including baseline runs. If you're creating a new skill, the baseline is always `without_skill` (no skill) — that stays the same across iterations. If you're improving an existing skill, use your judgment on what makes sense as the baseline: the original version the user came in with, or the previous iteration. +3. Launch the reviewer with `--previous-workspace` pointing at the previous iteration +4. Wait for the user to review and tell you they're done +5. Read the new feedback, improve again, repeat + +Keep going until: +- The user says they're happy +- The feedback is all empty (everything looks good) +- You're not making meaningful progress + +--- + +## Advanced: Blind comparison + +For situations where you want a more rigorous comparison between two versions of a skill (e.g., the user asks "is the new version actually better?"), there's a blind comparison system. Read `agents/comparator.md` and `agents/analyzer.md` for the details. The basic idea is: give two outputs to an independent agent without telling it which is which, and let it judge quality. Then analyze why the winner won. + +This is optional, requires subagents, and most users won't need it. The human review loop is usually sufficient. + +--- + +## Description Optimization + +The description field in SKILL.md frontmatter is the primary mechanism that determines whether Claude invokes a skill. After creating or improving a skill, offer to optimize the description for better triggering accuracy. + +### Step 1: Generate trigger eval queries + +Create 20 eval queries — a mix of should-trigger and should-not-trigger. Save as JSON: + +```json +[ + {"query": "the user prompt", "should_trigger": true}, + {"query": "another prompt", "should_trigger": false} +] +``` + +The queries must be realistic and something a Claude Code or Claude.ai user would actually type. Not abstract requests, but requests that are concrete and specific and have a good amount of detail. For instance, file paths, personal context about the user's job or situation, column names and values, company names, URLs. A little bit of backstory. Some might be in lowercase or contain abbreviations or typos or casual speech. Use a mix of different lengths, and focus on edge cases rather than making them clear-cut (the user will get a chance to sign off on them). + +Bad: `"Format this data"`, `"Extract text from PDF"`, `"Create a chart"` + +Good: `"ok so my boss just sent me this xlsx file (its in my downloads, called something like 'Q4 sales final FINAL v2.xlsx') and she wants me to add a column that shows the profit margin as a percentage. The revenue is in column C and costs are in column D i think"` + +For the **should-trigger** queries (8-10), think about coverage. You want different phrasings of the same intent — some formal, some casual. Include cases where the user doesn't explicitly name the skill or file type but clearly needs it. Throw in some uncommon use cases and cases where this skill competes with another but should win. + +For the **should-not-trigger** queries (8-10), the most valuable ones are the near-misses — queries that share keywords or concepts with the skill but actually need something different. Think adjacent domains, ambiguous phrasing where a naive keyword match would trigger but shouldn't, and cases where the query touches on something the skill does but in a context where another tool is more appropriate. + +The key thing to avoid: don't make should-not-trigger queries obviously irrelevant. "Write a fibonacci function" as a negative test for a PDF skill is too easy — it doesn't test anything. The negative cases should be genuinely tricky. + +### Step 2: Review with user + +Present the eval set to the user for review using the HTML template: + +1. Read the template from `assets/eval_review.html` +2. Replace the placeholders: + - `__EVAL_DATA_PLACEHOLDER__` → the JSON array of eval items (no quotes around it — it's a JS variable assignment) + - `__SKILL_NAME_PLACEHOLDER__` → the skill's name + - `__SKILL_DESCRIPTION_PLACEHOLDER__` → the skill's current description +3. Write to a temp file (e.g., `/tmp/eval_review_.html`) and open it: `open /tmp/eval_review_.html` +4. The user can edit queries, toggle should-trigger, add/remove entries, then click "Export Eval Set" +5. The file downloads to `~/Downloads/eval_set.json` — check the Downloads folder for the most recent version in case there are multiple (e.g., `eval_set (1).json`) + +This step matters — bad eval queries lead to bad descriptions. + +### Step 3: Run the optimization loop + +Tell the user: "This will take some time — I'll run the optimization loop in the background and check on it periodically." + +Save the eval set to the workspace, then run in the background: + +```bash +python -m scripts.run_loop \ + --eval-set \ + --skill-path \ + --model \ + --max-iterations 5 \ + --verbose +``` + +Use the model ID from your system prompt (the one powering the current session) so the triggering test matches what the user actually experiences. + +While it runs, periodically tail the output to give the user updates on which iteration it's on and what the scores look like. + +This handles the full optimization loop automatically. It splits the eval set into 60% train and 40% held-out test, evaluates the current description (running each query 3 times to get a reliable trigger rate), then calls Claude to propose improvements based on what failed. It re-evaluates each new description on both train and test, iterating up to 5 times. When it's done, it opens an HTML report in the browser showing the results per iteration and returns JSON with `best_description` — selected by test score rather than train score to avoid overfitting. + +### How skill triggering works + +Understanding the triggering mechanism helps design better eval queries. Skills appear in Claude's `available_skills` list with their name + description, and Claude decides whether to consult a skill based on that description. The important thing to know is that Claude only consults skills for tasks it can't easily handle on its own — simple, one-step queries like "read this PDF" may not trigger a skill even if the description matches perfectly, because Claude can handle them directly with basic tools. Complex, multi-step, or specialized queries reliably trigger skills when the description matches. + +This means your eval queries should be substantive enough that Claude would actually benefit from consulting a skill. Simple queries like "read file X" are poor test cases — they won't trigger skills regardless of description quality. + +### Step 4: Apply the result + +Take `best_description` from the JSON output and update the skill's SKILL.md frontmatter. Show the user before/after and report the scores. + +--- + +### Package and Present (only if `present_files` tool is available) + +Check whether you have access to the `present_files` tool. If you don't, skip this step. If you do, package the skill and present the .skill file to the user: + +```bash +python -m scripts.package_skill +``` + +After packaging, direct the user to the resulting `.skill` file path so they can install it. + +--- + +## Claude.ai-specific instructions + +In Claude.ai, the core workflow is the same (draft → test → review → improve → repeat), but because Claude.ai doesn't have subagents, some mechanics change. Here's what to adapt: + +**Running test cases**: No subagents means no parallel execution. For each test case, read the skill's SKILL.md, then follow its instructions to accomplish the test prompt yourself. Do them one at a time. This is less rigorous than independent subagents (you wrote the skill and you're also running it, so you have full context), but it's a useful sanity check — and the human review step compensates. Skip the baseline runs — just use the skill to complete the task as requested. + +**Reviewing results**: If you can't open a browser (e.g., Claude.ai's VM has no display, or you're on a remote server), skip the browser reviewer entirely. Instead, present results directly in the conversation. For each test case, show the prompt and the output. If the output is a file the user needs to see (like a .docx or .xlsx), save it to the filesystem and tell them where it is so they can download and inspect it. Ask for feedback inline: "How does this look? Anything you'd change?" + +**Benchmarking**: Skip the quantitative benchmarking — it relies on baseline comparisons which aren't meaningful without subagents. Focus on qualitative feedback from the user. + +**The iteration loop**: Same as before — improve the skill, rerun the test cases, ask for feedback — just without the browser reviewer in the middle. You can still organize results into iteration directories on the filesystem if you have one. + +**Description optimization**: This section requires the `claude` CLI tool (specifically `claude -p`) which is only available in Claude Code. Skip it if you're on Claude.ai. + +**Blind comparison**: Requires subagents. Skip it. + +**Packaging**: The `package_skill.py` script works anywhere with Python and a filesystem. On Claude.ai, you can run it and the user can download the resulting `.skill` file. + +**Updating an existing skill**: The user might be asking you to update an existing skill, not create a new one. In this case: +- **Preserve the original name.** Note the skill's directory name and `name` frontmatter field -- use them unchanged. E.g., if the installed skill is `research-helper`, output `research-helper.skill` (not `research-helper-v2`). +- **Copy to a writeable location before editing.** The installed skill path may be read-only. Copy to `/tmp/skill-name/`, edit there, and package from the copy. +- **If packaging manually, stage in `/tmp/` first**, then copy to the output directory -- direct writes may fail due to permissions. + +--- + +## Cowork-Specific Instructions + +If you're in Cowork, the main things to know are: + +- You have subagents, so the main workflow (spawn test cases in parallel, run baselines, grade, etc.) all works. (However, if you run into severe problems with timeouts, it's OK to run the test prompts in series rather than parallel.) +- You don't have a browser or display, so when generating the eval viewer, use `--static ` to write a standalone HTML file instead of starting a server. Then proffer a link that the user can click to open the HTML in their browser. +- For whatever reason, the Cowork setup seems to disincline Claude from generating the eval viewer after running the tests, so just to reiterate: whether you're in Cowork or in Claude Code, after running tests, you should always generate the eval viewer for the human to look at examples before revising the skill yourself and trying to make corrections, using `generate_review.py` (not writing your own boutique html code). Sorry in advance but I'm gonna go all caps here: GENERATE THE EVAL VIEWER *BEFORE* evaluating inputs yourself. You want to get them in front of the human ASAP! +- Feedback works differently: since there's no running server, the viewer's "Submit All Reviews" button will download `feedback.json` as a file. You can then read it from there (you may have to request access first). +- Packaging works — `package_skill.py` just needs Python and a filesystem. +- Description optimization (`run_loop.py` / `run_eval.py`) should work in Cowork just fine since it uses `claude -p` via subprocess, not a browser, but please save it until you've fully finished making the skill and the user agrees it's in good shape. +- **Updating an existing skill**: The user might be asking you to update an existing skill, not create a new one. Follow the update guidance in the claude.ai section above. + +--- + +## Reference files + +The agents/ directory contains instructions for specialized subagents. Read them when you need to spawn the relevant subagent. + +- `agents/grader.md` — How to evaluate assertions against outputs +- `agents/comparator.md` — How to do blind A/B comparison between two outputs +- `agents/analyzer.md` — How to analyze why one version beat another + +The references/ directory has additional documentation: +- `references/schemas.md` — JSON structures for evals.json, grading.json, etc. + +--- + +Repeating one more time the core loop here for emphasis: + +- Figure out what the skill is about +- Draft or edit the skill +- Run claude-with-access-to-the-skill on test prompts +- With the user, evaluate the outputs: + - Create benchmark.json and run `eval-viewer/generate_review.py` to help the user review them + - Run quantitative evals +- Repeat until you and the user are satisfied +- Package the final skill and return it to the user. + +Please add steps to your TodoList, if you have such a thing, to make sure you don't forget. If you're in Cowork, please specifically put "Create evals JSON and run `eval-viewer/generate_review.py` so human can review test cases" in your TodoList to make sure it happens. + +Good luck! diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/analyzer.md b/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/analyzer.md new file mode 100644 index 00000000..14e41d60 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/analyzer.md @@ -0,0 +1,274 @@ +# Post-hoc Analyzer Agent + +Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions. + +## Role + +After the blind comparator determines a winner, the Post-hoc Analyzer "unblids" the results by examining the skills and transcripts. The goal is to extract actionable insights: what made the winner better, and how can the loser be improved? + +## Inputs + +You receive these parameters in your prompt: + +- **winner**: "A" or "B" (from blind comparison) +- **winner_skill_path**: Path to the skill that produced the winning output +- **winner_transcript_path**: Path to the execution transcript for the winner +- **loser_skill_path**: Path to the skill that produced the losing output +- **loser_transcript_path**: Path to the execution transcript for the loser +- **comparison_result_path**: Path to the blind comparator's output JSON +- **output_path**: Where to save the analysis results + +## Process + +### Step 1: Read Comparison Result + +1. Read the blind comparator's output at comparison_result_path +2. Note the winning side (A or B), the reasoning, and any scores +3. Understand what the comparator valued in the winning output + +### Step 2: Read Both Skills + +1. Read the winner skill's SKILL.md and key referenced files +2. Read the loser skill's SKILL.md and key referenced files +3. Identify structural differences: + - Instructions clarity and specificity + - Script/tool usage patterns + - Example coverage + - Edge case handling + +### Step 3: Read Both Transcripts + +1. Read the winner's transcript +2. Read the loser's transcript +3. Compare execution patterns: + - How closely did each follow their skill's instructions? + - What tools were used differently? + - Where did the loser diverge from optimal behavior? + - Did either encounter errors or make recovery attempts? + +### Step 4: Analyze Instruction Following + +For each transcript, evaluate: +- Did the agent follow the skill's explicit instructions? +- Did the agent use the skill's provided tools/scripts? +- Were there missed opportunities to leverage skill content? +- Did the agent add unnecessary steps not in the skill? + +Score instruction following 1-10 and note specific issues. + +### Step 5: Identify Winner Strengths + +Determine what made the winner better: +- Clearer instructions that led to better behavior? +- Better scripts/tools that produced better output? +- More comprehensive examples that guided edge cases? +- Better error handling guidance? + +Be specific. Quote from skills/transcripts where relevant. + +### Step 6: Identify Loser Weaknesses + +Determine what held the loser back: +- Ambiguous instructions that led to suboptimal choices? +- Missing tools/scripts that forced workarounds? +- Gaps in edge case coverage? +- Poor error handling that caused failures? + +### Step 7: Generate Improvement Suggestions + +Based on the analysis, produce actionable suggestions for improving the loser skill: +- Specific instruction changes to make +- Tools/scripts to add or modify +- Examples to include +- Edge cases to address + +Prioritize by impact. Focus on changes that would have changed the outcome. + +### Step 8: Write Analysis Results + +Save structured analysis to `{output_path}`. + +## Output Format + +Write a JSON file with this structure: + +```json +{ + "comparison_summary": { + "winner": "A", + "winner_skill": "path/to/winner/skill", + "loser_skill": "path/to/loser/skill", + "comparator_reasoning": "Brief summary of why comparator chose winner" + }, + "winner_strengths": [ + "Clear step-by-step instructions for handling multi-page documents", + "Included validation script that caught formatting errors", + "Explicit guidance on fallback behavior when OCR fails" + ], + "loser_weaknesses": [ + "Vague instruction 'process the document appropriately' led to inconsistent behavior", + "No script for validation, agent had to improvise and made errors", + "No guidance on OCR failure, agent gave up instead of trying alternatives" + ], + "instruction_following": { + "winner": { + "score": 9, + "issues": [ + "Minor: skipped optional logging step" + ] + }, + "loser": { + "score": 6, + "issues": [ + "Did not use the skill's formatting template", + "Invented own approach instead of following step 3", + "Missed the 'always validate output' instruction" + ] + } + }, + "improvement_suggestions": [ + { + "priority": "high", + "category": "instructions", + "suggestion": "Replace 'process the document appropriately' with explicit steps: 1) Extract text, 2) Identify sections, 3) Format per template", + "expected_impact": "Would eliminate ambiguity that caused inconsistent behavior" + }, + { + "priority": "high", + "category": "tools", + "suggestion": "Add validate_output.py script similar to winner skill's validation approach", + "expected_impact": "Would catch formatting errors before final output" + }, + { + "priority": "medium", + "category": "error_handling", + "suggestion": "Add fallback instructions: 'If OCR fails, try: 1) different resolution, 2) image preprocessing, 3) manual extraction'", + "expected_impact": "Would prevent early failure on difficult documents" + } + ], + "transcript_insights": { + "winner_execution_pattern": "Read skill -> Followed 5-step process -> Used validation script -> Fixed 2 issues -> Produced output", + "loser_execution_pattern": "Read skill -> Unclear on approach -> Tried 3 different methods -> No validation -> Output had errors" + } +} +``` + +## Guidelines + +- **Be specific**: Quote from skills and transcripts, don't just say "instructions were unclear" +- **Be actionable**: Suggestions should be concrete changes, not vague advice +- **Focus on skill improvements**: The goal is to improve the losing skill, not critique the agent +- **Prioritize by impact**: Which changes would most likely have changed the outcome? +- **Consider causation**: Did the skill weakness actually cause the worse output, or is it incidental? +- **Stay objective**: Analyze what happened, don't editorialize +- **Think about generalization**: Would this improvement help on other evals too? + +## Categories for Suggestions + +Use these categories to organize improvement suggestions: + +| Category | Description | +|----------|-------------| +| `instructions` | Changes to the skill's prose instructions | +| `tools` | Scripts, templates, or utilities to add/modify | +| `examples` | Example inputs/outputs to include | +| `error_handling` | Guidance for handling failures | +| `structure` | Reorganization of skill content | +| `references` | External docs or resources to add | + +## Priority Levels + +- **high**: Would likely change the outcome of this comparison +- **medium**: Would improve quality but may not change win/loss +- **low**: Nice to have, marginal improvement + +--- + +# Analyzing Benchmark Results + +When analyzing benchmark results, the analyzer's purpose is to **surface patterns and anomalies** across multiple runs, not suggest skill improvements. + +## Role + +Review all benchmark run results and generate freeform notes that help the user understand skill performance. Focus on patterns that wouldn't be visible from aggregate metrics alone. + +## Inputs + +You receive these parameters in your prompt: + +- **benchmark_data_path**: Path to the in-progress benchmark.json with all run results +- **skill_path**: Path to the skill being benchmarked +- **output_path**: Where to save the notes (as JSON array of strings) + +## Process + +### Step 1: Read Benchmark Data + +1. Read the benchmark.json containing all run results +2. Note the configurations tested (with_skill, without_skill) +3. Understand the run_summary aggregates already calculated + +### Step 2: Analyze Per-Assertion Patterns + +For each expectation across all runs: +- Does it **always pass** in both configurations? (may not differentiate skill value) +- Does it **always fail** in both configurations? (may be broken or beyond capability) +- Does it **always pass with skill but fail without**? (skill clearly adds value here) +- Does it **always fail with skill but pass without**? (skill may be hurting) +- Is it **highly variable**? (flaky expectation or non-deterministic behavior) + +### Step 3: Analyze Cross-Eval Patterns + +Look for patterns across evals: +- Are certain eval types consistently harder/easier? +- Do some evals show high variance while others are stable? +- Are there surprising results that contradict expectations? + +### Step 4: Analyze Metrics Patterns + +Look at time_seconds, tokens, tool_calls: +- Does the skill significantly increase execution time? +- Is there high variance in resource usage? +- Are there outlier runs that skew the aggregates? + +### Step 5: Generate Notes + +Write freeform observations as a list of strings. Each note should: +- State a specific observation +- Be grounded in the data (not speculation) +- Help the user understand something the aggregate metrics don't show + +Examples: +- "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value" +- "Eval 3 shows high variance (50% ± 40%) - run 2 had an unusual failure that may be flaky" +- "Without-skill runs consistently fail on table extraction expectations (0% pass rate)" +- "Skill adds 13s average execution time but improves pass rate by 50%" +- "Token usage is 80% higher with skill, primarily due to script output parsing" +- "All 3 without-skill runs for eval 1 produced empty output" + +### Step 6: Write Notes + +Save notes to `{output_path}` as a JSON array of strings: + +```json +[ + "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value", + "Eval 3 shows high variance (50% ± 40%) - run 2 had an unusual failure", + "Without-skill runs consistently fail on table extraction expectations", + "Skill adds 13s average execution time but improves pass rate by 50%" +] +``` + +## Guidelines + +**DO:** +- Report what you observe in the data +- Be specific about which evals, expectations, or runs you're referring to +- Note patterns that aggregate metrics would hide +- Provide context that helps interpret the numbers + +**DO NOT:** +- Suggest improvements to the skill (that's for the improvement step, not benchmarking) +- Make subjective quality judgments ("the output was good/bad") +- Speculate about causes without evidence +- Repeat information already in the run_summary aggregates diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/comparator.md b/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/comparator.md new file mode 100644 index 00000000..80e00eb4 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/comparator.md @@ -0,0 +1,202 @@ +# Blind Comparator Agent + +Compare two outputs WITHOUT knowing which skill produced them. + +## Role + +The Blind Comparator judges which output better accomplishes the eval task. You receive two outputs labeled A and B, but you do NOT know which skill produced which. This prevents bias toward a particular skill or approach. + +Your judgment is based purely on output quality and task completion. + +## Inputs + +You receive these parameters in your prompt: + +- **output_a_path**: Path to the first output file or directory +- **output_b_path**: Path to the second output file or directory +- **eval_prompt**: The original task/prompt that was executed +- **expectations**: List of expectations to check (optional - may be empty) + +## Process + +### Step 1: Read Both Outputs + +1. Examine output A (file or directory) +2. Examine output B (file or directory) +3. Note the type, structure, and content of each +4. If outputs are directories, examine all relevant files inside + +### Step 2: Understand the Task + +1. Read the eval_prompt carefully +2. Identify what the task requires: + - What should be produced? + - What qualities matter (accuracy, completeness, format)? + - What would distinguish a good output from a poor one? + +### Step 3: Generate Evaluation Rubric + +Based on the task, generate a rubric with two dimensions: + +**Content Rubric** (what the output contains): +| Criterion | 1 (Poor) | 3 (Acceptable) | 5 (Excellent) | +|-----------|----------|----------------|---------------| +| Correctness | Major errors | Minor errors | Fully correct | +| Completeness | Missing key elements | Mostly complete | All elements present | +| Accuracy | Significant inaccuracies | Minor inaccuracies | Accurate throughout | + +**Structure Rubric** (how the output is organized): +| Criterion | 1 (Poor) | 3 (Acceptable) | 5 (Excellent) | +|-----------|----------|----------------|---------------| +| Organization | Disorganized | Reasonably organized | Clear, logical structure | +| Formatting | Inconsistent/broken | Mostly consistent | Professional, polished | +| Usability | Difficult to use | Usable with effort | Easy to use | + +Adapt criteria to the specific task. For example: +- PDF form → "Field alignment", "Text readability", "Data placement" +- Document → "Section structure", "Heading hierarchy", "Paragraph flow" +- Data output → "Schema correctness", "Data types", "Completeness" + +### Step 4: Evaluate Each Output Against the Rubric + +For each output (A and B): + +1. **Score each criterion** on the rubric (1-5 scale) +2. **Calculate dimension totals**: Content score, Structure score +3. **Calculate overall score**: Average of dimension scores, scaled to 1-10 + +### Step 5: Check Assertions (if provided) + +If expectations are provided: + +1. Check each expectation against output A +2. Check each expectation against output B +3. Count pass rates for each output +4. Use expectation scores as secondary evidence (not the primary decision factor) + +### Step 6: Determine the Winner + +Compare A and B based on (in priority order): + +1. **Primary**: Overall rubric score (content + structure) +2. **Secondary**: Assertion pass rates (if applicable) +3. **Tiebreaker**: If truly equal, declare a TIE + +Be decisive - ties should be rare. One output is usually better, even if marginally. + +### Step 7: Write Comparison Results + +Save results to a JSON file at the path specified (or `comparison.json` if not specified). + +## Output Format + +Write a JSON file with this structure: + +```json +{ + "winner": "A", + "reasoning": "Output A provides a complete solution with proper formatting and all required fields. Output B is missing the date field and has formatting inconsistencies.", + "rubric": { + "A": { + "content": { + "correctness": 5, + "completeness": 5, + "accuracy": 4 + }, + "structure": { + "organization": 4, + "formatting": 5, + "usability": 4 + }, + "content_score": 4.7, + "structure_score": 4.3, + "overall_score": 9.0 + }, + "B": { + "content": { + "correctness": 3, + "completeness": 2, + "accuracy": 3 + }, + "structure": { + "organization": 3, + "formatting": 2, + "usability": 3 + }, + "content_score": 2.7, + "structure_score": 2.7, + "overall_score": 5.4 + } + }, + "output_quality": { + "A": { + "score": 9, + "strengths": ["Complete solution", "Well-formatted", "All fields present"], + "weaknesses": ["Minor style inconsistency in header"] + }, + "B": { + "score": 5, + "strengths": ["Readable output", "Correct basic structure"], + "weaknesses": ["Missing date field", "Formatting inconsistencies", "Partial data extraction"] + } + }, + "expectation_results": { + "A": { + "passed": 4, + "total": 5, + "pass_rate": 0.80, + "details": [ + {"text": "Output includes name", "passed": true}, + {"text": "Output includes date", "passed": true}, + {"text": "Format is PDF", "passed": true}, + {"text": "Contains signature", "passed": false}, + {"text": "Readable text", "passed": true} + ] + }, + "B": { + "passed": 3, + "total": 5, + "pass_rate": 0.60, + "details": [ + {"text": "Output includes name", "passed": true}, + {"text": "Output includes date", "passed": false}, + {"text": "Format is PDF", "passed": true}, + {"text": "Contains signature", "passed": false}, + {"text": "Readable text", "passed": true} + ] + } + } +} +``` + +If no expectations were provided, omit the `expectation_results` field entirely. + +## Field Descriptions + +- **winner**: "A", "B", or "TIE" +- **reasoning**: Clear explanation of why the winner was chosen (or why it's a tie) +- **rubric**: Structured rubric evaluation for each output + - **content**: Scores for content criteria (correctness, completeness, accuracy) + - **structure**: Scores for structure criteria (organization, formatting, usability) + - **content_score**: Average of content criteria (1-5) + - **structure_score**: Average of structure criteria (1-5) + - **overall_score**: Combined score scaled to 1-10 +- **output_quality**: Summary quality assessment + - **score**: 1-10 rating (should match rubric overall_score) + - **strengths**: List of positive aspects + - **weaknesses**: List of issues or shortcomings +- **expectation_results**: (Only if expectations provided) + - **passed**: Number of expectations that passed + - **total**: Total number of expectations + - **pass_rate**: Fraction passed (0.0 to 1.0) + - **details**: Individual expectation results + +## Guidelines + +- **Stay blind**: DO NOT try to infer which skill produced which output. Judge purely on output quality. +- **Be specific**: Cite specific examples when explaining strengths and weaknesses. +- **Be decisive**: Choose a winner unless outputs are genuinely equivalent. +- **Output quality first**: Assertion scores are secondary to overall task completion. +- **Be objective**: Don't favor outputs based on style preferences; focus on correctness and completeness. +- **Explain your reasoning**: The reasoning field should make it clear why you chose the winner. +- **Handle edge cases**: If both outputs fail, pick the one that fails less badly. If both are excellent, pick the one that's marginally better. diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/grader.md b/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/grader.md new file mode 100644 index 00000000..558ab05c --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/agents/grader.md @@ -0,0 +1,223 @@ +# Grader Agent + +Evaluate expectations against an execution transcript and outputs. + +## Role + +The Grader reviews a transcript and output files, then determines whether each expectation passes or fails. Provide clear evidence for each judgment. + +You have two jobs: grade the outputs, and critique the evals themselves. A passing grade on a weak assertion is worse than useless — it creates false confidence. When you notice an assertion that's trivially satisfied, or an important outcome that no assertion checks, say so. + +## Inputs + +You receive these parameters in your prompt: + +- **expectations**: List of expectations to evaluate (strings) +- **transcript_path**: Path to the execution transcript (markdown file) +- **outputs_dir**: Directory containing output files from execution + +## Process + +### Step 1: Read the Transcript + +1. Read the transcript file completely +2. Note the eval prompt, execution steps, and final result +3. Identify any issues or errors documented + +### Step 2: Examine Output Files + +1. List files in outputs_dir +2. Read/examine each file relevant to the expectations. If outputs aren't plain text, use the inspection tools provided in your prompt — don't rely solely on what the transcript says the executor produced. +3. Note contents, structure, and quality + +### Step 3: Evaluate Each Assertion + +For each expectation: + +1. **Search for evidence** in the transcript and outputs +2. **Determine verdict**: + - **PASS**: Clear evidence the expectation is true AND the evidence reflects genuine task completion, not just surface-level compliance + - **FAIL**: No evidence, or evidence contradicts the expectation, or the evidence is superficial (e.g., correct filename but empty/wrong content) +3. **Cite the evidence**: Quote the specific text or describe what you found + +### Step 4: Extract and Verify Claims + +Beyond the predefined expectations, extract implicit claims from the outputs and verify them: + +1. **Extract claims** from the transcript and outputs: + - Factual statements ("The form has 12 fields") + - Process claims ("Used pypdf to fill the form") + - Quality claims ("All fields were filled correctly") + +2. **Verify each claim**: + - **Factual claims**: Can be checked against the outputs or external sources + - **Process claims**: Can be verified from the transcript + - **Quality claims**: Evaluate whether the claim is justified + +3. **Flag unverifiable claims**: Note claims that cannot be verified with available information + +This catches issues that predefined expectations might miss. + +### Step 5: Read User Notes + +If `{outputs_dir}/user_notes.md` exists: +1. Read it and note any uncertainties or issues flagged by the executor +2. Include relevant concerns in the grading output +3. These may reveal problems even when expectations pass + +### Step 6: Critique the Evals + +After grading, consider whether the evals themselves could be improved. Only surface suggestions when there's a clear gap. + +Good suggestions test meaningful outcomes — assertions that are hard to satisfy without actually doing the work correctly. Think about what makes an assertion *discriminating*: it passes when the skill genuinely succeeds and fails when it doesn't. + +Suggestions worth raising: +- An assertion that passed but would also pass for a clearly wrong output (e.g., checking filename existence but not file content) +- An important outcome you observed — good or bad — that no assertion covers at all +- An assertion that can't actually be verified from the available outputs + +Keep the bar high. The goal is to flag things the eval author would say "good catch" about, not to nitpick every assertion. + +### Step 7: Write Grading Results + +Save results to `{outputs_dir}/../grading.json` (sibling to outputs_dir). + +## Grading Criteria + +**PASS when**: +- The transcript or outputs clearly demonstrate the expectation is true +- Specific evidence can be cited +- The evidence reflects genuine substance, not just surface compliance (e.g., a file exists AND contains correct content, not just the right filename) + +**FAIL when**: +- No evidence found for the expectation +- Evidence contradicts the expectation +- The expectation cannot be verified from available information +- The evidence is superficial — the assertion is technically satisfied but the underlying task outcome is wrong or incomplete +- The output appears to meet the assertion by coincidence rather than by actually doing the work + +**When uncertain**: The burden of proof to pass is on the expectation. + +### Step 8: Read Executor Metrics and Timing + +1. If `{outputs_dir}/metrics.json` exists, read it and include in grading output +2. If `{outputs_dir}/../timing.json` exists, read it and include timing data + +## Output Format + +Write a JSON file with this structure: + +```json +{ + "expectations": [ + { + "text": "The output includes the name 'John Smith'", + "passed": true, + "evidence": "Found in transcript Step 3: 'Extracted names: John Smith, Sarah Johnson'" + }, + { + "text": "The spreadsheet has a SUM formula in cell B10", + "passed": false, + "evidence": "No spreadsheet was created. The output was a text file." + }, + { + "text": "The assistant used the skill's OCR script", + "passed": true, + "evidence": "Transcript Step 2 shows: 'Tool: Bash - python ocr_script.py image.png'" + } + ], + "summary": { + "passed": 2, + "failed": 1, + "total": 3, + "pass_rate": 0.67 + }, + "execution_metrics": { + "tool_calls": { + "Read": 5, + "Write": 2, + "Bash": 8 + }, + "total_tool_calls": 15, + "total_steps": 6, + "errors_encountered": 0, + "output_chars": 12450, + "transcript_chars": 3200 + }, + "timing": { + "executor_duration_seconds": 165.0, + "grader_duration_seconds": 26.0, + "total_duration_seconds": 191.0 + }, + "claims": [ + { + "claim": "The form has 12 fillable fields", + "type": "factual", + "verified": true, + "evidence": "Counted 12 fields in field_info.json" + }, + { + "claim": "All required fields were populated", + "type": "quality", + "verified": false, + "evidence": "Reference section was left blank despite data being available" + } + ], + "user_notes_summary": { + "uncertainties": ["Used 2023 data, may be stale"], + "needs_review": [], + "workarounds": ["Fell back to text overlay for non-fillable fields"] + }, + "eval_feedback": { + "suggestions": [ + { + "assertion": "The output includes the name 'John Smith'", + "reason": "A hallucinated document that mentions the name would also pass — consider checking it appears as the primary contact with matching phone and email from the input" + }, + { + "reason": "No assertion checks whether the extracted phone numbers match the input — I observed incorrect numbers in the output that went uncaught" + } + ], + "overall": "Assertions check presence but not correctness. Consider adding content verification." + } +} +``` + +## Field Descriptions + +- **expectations**: Array of graded expectations + - **text**: The original expectation text + - **passed**: Boolean - true if expectation passes + - **evidence**: Specific quote or description supporting the verdict +- **summary**: Aggregate statistics + - **passed**: Count of passed expectations + - **failed**: Count of failed expectations + - **total**: Total expectations evaluated + - **pass_rate**: Fraction passed (0.0 to 1.0) +- **execution_metrics**: Copied from executor's metrics.json (if available) + - **output_chars**: Total character count of output files (proxy for tokens) + - **transcript_chars**: Character count of transcript +- **timing**: Wall clock timing from timing.json (if available) + - **executor_duration_seconds**: Time spent in executor subagent + - **total_duration_seconds**: Total elapsed time for the run +- **claims**: Extracted and verified claims from the output + - **claim**: The statement being verified + - **type**: "factual", "process", or "quality" + - **verified**: Boolean - whether the claim holds + - **evidence**: Supporting or contradicting evidence +- **user_notes_summary**: Issues flagged by the executor + - **uncertainties**: Things the executor wasn't sure about + - **needs_review**: Items requiring human attention + - **workarounds**: Places where the skill didn't work as expected +- **eval_feedback**: Improvement suggestions for the evals (only when warranted) + - **suggestions**: List of concrete suggestions, each with a `reason` and optionally an `assertion` it relates to + - **overall**: Brief assessment — can be "No suggestions, evals look solid" if nothing to flag + +## Guidelines + +- **Be objective**: Base verdicts on evidence, not assumptions +- **Be specific**: Quote the exact text that supports your verdict +- **Be thorough**: Check both transcript and output files +- **Be consistent**: Apply the same standard to each expectation +- **Explain failures**: Make it clear why evidence was insufficient +- **No partial credit**: Each expectation is pass or fail, not partial diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/assets/eval_review.html b/libs/hexagent_demo/backend/skills/examples/skill-creator/assets/eval_review.html new file mode 100644 index 00000000..938ff32a --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/assets/eval_review.html @@ -0,0 +1,146 @@ + + + + + + Eval Set Review - __SKILL_NAME_PLACEHOLDER__ + + + + + + +

Eval Set Review: __SKILL_NAME_PLACEHOLDER__

+

Current description: __SKILL_DESCRIPTION_PLACEHOLDER__

+ +
+ + +
+ + + + + + + + + + +
QueryShould TriggerActions
+ +

+ + + + diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/eval-viewer/generate_review.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/eval-viewer/generate_review.py new file mode 100644 index 00000000..7fa59786 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/eval-viewer/generate_review.py @@ -0,0 +1,471 @@ +#!/usr/bin/env python3 +"""Generate and serve a review page for eval results. + +Reads the workspace directory, discovers runs (directories with outputs/), +embeds all output data into a self-contained HTML page, and serves it via +a tiny HTTP server. Feedback auto-saves to feedback.json in the workspace. + +Usage: + python generate_review.py [--port PORT] [--skill-name NAME] + python generate_review.py --previous-feedback /path/to/old/feedback.json + +No dependencies beyond the Python stdlib are required. +""" + +import argparse +import base64 +import json +import mimetypes +import os +import re +import signal +import subprocess +import sys +import time +import webbrowser +from functools import partial +from http.server import HTTPServer, BaseHTTPRequestHandler +from pathlib import Path + +# Files to exclude from output listings +METADATA_FILES = {"transcript.md", "user_notes.md", "metrics.json"} + +# Extensions we render as inline text +TEXT_EXTENSIONS = { + ".txt", ".md", ".json", ".csv", ".py", ".js", ".ts", ".tsx", ".jsx", + ".yaml", ".yml", ".xml", ".html", ".css", ".sh", ".rb", ".go", ".rs", + ".java", ".c", ".cpp", ".h", ".hpp", ".sql", ".r", ".toml", +} + +# Extensions we render as inline images +IMAGE_EXTENSIONS = {".png", ".jpg", ".jpeg", ".gif", ".svg", ".webp"} + +# MIME type overrides for common types +MIME_OVERRIDES = { + ".svg": "image/svg+xml", + ".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", + ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", + ".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation", +} + + +def get_mime_type(path: Path) -> str: + ext = path.suffix.lower() + if ext in MIME_OVERRIDES: + return MIME_OVERRIDES[ext] + mime, _ = mimetypes.guess_type(str(path)) + return mime or "application/octet-stream" + + +def find_runs(workspace: Path) -> list[dict]: + """Recursively find directories that contain an outputs/ subdirectory.""" + runs: list[dict] = [] + _find_runs_recursive(workspace, workspace, runs) + runs.sort(key=lambda r: (r.get("eval_id", float("inf")), r["id"])) + return runs + + +def _find_runs_recursive(root: Path, current: Path, runs: list[dict]) -> None: + if not current.is_dir(): + return + + outputs_dir = current / "outputs" + if outputs_dir.is_dir(): + run = build_run(root, current) + if run: + runs.append(run) + return + + skip = {"node_modules", ".git", "__pycache__", "skill", "inputs"} + for child in sorted(current.iterdir()): + if child.is_dir() and child.name not in skip: + _find_runs_recursive(root, child, runs) + + +def build_run(root: Path, run_dir: Path) -> dict | None: + """Build a run dict with prompt, outputs, and grading data.""" + prompt = "" + eval_id = None + + # Try eval_metadata.json + for candidate in [run_dir / "eval_metadata.json", run_dir.parent / "eval_metadata.json"]: + if candidate.exists(): + try: + metadata = json.loads(candidate.read_text()) + prompt = metadata.get("prompt", "") + eval_id = metadata.get("eval_id") + except (json.JSONDecodeError, OSError): + pass + if prompt: + break + + # Fall back to transcript.md + if not prompt: + for candidate in [run_dir / "transcript.md", run_dir / "outputs" / "transcript.md"]: + if candidate.exists(): + try: + text = candidate.read_text() + match = re.search(r"## Eval Prompt\n\n([\s\S]*?)(?=\n##|$)", text) + if match: + prompt = match.group(1).strip() + except OSError: + pass + if prompt: + break + + if not prompt: + prompt = "(No prompt found)" + + run_id = str(run_dir.relative_to(root)).replace("/", "-").replace("\\", "-") + + # Collect output files + outputs_dir = run_dir / "outputs" + output_files: list[dict] = [] + if outputs_dir.is_dir(): + for f in sorted(outputs_dir.iterdir()): + if f.is_file() and f.name not in METADATA_FILES: + output_files.append(embed_file(f)) + + # Load grading if present + grading = None + for candidate in [run_dir / "grading.json", run_dir.parent / "grading.json"]: + if candidate.exists(): + try: + grading = json.loads(candidate.read_text()) + except (json.JSONDecodeError, OSError): + pass + if grading: + break + + return { + "id": run_id, + "prompt": prompt, + "eval_id": eval_id, + "outputs": output_files, + "grading": grading, + } + + +def embed_file(path: Path) -> dict: + """Read a file and return an embedded representation.""" + ext = path.suffix.lower() + mime = get_mime_type(path) + + if ext in TEXT_EXTENSIONS: + try: + content = path.read_text(errors="replace") + except OSError: + content = "(Error reading file)" + return { + "name": path.name, + "type": "text", + "content": content, + } + elif ext in IMAGE_EXTENSIONS: + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "image", + "mime": mime, + "data_uri": f"data:{mime};base64,{b64}", + } + elif ext == ".pdf": + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "pdf", + "data_uri": f"data:{mime};base64,{b64}", + } + elif ext == ".xlsx": + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "xlsx", + "data_b64": b64, + } + else: + # Binary / unknown — base64 download link + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "binary", + "mime": mime, + "data_uri": f"data:{mime};base64,{b64}", + } + + +def load_previous_iteration(workspace: Path) -> dict[str, dict]: + """Load previous iteration's feedback and outputs. + + Returns a map of run_id -> {"feedback": str, "outputs": list[dict]}. + """ + result: dict[str, dict] = {} + + # Load feedback + feedback_map: dict[str, str] = {} + feedback_path = workspace / "feedback.json" + if feedback_path.exists(): + try: + data = json.loads(feedback_path.read_text()) + feedback_map = { + r["run_id"]: r["feedback"] + for r in data.get("reviews", []) + if r.get("feedback", "").strip() + } + except (json.JSONDecodeError, OSError, KeyError): + pass + + # Load runs (to get outputs) + prev_runs = find_runs(workspace) + for run in prev_runs: + result[run["id"]] = { + "feedback": feedback_map.get(run["id"], ""), + "outputs": run.get("outputs", []), + } + + # Also add feedback for run_ids that had feedback but no matching run + for run_id, fb in feedback_map.items(): + if run_id not in result: + result[run_id] = {"feedback": fb, "outputs": []} + + return result + + +def generate_html( + runs: list[dict], + skill_name: str, + previous: dict[str, dict] | None = None, + benchmark: dict | None = None, +) -> str: + """Generate the complete standalone HTML page with embedded data.""" + template_path = Path(__file__).parent / "viewer.html" + template = template_path.read_text() + + # Build previous_feedback and previous_outputs maps for the template + previous_feedback: dict[str, str] = {} + previous_outputs: dict[str, list[dict]] = {} + if previous: + for run_id, data in previous.items(): + if data.get("feedback"): + previous_feedback[run_id] = data["feedback"] + if data.get("outputs"): + previous_outputs[run_id] = data["outputs"] + + embedded = { + "skill_name": skill_name, + "runs": runs, + "previous_feedback": previous_feedback, + "previous_outputs": previous_outputs, + } + if benchmark: + embedded["benchmark"] = benchmark + + data_json = json.dumps(embedded) + + return template.replace("/*__EMBEDDED_DATA__*/", f"const EMBEDDED_DATA = {data_json};") + + +# --------------------------------------------------------------------------- +# HTTP server (stdlib only, zero dependencies) +# --------------------------------------------------------------------------- + +def _kill_port(port: int) -> None: + """Kill any process listening on the given port.""" + try: + result = subprocess.run( + ["lsof", "-ti", f":{port}"], + capture_output=True, text=True, timeout=5, + ) + for pid_str in result.stdout.strip().split("\n"): + if pid_str.strip(): + try: + os.kill(int(pid_str.strip()), signal.SIGTERM) + except (ProcessLookupError, ValueError): + pass + if result.stdout.strip(): + time.sleep(0.5) + except subprocess.TimeoutExpired: + pass + except FileNotFoundError: + print("Note: lsof not found, cannot check if port is in use", file=sys.stderr) + +class ReviewHandler(BaseHTTPRequestHandler): + """Serves the review HTML and handles feedback saves. + + Regenerates the HTML on each page load so that refreshing the browser + picks up new eval outputs without restarting the server. + """ + + def __init__( + self, + workspace: Path, + skill_name: str, + feedback_path: Path, + previous: dict[str, dict], + benchmark_path: Path | None, + *args, + **kwargs, + ): + self.workspace = workspace + self.skill_name = skill_name + self.feedback_path = feedback_path + self.previous = previous + self.benchmark_path = benchmark_path + super().__init__(*args, **kwargs) + + def do_GET(self) -> None: + if self.path == "/" or self.path == "/index.html": + # Regenerate HTML on each request (re-scans workspace for new outputs) + runs = find_runs(self.workspace) + benchmark = None + if self.benchmark_path and self.benchmark_path.exists(): + try: + benchmark = json.loads(self.benchmark_path.read_text()) + except (json.JSONDecodeError, OSError): + pass + html = generate_html(runs, self.skill_name, self.previous, benchmark) + content = html.encode("utf-8") + self.send_response(200) + self.send_header("Content-Type", "text/html; charset=utf-8") + self.send_header("Content-Length", str(len(content))) + self.end_headers() + self.wfile.write(content) + elif self.path == "/api/feedback": + data = b"{}" + if self.feedback_path.exists(): + data = self.feedback_path.read_bytes() + self.send_response(200) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(data))) + self.end_headers() + self.wfile.write(data) + else: + self.send_error(404) + + def do_POST(self) -> None: + if self.path == "/api/feedback": + length = int(self.headers.get("Content-Length", 0)) + body = self.rfile.read(length) + try: + data = json.loads(body) + if not isinstance(data, dict) or "reviews" not in data: + raise ValueError("Expected JSON object with 'reviews' key") + self.feedback_path.write_text(json.dumps(data, indent=2) + "\n") + resp = b'{"ok":true}' + self.send_response(200) + except (json.JSONDecodeError, OSError, ValueError) as e: + resp = json.dumps({"error": str(e)}).encode() + self.send_response(500) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(resp))) + self.end_headers() + self.wfile.write(resp) + else: + self.send_error(404) + + def log_message(self, format: str, *args: object) -> None: + # Suppress request logging to keep terminal clean + pass + + +def main() -> None: + parser = argparse.ArgumentParser(description="Generate and serve eval review") + parser.add_argument("workspace", type=Path, help="Path to workspace directory") + parser.add_argument("--port", "-p", type=int, default=3117, help="Server port (default: 3117)") + parser.add_argument("--skill-name", "-n", type=str, default=None, help="Skill name for header") + parser.add_argument( + "--previous-workspace", type=Path, default=None, + help="Path to previous iteration's workspace (shows old outputs and feedback as context)", + ) + parser.add_argument( + "--benchmark", type=Path, default=None, + help="Path to benchmark.json to show in the Benchmark tab", + ) + parser.add_argument( + "--static", "-s", type=Path, default=None, + help="Write standalone HTML to this path instead of starting a server", + ) + args = parser.parse_args() + + workspace = args.workspace.resolve() + if not workspace.is_dir(): + print(f"Error: {workspace} is not a directory", file=sys.stderr) + sys.exit(1) + + runs = find_runs(workspace) + if not runs: + print(f"No runs found in {workspace}", file=sys.stderr) + sys.exit(1) + + skill_name = args.skill_name or workspace.name.replace("-workspace", "") + feedback_path = workspace / "feedback.json" + + previous: dict[str, dict] = {} + if args.previous_workspace: + previous = load_previous_iteration(args.previous_workspace.resolve()) + + benchmark_path = args.benchmark.resolve() if args.benchmark else None + benchmark = None + if benchmark_path and benchmark_path.exists(): + try: + benchmark = json.loads(benchmark_path.read_text()) + except (json.JSONDecodeError, OSError): + pass + + if args.static: + html = generate_html(runs, skill_name, previous, benchmark) + args.static.parent.mkdir(parents=True, exist_ok=True) + args.static.write_text(html) + print(f"\n Static viewer written to: {args.static}\n") + sys.exit(0) + + # Kill any existing process on the target port + port = args.port + _kill_port(port) + handler = partial(ReviewHandler, workspace, skill_name, feedback_path, previous, benchmark_path) + try: + server = HTTPServer(("127.0.0.1", port), handler) + except OSError: + # Port still in use after kill attempt — find a free one + server = HTTPServer(("127.0.0.1", 0), handler) + port = server.server_address[1] + + url = f"http://localhost:{port}" + print(f"\n Eval Viewer") + print(f" ─────────────────────────────────") + print(f" URL: {url}") + print(f" Workspace: {workspace}") + print(f" Feedback: {feedback_path}") + if previous: + print(f" Previous: {args.previous_workspace} ({len(previous)} runs)") + if benchmark_path: + print(f" Benchmark: {benchmark_path}") + print(f"\n Press Ctrl+C to stop.\n") + + webbrowser.open(url) + + try: + server.serve_forever() + except KeyboardInterrupt: + print("\nStopped.") + server.server_close() + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/eval-viewer/viewer.html b/libs/hexagent_demo/backend/skills/examples/skill-creator/eval-viewer/viewer.html new file mode 100644 index 00000000..6d8e9634 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/eval-viewer/viewer.html @@ -0,0 +1,1325 @@ + + + + + + Eval Review + + + + + + + +
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+ + + + diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/references/output-patterns.md b/libs/hexagent_demo/backend/skills/examples/skill-creator/references/output-patterns.md new file mode 100644 index 00000000..073ddda5 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/references/output-patterns.md @@ -0,0 +1,82 @@ +# Output Patterns + +Use these patterns when skills need to produce consistent, high-quality output. + +## Template Pattern + +Provide templates for output format. Match the level of strictness to your needs. + +**For strict requirements (like API responses or data formats):** + +```markdown +## Report structure + +ALWAYS use this exact template structure: + +# [Analysis Title] + +## Executive summary +[One-paragraph overview of key findings] + +## Key findings +- Finding 1 with supporting data +- Finding 2 with supporting data +- Finding 3 with supporting data + +## Recommendations +1. Specific actionable recommendation +2. Specific actionable recommendation +``` + +**For flexible guidance (when adaptation is useful):** + +```markdown +## Report structure + +Here is a sensible default format, but use your best judgment: + +# [Analysis Title] + +## Executive summary +[Overview] + +## Key findings +[Adapt sections based on what you discover] + +## Recommendations +[Tailor to the specific context] + +Adjust sections as needed for the specific analysis type. +``` + +## Examples Pattern + +For skills where output quality depends on seeing examples, provide input/output pairs: + +```markdown +## Commit message format + +Generate commit messages following these examples: + +**Example 1:** +Input: Added user authentication with JWT tokens +Output: +``` +feat(auth): implement JWT-based authentication + +Add login endpoint and token validation middleware +``` + +**Example 2:** +Input: Fixed bug where dates displayed incorrectly in reports +Output: +``` +fix(reports): correct date formatting in timezone conversion + +Use UTC timestamps consistently across report generation +``` + +Follow this style: type(scope): brief description, then detailed explanation. +``` + +Examples help Claude understand the desired style and level of detail more clearly than descriptions alone. diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/references/schemas.md b/libs/hexagent_demo/backend/skills/examples/skill-creator/references/schemas.md new file mode 100644 index 00000000..b6eeaa2d --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/references/schemas.md @@ -0,0 +1,430 @@ +# JSON Schemas + +This document defines the JSON schemas used by skill-creator. + +--- + +## evals.json + +Defines the evals for a skill. Located at `evals/evals.json` within the skill directory. + +```json +{ + "skill_name": "example-skill", + "evals": [ + { + "id": 1, + "prompt": "User's example prompt", + "expected_output": "Description of expected result", + "files": ["evals/files/sample1.pdf"], + "expectations": [ + "The output includes X", + "The skill used script Y" + ] + } + ] +} +``` + +**Fields:** +- `skill_name`: Name matching the skill's frontmatter +- `evals[].id`: Unique integer identifier +- `evals[].prompt`: The task to execute +- `evals[].expected_output`: Human-readable description of success +- `evals[].files`: Optional list of input file paths (relative to skill root) +- `evals[].expectations`: List of verifiable statements + +--- + +## history.json + +Tracks version progression in Improve mode. Located at workspace root. + +```json +{ + "started_at": "2026-01-15T10:30:00Z", + "skill_name": "pdf", + "current_best": "v2", + "iterations": [ + { + "version": "v0", + "parent": null, + "expectation_pass_rate": 0.65, + "grading_result": "baseline", + "is_current_best": false + }, + { + "version": "v1", + "parent": "v0", + "expectation_pass_rate": 0.75, + "grading_result": "won", + "is_current_best": false + }, + { + "version": "v2", + "parent": "v1", + "expectation_pass_rate": 0.85, + "grading_result": "won", + "is_current_best": true + } + ] +} +``` + +**Fields:** +- `started_at`: ISO timestamp of when improvement started +- `skill_name`: Name of the skill being improved +- `current_best`: Version identifier of the best performer +- `iterations[].version`: Version identifier (v0, v1, ...) +- `iterations[].parent`: Parent version this was derived from +- `iterations[].expectation_pass_rate`: Pass rate from grading +- `iterations[].grading_result`: "baseline", "won", "lost", or "tie" +- `iterations[].is_current_best`: Whether this is the current best version + +--- + +## grading.json + +Output from the grader agent. Located at `/grading.json`. + +```json +{ + "expectations": [ + { + "text": "The output includes the name 'John Smith'", + "passed": true, + "evidence": "Found in transcript Step 3: 'Extracted names: John Smith, Sarah Johnson'" + }, + { + "text": "The spreadsheet has a SUM formula in cell B10", + "passed": false, + "evidence": "No spreadsheet was created. The output was a text file." + } + ], + "summary": { + "passed": 2, + "failed": 1, + "total": 3, + "pass_rate": 0.67 + }, + "execution_metrics": { + "tool_calls": { + "Read": 5, + "Write": 2, + "Bash": 8 + }, + "total_tool_calls": 15, + "total_steps": 6, + "errors_encountered": 0, + "output_chars": 12450, + "transcript_chars": 3200 + }, + "timing": { + "executor_duration_seconds": 165.0, + "grader_duration_seconds": 26.0, + "total_duration_seconds": 191.0 + }, + "claims": [ + { + "claim": "The form has 12 fillable fields", + "type": "factual", + "verified": true, + "evidence": "Counted 12 fields in field_info.json" + } + ], + "user_notes_summary": { + "uncertainties": ["Used 2023 data, may be stale"], + "needs_review": [], + "workarounds": ["Fell back to text overlay for non-fillable fields"] + }, + "eval_feedback": { + "suggestions": [ + { + "assertion": "The output includes the name 'John Smith'", + "reason": "A hallucinated document that mentions the name would also pass" + } + ], + "overall": "Assertions check presence but not correctness." + } +} +``` + +**Fields:** +- `expectations[]`: Graded expectations with evidence +- `summary`: Aggregate pass/fail counts +- `execution_metrics`: Tool usage and output size (from executor's metrics.json) +- `timing`: Wall clock timing (from timing.json) +- `claims`: Extracted and verified claims from the output +- `user_notes_summary`: Issues flagged by the executor +- `eval_feedback`: (optional) Improvement suggestions for the evals, only present when the grader identifies issues worth raising + +--- + +## metrics.json + +Output from the executor agent. Located at `/outputs/metrics.json`. + +```json +{ + "tool_calls": { + "Read": 5, + "Write": 2, + "Bash": 8, + "Edit": 1, + "Glob": 2, + "Grep": 0 + }, + "total_tool_calls": 18, + "total_steps": 6, + "files_created": ["filled_form.pdf", "field_values.json"], + "errors_encountered": 0, + "output_chars": 12450, + "transcript_chars": 3200 +} +``` + +**Fields:** +- `tool_calls`: Count per tool type +- `total_tool_calls`: Sum of all tool calls +- `total_steps`: Number of major execution steps +- `files_created`: List of output files created +- `errors_encountered`: Number of errors during execution +- `output_chars`: Total character count of output files +- `transcript_chars`: Character count of transcript + +--- + +## timing.json + +Wall clock timing for a run. Located at `/timing.json`. + +**How to capture:** When a subagent task completes, the task notification includes `total_tokens` and `duration_ms`. Save these immediately — they are not persisted anywhere else and cannot be recovered after the fact. + +```json +{ + "total_tokens": 84852, + "duration_ms": 23332, + "total_duration_seconds": 23.3, + "executor_start": "2026-01-15T10:30:00Z", + "executor_end": "2026-01-15T10:32:45Z", + "executor_duration_seconds": 165.0, + "grader_start": "2026-01-15T10:32:46Z", + "grader_end": "2026-01-15T10:33:12Z", + "grader_duration_seconds": 26.0 +} +``` + +--- + +## benchmark.json + +Output from Benchmark mode. Located at `benchmarks//benchmark.json`. + +```json +{ + "metadata": { + "skill_name": "pdf", + "skill_path": "/path/to/pdf", + "executor_model": "claude-sonnet-4-20250514", + "analyzer_model": "most-capable-model", + "timestamp": "2026-01-15T10:30:00Z", + "evals_run": [1, 2, 3], + "runs_per_configuration": 3 + }, + + "runs": [ + { + "eval_id": 1, + "eval_name": "Ocean", + "configuration": "with_skill", + "run_number": 1, + "result": { + "pass_rate": 0.85, + "passed": 6, + "failed": 1, + "total": 7, + "time_seconds": 42.5, + "tokens": 3800, + "tool_calls": 18, + "errors": 0 + }, + "expectations": [ + {"text": "...", "passed": true, "evidence": "..."} + ], + "notes": [ + "Used 2023 data, may be stale", + "Fell back to text overlay for non-fillable fields" + ] + } + ], + + "run_summary": { + "with_skill": { + "pass_rate": {"mean": 0.85, "stddev": 0.05, "min": 0.80, "max": 0.90}, + "time_seconds": {"mean": 45.0, "stddev": 12.0, "min": 32.0, "max": 58.0}, + "tokens": {"mean": 3800, "stddev": 400, "min": 3200, "max": 4100} + }, + "without_skill": { + "pass_rate": {"mean": 0.35, "stddev": 0.08, "min": 0.28, "max": 0.45}, + "time_seconds": {"mean": 32.0, "stddev": 8.0, "min": 24.0, "max": 42.0}, + "tokens": {"mean": 2100, "stddev": 300, "min": 1800, "max": 2500} + }, + "delta": { + "pass_rate": "+0.50", + "time_seconds": "+13.0", + "tokens": "+1700" + } + }, + + "notes": [ + "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value", + "Eval 3 shows high variance (50% ± 40%) - may be flaky or model-dependent", + "Without-skill runs consistently fail on table extraction expectations", + "Skill adds 13s average execution time but improves pass rate by 50%" + ] +} +``` + +**Fields:** +- `metadata`: Information about the benchmark run + - `skill_name`: Name of the skill + - `timestamp`: When the benchmark was run + - `evals_run`: List of eval names or IDs + - `runs_per_configuration`: Number of runs per config (e.g. 3) +- `runs[]`: Individual run results + - `eval_id`: Numeric eval identifier + - `eval_name`: Human-readable eval name (used as section header in the viewer) + - `configuration`: Must be `"with_skill"` or `"without_skill"` (the viewer uses this exact string for grouping and color coding) + - `run_number`: Integer run number (1, 2, 3...) + - `result`: Nested object with `pass_rate`, `passed`, `total`, `time_seconds`, `tokens`, `errors` +- `run_summary`: Statistical aggregates per configuration + - `with_skill` / `without_skill`: Each contains `pass_rate`, `time_seconds`, `tokens` objects with `mean` and `stddev` fields + - `delta`: Difference strings like `"+0.50"`, `"+13.0"`, `"+1700"` +- `notes`: Freeform observations from the analyzer + +**Important:** The viewer reads these field names exactly. Using `config` instead of `configuration`, or putting `pass_rate` at the top level of a run instead of nested under `result`, will cause the viewer to show empty/zero values. Always reference this schema when generating benchmark.json manually. + +--- + +## comparison.json + +Output from blind comparator. Located at `/comparison-N.json`. + +```json +{ + "winner": "A", + "reasoning": "Output A provides a complete solution with proper formatting and all required fields. Output B is missing the date field and has formatting inconsistencies.", + "rubric": { + "A": { + "content": { + "correctness": 5, + "completeness": 5, + "accuracy": 4 + }, + "structure": { + "organization": 4, + "formatting": 5, + "usability": 4 + }, + "content_score": 4.7, + "structure_score": 4.3, + "overall_score": 9.0 + }, + "B": { + "content": { + "correctness": 3, + "completeness": 2, + "accuracy": 3 + }, + "structure": { + "organization": 3, + "formatting": 2, + "usability": 3 + }, + "content_score": 2.7, + "structure_score": 2.7, + "overall_score": 5.4 + } + }, + "output_quality": { + "A": { + "score": 9, + "strengths": ["Complete solution", "Well-formatted", "All fields present"], + "weaknesses": ["Minor style inconsistency in header"] + }, + "B": { + "score": 5, + "strengths": ["Readable output", "Correct basic structure"], + "weaknesses": ["Missing date field", "Formatting inconsistencies", "Partial data extraction"] + } + }, + "expectation_results": { + "A": { + "passed": 4, + "total": 5, + "pass_rate": 0.80, + "details": [ + {"text": "Output includes name", "passed": true} + ] + }, + "B": { + "passed": 3, + "total": 5, + "pass_rate": 0.60, + "details": [ + {"text": "Output includes name", "passed": true} + ] + } + } +} +``` + +--- + +## analysis.json + +Output from post-hoc analyzer. Located at `/analysis.json`. + +```json +{ + "comparison_summary": { + "winner": "A", + "winner_skill": "path/to/winner/skill", + "loser_skill": "path/to/loser/skill", + "comparator_reasoning": "Brief summary of why comparator chose winner" + }, + "winner_strengths": [ + "Clear step-by-step instructions for handling multi-page documents", + "Included validation script that caught formatting errors" + ], + "loser_weaknesses": [ + "Vague instruction 'process the document appropriately' led to inconsistent behavior", + "No script for validation, agent had to improvise" + ], + "instruction_following": { + "winner": { + "score": 9, + "issues": ["Minor: skipped optional logging step"] + }, + "loser": { + "score": 6, + "issues": [ + "Did not use the skill's formatting template", + "Invented own approach instead of following step 3" + ] + } + }, + "improvement_suggestions": [ + { + "priority": "high", + "category": "instructions", + "suggestion": "Replace 'process the document appropriately' with explicit steps", + "expected_impact": "Would eliminate ambiguity that caused inconsistent behavior" + } + ], + "transcript_insights": { + "winner_execution_pattern": "Read skill -> Followed 5-step process -> Used validation script", + "loser_execution_pattern": "Read skill -> Unclear on approach -> Tried 3 different methods" + } +} +``` diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/references/workflows.md b/libs/hexagent_demo/backend/skills/examples/skill-creator/references/workflows.md new file mode 100644 index 00000000..54b01740 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/references/workflows.md @@ -0,0 +1,28 @@ +# Workflow Patterns + +## Sequential Workflows + +For complex tasks, break operations into clear, sequential steps. It is often helpful to give Claude an overview of the process towards the beginning of SKILL.md: + +```markdown +Filling a PDF form involves these steps: + +1. Analyze the form (run analyze_form.py) +2. Create field mapping (edit fields.json) +3. Validate mapping (run validate_fields.py) +4. Fill the form (run fill_form.py) +5. Verify output (run verify_output.py) +``` + +## Conditional Workflows + +For tasks with branching logic, guide Claude through decision points: + +```markdown +1. Determine the modification type: + **Creating new content?** → Follow "Creation workflow" below + **Editing existing content?** → Follow "Editing workflow" below + +2. Creation workflow: [steps] +3. Editing workflow: [steps] +``` diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/aggregate_benchmark.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/aggregate_benchmark.py new file mode 100644 index 00000000..fa44b384 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/aggregate_benchmark.py @@ -0,0 +1,401 @@ +#!/usr/bin/env python3 +""" +Aggregate individual run results into benchmark summary statistics. + +Reads grading.json files from run directories and produces: +- run_summary with mean, stddev, min, max for each metric +- delta between with_skill and without_skill configurations + +Usage: + python aggregate_benchmark.py + +Example: + python aggregate_benchmark.py benchmarks/2026-01-15T10-30-00/ + +The script supports two directory layouts: + + Workspace layout (from skill-creator iterations): + / + └── eval-N/ + ├── with_skill/ + │ ├── run-1/grading.json + │ └── run-2/grading.json + └── without_skill/ + ├── run-1/grading.json + └── run-2/grading.json + + Legacy layout (with runs/ subdirectory): + / + └── runs/ + └── eval-N/ + ├── with_skill/ + │ └── run-1/grading.json + └── without_skill/ + └── run-1/grading.json +""" + +import argparse +import json +import math +import sys +from datetime import datetime, timezone +from pathlib import Path + + +def calculate_stats(values: list[float]) -> dict: + """Calculate mean, stddev, min, max for a list of values.""" + if not values: + return {"mean": 0.0, "stddev": 0.0, "min": 0.0, "max": 0.0} + + n = len(values) + mean = sum(values) / n + + if n > 1: + variance = sum((x - mean) ** 2 for x in values) / (n - 1) + stddev = math.sqrt(variance) + else: + stddev = 0.0 + + return { + "mean": round(mean, 4), + "stddev": round(stddev, 4), + "min": round(min(values), 4), + "max": round(max(values), 4) + } + + +def load_run_results(benchmark_dir: Path) -> dict: + """ + Load all run results from a benchmark directory. + + Returns dict keyed by config name (e.g. "with_skill"/"without_skill", + or "new_skill"/"old_skill"), each containing a list of run results. + """ + # Support both layouts: eval dirs directly under benchmark_dir, or under runs/ + runs_dir = benchmark_dir / "runs" + if runs_dir.exists(): + search_dir = runs_dir + elif list(benchmark_dir.glob("eval-*")): + search_dir = benchmark_dir + else: + print(f"No eval directories found in {benchmark_dir} or {benchmark_dir / 'runs'}") + return {} + + results: dict[str, list] = {} + + for eval_idx, eval_dir in enumerate(sorted(search_dir.glob("eval-*"))): + metadata_path = eval_dir / "eval_metadata.json" + if metadata_path.exists(): + try: + with open(metadata_path, encoding="utf-8") as mf: + eval_id = json.load(mf).get("eval_id", eval_idx) + except (json.JSONDecodeError, OSError): + eval_id = eval_idx + else: + try: + eval_id = int(eval_dir.name.split("-")[1]) + except ValueError: + eval_id = eval_idx + + # Discover config directories dynamically rather than hardcoding names + for config_dir in sorted(eval_dir.iterdir()): + if not config_dir.is_dir(): + continue + # Skip non-config directories (inputs, outputs, etc.) + if not list(config_dir.glob("run-*")): + continue + config = config_dir.name + if config not in results: + results[config] = [] + + for run_dir in sorted(config_dir.glob("run-*")): + run_number = int(run_dir.name.split("-")[1]) + grading_file = run_dir / "grading.json" + + if not grading_file.exists(): + print(f"Warning: grading.json not found in {run_dir}") + continue + + try: + with open(grading_file, encoding="utf-8") as f: + grading = json.load(f) + except json.JSONDecodeError as e: + print(f"Warning: Invalid JSON in {grading_file}: {e}") + continue + + # Extract metrics + result = { + "eval_id": eval_id, + "run_number": run_number, + "pass_rate": grading.get("summary", {}).get("pass_rate", 0.0), + "passed": grading.get("summary", {}).get("passed", 0), + "failed": grading.get("summary", {}).get("failed", 0), + "total": grading.get("summary", {}).get("total", 0), + } + + # Extract timing — check grading.json first, then sibling timing.json + timing = grading.get("timing", {}) + result["time_seconds"] = timing.get("total_duration_seconds", 0.0) + timing_file = run_dir / "timing.json" + if result["time_seconds"] == 0.0 and timing_file.exists(): + try: + with open(timing_file, encoding="utf-8") as tf: + timing_data = json.load(tf) + result["time_seconds"] = timing_data.get("total_duration_seconds", 0.0) + result["tokens"] = timing_data.get("total_tokens", 0) + except json.JSONDecodeError: + pass + + # Extract metrics if available + metrics = grading.get("execution_metrics", {}) + result["tool_calls"] = metrics.get("total_tool_calls", 0) + if not result.get("tokens"): + result["tokens"] = metrics.get("output_chars", 0) + result["errors"] = metrics.get("errors_encountered", 0) + + # Extract expectations — viewer requires fields: text, passed, evidence + raw_expectations = grading.get("expectations", []) + for exp in raw_expectations: + if "text" not in exp or "passed" not in exp: + print(f"Warning: expectation in {grading_file} missing required fields (text, passed, evidence): {exp}") + result["expectations"] = raw_expectations + + # Extract notes from user_notes_summary + notes_summary = grading.get("user_notes_summary", {}) + notes = [] + notes.extend(notes_summary.get("uncertainties", [])) + notes.extend(notes_summary.get("needs_review", [])) + notes.extend(notes_summary.get("workarounds", [])) + result["notes"] = notes + + results[config].append(result) + + return results + + +def aggregate_results(results: dict) -> dict: + """ + Aggregate run results into summary statistics. + + Returns run_summary with stats for each configuration and delta. + """ + run_summary = {} + configs = list(results.keys()) + + for config in configs: + runs = results.get(config, []) + + if not runs: + run_summary[config] = { + "pass_rate": {"mean": 0.0, "stddev": 0.0, "min": 0.0, "max": 0.0}, + "time_seconds": {"mean": 0.0, "stddev": 0.0, "min": 0.0, "max": 0.0}, + "tokens": {"mean": 0, "stddev": 0, "min": 0, "max": 0} + } + continue + + pass_rates = [r["pass_rate"] for r in runs] + times = [r["time_seconds"] for r in runs] + tokens = [r.get("tokens", 0) for r in runs] + + run_summary[config] = { + "pass_rate": calculate_stats(pass_rates), + "time_seconds": calculate_stats(times), + "tokens": calculate_stats(tokens) + } + + # Calculate delta between the first two configs (if two exist) + if len(configs) >= 2: + primary = run_summary.get(configs[0], {}) + baseline = run_summary.get(configs[1], {}) + else: + primary = run_summary.get(configs[0], {}) if configs else {} + baseline = {} + + delta_pass_rate = primary.get("pass_rate", {}).get("mean", 0) - baseline.get("pass_rate", {}).get("mean", 0) + delta_time = primary.get("time_seconds", {}).get("mean", 0) - baseline.get("time_seconds", {}).get("mean", 0) + delta_tokens = primary.get("tokens", {}).get("mean", 0) - baseline.get("tokens", {}).get("mean", 0) + + run_summary["delta"] = { + "pass_rate": f"{delta_pass_rate:+.2f}", + "time_seconds": f"{delta_time:+.1f}", + "tokens": f"{delta_tokens:+.0f}" + } + + return run_summary + + +def generate_benchmark(benchmark_dir: Path, skill_name: str = "", skill_path: str = "") -> dict: + """ + Generate complete benchmark.json from run results. + """ + results = load_run_results(benchmark_dir) + run_summary = aggregate_results(results) + + # Build runs array for benchmark.json + runs = [] + for config in results: + for result in results[config]: + runs.append({ + "eval_id": result["eval_id"], + "configuration": config, + "run_number": result["run_number"], + "result": { + "pass_rate": result["pass_rate"], + "passed": result["passed"], + "failed": result["failed"], + "total": result["total"], + "time_seconds": result["time_seconds"], + "tokens": result.get("tokens", 0), + "tool_calls": result.get("tool_calls", 0), + "errors": result.get("errors", 0) + }, + "expectations": result["expectations"], + "notes": result["notes"] + }) + + # Determine eval IDs from results + eval_ids = sorted(set( + r["eval_id"] + for config in results.values() + for r in config + )) + + benchmark = { + "metadata": { + "skill_name": skill_name or "", + "skill_path": skill_path or "", + "executor_model": "", + "analyzer_model": "", + "timestamp": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"), + "evals_run": eval_ids, + "runs_per_configuration": 3 + }, + "runs": runs, + "run_summary": run_summary, + "notes": [] # To be filled by analyzer + } + + return benchmark + + +def generate_markdown(benchmark: dict) -> str: + """Generate human-readable benchmark.md from benchmark data.""" + metadata = benchmark["metadata"] + run_summary = benchmark["run_summary"] + + # Determine config names (excluding "delta") + configs = [k for k in run_summary if k != "delta"] + config_a = configs[0] if len(configs) >= 1 else "config_a" + config_b = configs[1] if len(configs) >= 2 else "config_b" + label_a = config_a.replace("_", " ").title() + label_b = config_b.replace("_", " ").title() + + lines = [ + f"# Skill Benchmark: {metadata['skill_name']}", + "", + f"**Model**: {metadata['executor_model']}", + f"**Date**: {metadata['timestamp']}", + f"**Evals**: {', '.join(map(str, metadata['evals_run']))} ({metadata['runs_per_configuration']} runs each per configuration)", + "", + "## Summary", + "", + f"| Metric | {label_a} | {label_b} | Delta |", + "|--------|------------|---------------|-------|", + ] + + a_summary = run_summary.get(config_a, {}) + b_summary = run_summary.get(config_b, {}) + delta = run_summary.get("delta", {}) + + # Format pass rate + a_pr = a_summary.get("pass_rate", {}) + b_pr = b_summary.get("pass_rate", {}) + lines.append(f"| Pass Rate | {a_pr.get('mean', 0)*100:.0f}% ± {a_pr.get('stddev', 0)*100:.0f}% | {b_pr.get('mean', 0)*100:.0f}% ± {b_pr.get('stddev', 0)*100:.0f}% | {delta.get('pass_rate', '—')} |") + + # Format time + a_time = a_summary.get("time_seconds", {}) + b_time = b_summary.get("time_seconds", {}) + lines.append(f"| Time | {a_time.get('mean', 0):.1f}s ± {a_time.get('stddev', 0):.1f}s | {b_time.get('mean', 0):.1f}s ± {b_time.get('stddev', 0):.1f}s | {delta.get('time_seconds', '—')}s |") + + # Format tokens + a_tokens = a_summary.get("tokens", {}) + b_tokens = b_summary.get("tokens", {}) + lines.append(f"| Tokens | {a_tokens.get('mean', 0):.0f} ± {a_tokens.get('stddev', 0):.0f} | {b_tokens.get('mean', 0):.0f} ± {b_tokens.get('stddev', 0):.0f} | {delta.get('tokens', '—')} |") + + # Notes section + if benchmark.get("notes"): + lines.extend([ + "", + "## Notes", + "" + ]) + for note in benchmark["notes"]: + lines.append(f"- {note}") + + return "\n".join(lines) + + +def main(): + parser = argparse.ArgumentParser( + description="Aggregate benchmark run results into summary statistics" + ) + parser.add_argument( + "benchmark_dir", + type=Path, + help="Path to the benchmark directory" + ) + parser.add_argument( + "--skill-name", + default="", + help="Name of the skill being benchmarked" + ) + parser.add_argument( + "--skill-path", + default="", + help="Path to the skill being benchmarked" + ) + parser.add_argument( + "--output", "-o", + type=Path, + help="Output path for benchmark.json (default: /benchmark.json)" + ) + + args = parser.parse_args() + + if not args.benchmark_dir.exists(): + print(f"Directory not found: {args.benchmark_dir}") + sys.exit(1) + + # Generate benchmark + benchmark = generate_benchmark(args.benchmark_dir, args.skill_name, args.skill_path) + + # Determine output paths + output_json = args.output or (args.benchmark_dir / "benchmark.json") + output_md = output_json.with_suffix(".md") + + # Write benchmark.json + with open(output_json, "w", encoding="utf-8") as f: + json.dump(benchmark, f, indent=2) + print(f"Generated: {output_json}") + + # Write benchmark.md + markdown = generate_markdown(benchmark) + with open(output_md, "w", encoding="utf-8") as f: + f.write(markdown) + print(f"Generated: {output_md}") + + # Print summary + run_summary = benchmark["run_summary"] + configs = [k for k in run_summary if k != "delta"] + delta = run_summary.get("delta", {}) + + print(f"\nSummary:") + for config in configs: + pr = run_summary[config]["pass_rate"]["mean"] + label = config.replace("_", " ").title() + print(f" {label}: {pr*100:.1f}% pass rate") + print(f" Delta: {delta.get('pass_rate', '—')}") + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/generate_report.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/generate_report.py new file mode 100644 index 00000000..959e30a0 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/generate_report.py @@ -0,0 +1,326 @@ +#!/usr/bin/env python3 +"""Generate an HTML report from run_loop.py output. + +Takes the JSON output from run_loop.py and generates a visual HTML report +showing each description attempt with check/x for each test case. +Distinguishes between train and test queries. +""" + +import argparse +import html +import json +import sys +from pathlib import Path + + +def generate_html(data: dict, auto_refresh: bool = False, skill_name: str = "") -> str: + """Generate HTML report from loop output data. If auto_refresh is True, adds a meta refresh tag.""" + history = data.get("history", []) + holdout = data.get("holdout", 0) + title_prefix = html.escape(skill_name + " \u2014 ") if skill_name else "" + + # Get all unique queries from train and test sets, with should_trigger info + train_queries: list[dict] = [] + test_queries: list[dict] = [] + if history: + for r in history[0].get("train_results", history[0].get("results", [])): + train_queries.append({"query": r["query"], "should_trigger": r.get("should_trigger", True)}) + if history[0].get("test_results"): + for r in history[0].get("test_results", []): + test_queries.append({"query": r["query"], "should_trigger": r.get("should_trigger", True)}) + + refresh_tag = ' \n' if auto_refresh else "" + + html_parts = [""" + + + +""" + refresh_tag + """ """ + title_prefix + """Skill Description Optimization + + + + + + +

""" + title_prefix + """Skill Description Optimization

+
+ Optimizing your skill's description. This page updates automatically as Claude tests different versions of your skill's description. Each row is an iteration — a new description attempt. The columns show test queries: green checkmarks mean the skill triggered correctly (or correctly didn't trigger), red crosses mean it got it wrong. The "Train" score shows performance on queries used to improve the description; the "Test" score shows performance on held-out queries the optimizer hasn't seen. When it's done, Claude will apply the best-performing description to your skill. +
+"""] + + # Summary section + best_test_score = data.get('best_test_score') + best_train_score = data.get('best_train_score') + html_parts.append(f""" +
+

Original: {html.escape(data.get('original_description', 'N/A'))}

+

Best: {html.escape(data.get('best_description', 'N/A'))}

+

Best Score: {data.get('best_score', 'N/A')} {'(test)' if best_test_score else '(train)'}

+

Iterations: {data.get('iterations_run', 0)} | Train: {data.get('train_size', '?')} | Test: {data.get('test_size', '?')}

+
+""") + + # Legend + html_parts.append(""" +
+ Query columns: + Should trigger + Should NOT trigger + Train + Test +
+""") + + # Table header + html_parts.append(""" +
+ + + + + + + +""") + + # Add column headers for train queries + for qinfo in train_queries: + polarity = "positive-col" if qinfo["should_trigger"] else "negative-col" + html_parts.append(f' \n') + + # Add column headers for test queries (different color) + for qinfo in test_queries: + polarity = "positive-col" if qinfo["should_trigger"] else "negative-col" + html_parts.append(f' \n') + + html_parts.append(""" + + +""") + + # Find best iteration for highlighting + if test_queries: + best_iter = max(history, key=lambda h: h.get("test_passed") or 0).get("iteration") + else: + best_iter = max(history, key=lambda h: h.get("train_passed", h.get("passed", 0))).get("iteration") + + # Add rows for each iteration + for h in history: + iteration = h.get("iteration", "?") + train_passed = h.get("train_passed", h.get("passed", 0)) + train_total = h.get("train_total", h.get("total", 0)) + test_passed = h.get("test_passed") + test_total = h.get("test_total") + description = h.get("description", "") + train_results = h.get("train_results", h.get("results", [])) + test_results = h.get("test_results", []) + + # Create lookups for results by query + train_by_query = {r["query"]: r for r in train_results} + test_by_query = {r["query"]: r for r in test_results} if test_results else {} + + # Compute aggregate correct/total runs across all retries + def aggregate_runs(results: list[dict]) -> tuple[int, int]: + correct = 0 + total = 0 + for r in results: + runs = r.get("runs", 0) + triggers = r.get("triggers", 0) + total += runs + if r.get("should_trigger", True): + correct += triggers + else: + correct += runs - triggers + return correct, total + + train_correct, train_runs = aggregate_runs(train_results) + test_correct, test_runs = aggregate_runs(test_results) + + # Determine score classes + def score_class(correct: int, total: int) -> str: + if total > 0: + ratio = correct / total + if ratio >= 0.8: + return "score-good" + elif ratio >= 0.5: + return "score-ok" + return "score-bad" + + train_class = score_class(train_correct, train_runs) + test_class = score_class(test_correct, test_runs) + + row_class = "best-row" if iteration == best_iter else "" + + html_parts.append(f""" + + + + +""") + + # Add result for each train query + for qinfo in train_queries: + r = train_by_query.get(qinfo["query"], {}) + did_pass = r.get("pass", False) + triggers = r.get("triggers", 0) + runs = r.get("runs", 0) + + icon = "✓" if did_pass else "✗" + css_class = "pass" if did_pass else "fail" + + html_parts.append(f' \n') + + # Add result for each test query (with different background) + for qinfo in test_queries: + r = test_by_query.get(qinfo["query"], {}) + did_pass = r.get("pass", False) + triggers = r.get("triggers", 0) + runs = r.get("runs", 0) + + icon = "✓" if did_pass else "✗" + css_class = "pass" if did_pass else "fail" + + html_parts.append(f' \n') + + html_parts.append(" \n") + + html_parts.append(""" +
IterTrainTestDescription{html.escape(qinfo["query"])}{html.escape(qinfo["query"])}
{iteration}{train_correct}/{train_runs}{test_correct}/{test_runs}{html.escape(description)}{icon}{triggers}/{runs}{icon}{triggers}/{runs}
+
+""") + + html_parts.append(""" + + +""") + + return "".join(html_parts) + + +def main(): + parser = argparse.ArgumentParser(description="Generate HTML report from run_loop output") + parser.add_argument("input", help="Path to JSON output from run_loop.py (or - for stdin)") + parser.add_argument("-o", "--output", default=None, help="Output HTML file (default: stdout)") + parser.add_argument("--skill-name", default="", help="Skill name to include in the report title") + args = parser.parse_args() + + if args.input == "-": + data = json.load(sys.stdin) + else: + data = json.loads(Path(args.input).read_text()) + + html_output = generate_html(data, skill_name=args.skill_name) + + if args.output: + Path(args.output).write_text(html_output) + print(f"Report written to {args.output}", file=sys.stderr) + else: + print(html_output) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/improve_description.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/improve_description.py new file mode 100644 index 00000000..9a3ad7e7 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/improve_description.py @@ -0,0 +1,247 @@ +#!/usr/bin/env python3 +"""Improve a skill description based on eval results. + +Takes eval results (from run_eval.py) and generates an improved description +by calling `claude -p` as a subprocess (same auth pattern as run_eval.py — +uses the session's Claude Code auth, no separate ANTHROPIC_API_KEY needed). +""" + +import argparse +import json +import os +import re +import subprocess +import sys +from pathlib import Path + +from scripts.utils import parse_skill_md + + +def _call_claude(prompt: str, model: str | None, timeout: int = 300) -> str: + """Run `claude -p` with the prompt on stdin and return the text response. + + Prompt goes over stdin (not argv) because it embeds the full SKILL.md + body and can easily exceed comfortable argv length. + """ + cmd = ["claude", "-p", "--output-format", "text"] + if model: + cmd.extend(["--model", model]) + + # Remove CLAUDECODE env var to allow nesting claude -p inside a + # Claude Code session. The guard is for interactive terminal conflicts; + # programmatic subprocess usage is safe. Same pattern as run_eval.py. + env = {k: v for k, v in os.environ.items() if k != "CLAUDECODE"} + + result = subprocess.run( + cmd, + input=prompt, + capture_output=True, + text=True, + env=env, + timeout=timeout, + ) + if result.returncode != 0: + raise RuntimeError( + f"claude -p exited {result.returncode}\nstderr: {result.stderr}" + ) + return result.stdout + + +def improve_description( + skill_name: str, + skill_content: str, + current_description: str, + eval_results: dict, + history: list[dict], + model: str, + test_results: dict | None = None, + log_dir: Path | None = None, + iteration: int | None = None, +) -> str: + """Call Claude to improve the description based on eval results.""" + failed_triggers = [ + r for r in eval_results["results"] + if r["should_trigger"] and not r["pass"] + ] + false_triggers = [ + r for r in eval_results["results"] + if not r["should_trigger"] and not r["pass"] + ] + + # Build scores summary + train_score = f"{eval_results['summary']['passed']}/{eval_results['summary']['total']}" + if test_results: + test_score = f"{test_results['summary']['passed']}/{test_results['summary']['total']}" + scores_summary = f"Train: {train_score}, Test: {test_score}" + else: + scores_summary = f"Train: {train_score}" + + prompt = f"""You are optimizing a skill description for a Claude Code skill called "{skill_name}". A "skill" is sort of like a prompt, but with progressive disclosure -- there's a title and description that Claude sees when deciding whether to use the skill, and then if it does use the skill, it reads the .md file which has lots more details and potentially links to other resources in the skill folder like helper files and scripts and additional documentation or examples. + +The description appears in Claude's "available_skills" list. When a user sends a query, Claude decides whether to invoke the skill based solely on the title and on this description. Your goal is to write a description that triggers for relevant queries, and doesn't trigger for irrelevant ones. + +Here's the current description: + +"{current_description}" + + +Current scores ({scores_summary}): + +""" + if failed_triggers: + prompt += "FAILED TO TRIGGER (should have triggered but didn't):\n" + for r in failed_triggers: + prompt += f' - "{r["query"]}" (triggered {r["triggers"]}/{r["runs"]} times)\n' + prompt += "\n" + + if false_triggers: + prompt += "FALSE TRIGGERS (triggered but shouldn't have):\n" + for r in false_triggers: + prompt += f' - "{r["query"]}" (triggered {r["triggers"]}/{r["runs"]} times)\n' + prompt += "\n" + + if history: + prompt += "PREVIOUS ATTEMPTS (do NOT repeat these — try something structurally different):\n\n" + for h in history: + train_s = f"{h.get('train_passed', h.get('passed', 0))}/{h.get('train_total', h.get('total', 0))}" + test_s = f"{h.get('test_passed', '?')}/{h.get('test_total', '?')}" if h.get('test_passed') is not None else None + score_str = f"train={train_s}" + (f", test={test_s}" if test_s else "") + prompt += f'\n' + prompt += f'Description: "{h["description"]}"\n' + if "results" in h: + prompt += "Train results:\n" + for r in h["results"]: + status = "PASS" if r["pass"] else "FAIL" + prompt += f' [{status}] "{r["query"][:80]}" (triggered {r["triggers"]}/{r["runs"]})\n' + if h.get("note"): + prompt += f'Note: {h["note"]}\n' + prompt += "\n\n" + + prompt += f""" + +Skill content (for context on what the skill does): + +{skill_content} + + +Based on the failures, write a new and improved description that is more likely to trigger correctly. When I say "based on the failures", it's a bit of a tricky line to walk because we don't want to overfit to the specific cases you're seeing. So what I DON'T want you to do is produce an ever-expanding list of specific queries that this skill should or shouldn't trigger for. Instead, try to generalize from the failures to broader categories of user intent and situations where this skill would be useful or not useful. The reason for this is twofold: + +1. Avoid overfitting +2. The list might get loooong and it's injected into ALL queries and there might be a lot of skills, so we don't want to blow too much space on any given description. + +Concretely, your description should not be more than about 100-200 words, even if that comes at the cost of accuracy. There is a hard limit of 1024 characters — descriptions over that will be truncated, so stay comfortably under it. + +Here are some tips that we've found to work well in writing these descriptions: +- The skill should be phrased in the imperative -- "Use this skill for" rather than "this skill does" +- The skill description should focus on the user's intent, what they are trying to achieve, vs. the implementation details of how the skill works. +- The description competes with other skills for Claude's attention — make it distinctive and immediately recognizable. +- If you're getting lots of failures after repeated attempts, change things up. Try different sentence structures or wordings. + +I'd encourage you to be creative and mix up the style in different iterations since you'll have multiple opportunities to try different approaches and we'll just grab the highest-scoring one at the end. + +Please respond with only the new description text in tags, nothing else.""" + + text = _call_claude(prompt, model) + + match = re.search(r"(.*?)", text, re.DOTALL) + description = match.group(1).strip().strip('"') if match else text.strip().strip('"') + + transcript: dict = { + "iteration": iteration, + "prompt": prompt, + "response": text, + "parsed_description": description, + "char_count": len(description), + "over_limit": len(description) > 1024, + } + + # Safety net: the prompt already states the 1024-char hard limit, but if + # the model blew past it anyway, make one fresh single-turn call that + # quotes the too-long version and asks for a shorter rewrite. (The old + # SDK path did this as a true multi-turn; `claude -p` is one-shot, so we + # inline the prior output into the new prompt instead.) + if len(description) > 1024: + shorten_prompt = ( + f"{prompt}\n\n" + f"---\n\n" + f"A previous attempt produced this description, which at " + f"{len(description)} characters is over the 1024-character hard limit:\n\n" + f'"{description}"\n\n' + f"Rewrite it to be under 1024 characters while keeping the most " + f"important trigger words and intent coverage. Respond with only " + f"the new description in tags." + ) + shorten_text = _call_claude(shorten_prompt, model) + match = re.search(r"(.*?)", shorten_text, re.DOTALL) + shortened = match.group(1).strip().strip('"') if match else shorten_text.strip().strip('"') + + transcript["rewrite_prompt"] = shorten_prompt + transcript["rewrite_response"] = shorten_text + transcript["rewrite_description"] = shortened + transcript["rewrite_char_count"] = len(shortened) + description = shortened + + transcript["final_description"] = description + + if log_dir: + log_dir.mkdir(parents=True, exist_ok=True) + log_file = log_dir / f"improve_iter_{iteration or 'unknown'}.json" + log_file.write_text(json.dumps(transcript, indent=2)) + + return description + + +def main(): + parser = argparse.ArgumentParser(description="Improve a skill description based on eval results") + parser.add_argument("--eval-results", required=True, help="Path to eval results JSON (from run_eval.py)") + parser.add_argument("--skill-path", required=True, help="Path to skill directory") + parser.add_argument("--history", default=None, help="Path to history JSON (previous attempts)") + parser.add_argument("--model", required=True, help="Model for improvement") + parser.add_argument("--verbose", action="store_true", help="Print thinking to stderr") + args = parser.parse_args() + + skill_path = Path(args.skill_path) + if not (skill_path / "SKILL.md").exists(): + print(f"Error: No SKILL.md found at {skill_path}", file=sys.stderr) + sys.exit(1) + + eval_results = json.loads(Path(args.eval_results).read_text()) + history = [] + if args.history: + history = json.loads(Path(args.history).read_text()) + + name, _, content = parse_skill_md(skill_path) + current_description = eval_results["description"] + + if args.verbose: + print(f"Current: {current_description}", file=sys.stderr) + print(f"Score: {eval_results['summary']['passed']}/{eval_results['summary']['total']}", file=sys.stderr) + + new_description = improve_description( + skill_name=name, + skill_content=content, + current_description=current_description, + eval_results=eval_results, + history=history, + model=args.model, + ) + + if args.verbose: + print(f"Improved: {new_description}", file=sys.stderr) + + # Output as JSON with both the new description and updated history + output = { + "description": new_description, + "history": history + [{ + "description": current_description, + "passed": eval_results["summary"]["passed"], + "failed": eval_results["summary"]["failed"], + "total": eval_results["summary"]["total"], + "results": eval_results["results"], + }], + } + print(json.dumps(output, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/init_skill.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/init_skill.py new file mode 100644 index 00000000..329ad4e5 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/init_skill.py @@ -0,0 +1,303 @@ +#!/usr/bin/env python3 +""" +Skill Initializer - Creates a new skill from template + +Usage: + init_skill.py --path + +Examples: + init_skill.py my-new-skill --path skills/public + init_skill.py my-api-helper --path skills/private + init_skill.py custom-skill --path /custom/location +""" + +import sys +from pathlib import Path + + +SKILL_TEMPLATE = """--- +name: {skill_name} +description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.] +--- + +# {skill_title} + +## Overview + +[TODO: 1-2 sentences explaining what this skill enables] + +## Structuring This Skill + +[TODO: Choose the structure that best fits this skill's purpose. Common patterns: + +**1. Workflow-Based** (best for sequential processes) +- Works well when there are clear step-by-step procedures +- Example: DOCX skill with "Workflow Decision Tree" → "Reading" → "Creating" → "Editing" +- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2... + +**2. Task-Based** (best for tool collections) +- Works well when the skill offers different operations/capabilities +- Example: PDF skill with "Quick Start" → "Merge PDFs" → "Split PDFs" → "Extract Text" +- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2... + +**3. Reference/Guidelines** (best for standards or specifications) +- Works well for brand guidelines, coding standards, or requirements +- Example: Brand styling with "Brand Guidelines" → "Colors" → "Typography" → "Features" +- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage... + +**4. Capabilities-Based** (best for integrated systems) +- Works well when the skill provides multiple interrelated features +- Example: Product Management with "Core Capabilities" → numbered capability list +- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature... + +Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations). + +Delete this entire "Structuring This Skill" section when done - it's just guidance.] + +## [TODO: Replace with the first main section based on chosen structure] + +[TODO: Add content here. See examples in existing skills: +- Code samples for technical skills +- Decision trees for complex workflows +- Concrete examples with realistic user requests +- References to scripts/templates/references as needed] + +## Resources + +This skill includes example resource directories that demonstrate how to organize different types of bundled resources: + +### scripts/ +Executable code (Python/Bash/etc.) that can be run directly to perform specific operations. + +**Examples from other skills:** +- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation +- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing + +**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations. + +**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments. + +### references/ +Documentation and reference material intended to be loaded into context to inform Claude's process and thinking. + +**Examples from other skills:** +- Product management: `communication.md`, `context_building.md` - detailed workflow guides +- BigQuery: API reference documentation and query examples +- Finance: Schema documentation, company policies + +**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working. + +### assets/ +Files not intended to be loaded into context, but rather used within the output Claude produces. + +**Examples from other skills:** +- Brand styling: PowerPoint template files (.pptx), logo files +- Frontend builder: HTML/React boilerplate project directories +- Typography: Font files (.ttf, .woff2) + +**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output. + +--- + +**Any unneeded directories can be deleted.** Not every skill requires all three types of resources. +""" + +EXAMPLE_SCRIPT = '''#!/usr/bin/env python3 +""" +Example helper script for {skill_name} + +This is a placeholder script that can be executed directly. +Replace with actual implementation or delete if not needed. + +Example real scripts from other skills: +- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields +- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images +""" + +def main(): + print("This is an example script for {skill_name}") + # TODO: Add actual script logic here + # This could be data processing, file conversion, API calls, etc. + +if __name__ == "__main__": + main() +''' + +EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title} + +This is a placeholder for detailed reference documentation. +Replace with actual reference content or delete if not needed. + +Example real reference docs from other skills: +- product-management/references/communication.md - Comprehensive guide for status updates +- product-management/references/context_building.md - Deep-dive on gathering context +- bigquery/references/ - API references and query examples + +## When Reference Docs Are Useful + +Reference docs are ideal for: +- Comprehensive API documentation +- Detailed workflow guides +- Complex multi-step processes +- Information too lengthy for main SKILL.md +- Content that's only needed for specific use cases + +## Structure Suggestions + +### API Reference Example +- Overview +- Authentication +- Endpoints with examples +- Error codes +- Rate limits + +### Workflow Guide Example +- Prerequisites +- Step-by-step instructions +- Common patterns +- Troubleshooting +- Best practices +""" + +EXAMPLE_ASSET = """# Example Asset File + +This placeholder represents where asset files would be stored. +Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed. + +Asset files are NOT intended to be loaded into context, but rather used within +the output Claude produces. + +Example asset files from other skills: +- Brand guidelines: logo.png, slides_template.pptx +- Frontend builder: hello-world/ directory with HTML/React boilerplate +- Typography: custom-font.ttf, font-family.woff2 +- Data: sample_data.csv, test_dataset.json + +## Common Asset Types + +- Templates: .pptx, .docx, boilerplate directories +- Images: .png, .jpg, .svg, .gif +- Fonts: .ttf, .otf, .woff, .woff2 +- Boilerplate code: Project directories, starter files +- Icons: .ico, .svg +- Data files: .csv, .json, .xml, .yaml + +Note: This is a text placeholder. Actual assets can be any file type. +""" + + +def title_case_skill_name(skill_name): + """Convert hyphenated skill name to Title Case for display.""" + return ' '.join(word.capitalize() for word in skill_name.split('-')) + + +def init_skill(skill_name, path): + """ + Initialize a new skill directory with template SKILL.md. + + Args: + skill_name: Name of the skill + path: Path where the skill directory should be created + + Returns: + Path to created skill directory, or None if error + """ + # Determine skill directory path + skill_dir = Path(path).resolve() / skill_name + + # Check if directory already exists + if skill_dir.exists(): + print(f"❌ Error: Skill directory already exists: {skill_dir}") + return None + + # Create skill directory + try: + skill_dir.mkdir(parents=True, exist_ok=False) + print(f"✅ Created skill directory: {skill_dir}") + except Exception as e: + print(f"❌ Error creating directory: {e}") + return None + + # Create SKILL.md from template + skill_title = title_case_skill_name(skill_name) + skill_content = SKILL_TEMPLATE.format( + skill_name=skill_name, + skill_title=skill_title + ) + + skill_md_path = skill_dir / 'SKILL.md' + try: + skill_md_path.write_text(skill_content) + print("✅ Created SKILL.md") + except Exception as e: + print(f"❌ Error creating SKILL.md: {e}") + return None + + # Create resource directories with example files + try: + # Create scripts/ directory with example script + scripts_dir = skill_dir / 'scripts' + scripts_dir.mkdir(exist_ok=True) + example_script = scripts_dir / 'example.py' + example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name)) + example_script.chmod(0o755) + print("✅ Created scripts/example.py") + + # Create references/ directory with example reference doc + references_dir = skill_dir / 'references' + references_dir.mkdir(exist_ok=True) + example_reference = references_dir / 'api_reference.md' + example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title)) + print("✅ Created references/api_reference.md") + + # Create assets/ directory with example asset placeholder + assets_dir = skill_dir / 'assets' + assets_dir.mkdir(exist_ok=True) + example_asset = assets_dir / 'example_asset.txt' + example_asset.write_text(EXAMPLE_ASSET) + print("✅ Created assets/example_asset.txt") + except Exception as e: + print(f"❌ Error creating resource directories: {e}") + return None + + # Print next steps + print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}") + print("\nNext steps:") + print("1. Edit SKILL.md to complete the TODO items and update the description") + print("2. Customize or delete the example files in scripts/, references/, and assets/") + print("3. Run the validator when ready to check the skill structure") + + return skill_dir + + +def main(): + if len(sys.argv) < 4 or sys.argv[2] != '--path': + print("Usage: init_skill.py --path ") + print("\nSkill name requirements:") + print(" - Hyphen-case identifier (e.g., 'data-analyzer')") + print(" - Lowercase letters, digits, and hyphens only") + print(" - Max 40 characters") + print(" - Must match directory name exactly") + print("\nExamples:") + print(" init_skill.py my-new-skill --path skills/public") + print(" init_skill.py my-api-helper --path skills/private") + print(" init_skill.py custom-skill --path /custom/location") + sys.exit(1) + + skill_name = sys.argv[1] + path = sys.argv[3] + + print(f"🚀 Initializing skill: {skill_name}") + print(f" Location: {path}") + print() + + result = init_skill(skill_name, path) + + if result: + sys.exit(0) + else: + sys.exit(1) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/package_skill.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/package_skill.py new file mode 100644 index 00000000..f48eac44 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/package_skill.py @@ -0,0 +1,136 @@ +#!/usr/bin/env python3 +""" +Skill Packager - Creates a distributable .skill file of a skill folder + +Usage: + python utils/package_skill.py [output-directory] + +Example: + python utils/package_skill.py skills/public/my-skill + python utils/package_skill.py skills/public/my-skill ./dist +""" + +import fnmatch +import sys +import zipfile +from pathlib import Path +from scripts.quick_validate import validate_skill + +# Patterns to exclude when packaging skills. +EXCLUDE_DIRS = {"__pycache__", "node_modules"} +EXCLUDE_GLOBS = {"*.pyc"} +EXCLUDE_FILES = {".DS_Store"} +# Directories excluded only at the skill root (not when nested deeper). +ROOT_EXCLUDE_DIRS = {"evals"} + + +def should_exclude(rel_path: Path) -> bool: + """Check if a path should be excluded from packaging.""" + parts = rel_path.parts + if any(part in EXCLUDE_DIRS for part in parts): + return True + # rel_path is relative to skill_path.parent, so parts[0] is the skill + # folder name and parts[1] (if present) is the first subdir. + if len(parts) > 1 and parts[1] in ROOT_EXCLUDE_DIRS: + return True + name = rel_path.name + if name in EXCLUDE_FILES: + return True + return any(fnmatch.fnmatch(name, pat) for pat in EXCLUDE_GLOBS) + + +def package_skill(skill_path, output_dir=None): + """ + Package a skill folder into a .skill file. + + Args: + skill_path: Path to the skill folder + output_dir: Optional output directory for the .skill file (defaults to current directory) + + Returns: + Path to the created .skill file, or None if error + """ + skill_path = Path(skill_path).resolve() + + # Validate skill folder exists + if not skill_path.exists(): + print(f"❌ Error: Skill folder not found: {skill_path}") + return None + + if not skill_path.is_dir(): + print(f"❌ Error: Path is not a directory: {skill_path}") + return None + + # Validate SKILL.md exists + skill_md = skill_path / "SKILL.md" + if not skill_md.exists(): + print(f"❌ Error: SKILL.md not found in {skill_path}") + return None + + # Run validation before packaging + print("🔍 Validating skill...") + valid, message = validate_skill(skill_path) + if not valid: + print(f"❌ Validation failed: {message}") + print(" Please fix the validation errors before packaging.") + return None + print(f"✅ {message}\n") + + # Determine output location + skill_name = skill_path.name + if output_dir: + output_path = Path(output_dir).resolve() + output_path.mkdir(parents=True, exist_ok=True) + else: + output_path = Path.cwd() + + skill_filename = output_path / f"{skill_name}.skill" + + # Create the .skill file (zip format) + try: + with zipfile.ZipFile(skill_filename, 'w', zipfile.ZIP_DEFLATED) as zipf: + # Walk through the skill directory, excluding build artifacts + for file_path in skill_path.rglob('*'): + if not file_path.is_file(): + continue + arcname = file_path.relative_to(skill_path.parent) + if should_exclude(arcname): + print(f" Skipped: {arcname}") + continue + zipf.write(file_path, arcname) + print(f" Added: {arcname}") + + print(f"\n✅ Successfully packaged skill to: {skill_filename}") + return skill_filename + + except Exception as e: + print(f"❌ Error creating .skill file: {e}") + return None + + +def main(): + if len(sys.argv) < 2: + print("Usage: python utils/package_skill.py [output-directory]") + print("\nExample:") + print(" python utils/package_skill.py skills/public/my-skill") + print(" python utils/package_skill.py skills/public/my-skill ./dist") + sys.exit(1) + + skill_path = sys.argv[1] + output_dir = sys.argv[2] if len(sys.argv) > 2 else None + + print(f"📦 Packaging skill: {skill_path}") + if output_dir: + print(f" Output directory: {output_dir}") + print() + + result = package_skill(skill_path, output_dir) + + if result: + sys.exit(0) + else: + sys.exit(1) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/quick_validate.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/quick_validate.py new file mode 100644 index 00000000..54f682ce --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/quick_validate.py @@ -0,0 +1,103 @@ +#!/usr/bin/env python3 +""" +Quick validation script for skills - minimal version +""" + +import sys +import os +import re +import yaml +from pathlib import Path + +def validate_skill(skill_path): + """Basic validation of a skill""" + skill_path = Path(skill_path) + + # Check SKILL.md exists + skill_md = skill_path / 'SKILL.md' + if not skill_md.exists(): + return False, "SKILL.md not found" + + # Read and validate frontmatter + content = skill_md.read_text() + if not content.startswith('---'): + return False, "No YAML frontmatter found" + + # Extract frontmatter + match = re.match(r'^---\n(.*?)\n---', content, re.DOTALL) + if not match: + return False, "Invalid frontmatter format" + + frontmatter_text = match.group(1) + + # Parse YAML frontmatter + try: + frontmatter = yaml.safe_load(frontmatter_text) + if not isinstance(frontmatter, dict): + return False, "Frontmatter must be a YAML dictionary" + except yaml.YAMLError as e: + return False, f"Invalid YAML in frontmatter: {e}" + + # Define allowed properties + ALLOWED_PROPERTIES = {'name', 'description', 'license', 'allowed-tools', 'metadata', 'compatibility'} + + # Check for unexpected properties (excluding nested keys under metadata) + unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES + if unexpected_keys: + return False, ( + f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. " + f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}" + ) + + # Check required fields + if 'name' not in frontmatter: + return False, "Missing 'name' in frontmatter" + if 'description' not in frontmatter: + return False, "Missing 'description' in frontmatter" + + # Extract name for validation + name = frontmatter.get('name', '') + if not isinstance(name, str): + return False, f"Name must be a string, got {type(name).__name__}" + name = name.strip() + if name: + # Check naming convention (kebab-case: lowercase with hyphens) + if not re.match(r'^[a-z0-9-]+$', name): + return False, f"Name '{name}' should be kebab-case (lowercase letters, digits, and hyphens only)" + if name.startswith('-') or name.endswith('-') or '--' in name: + return False, f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens" + # Check name length (max 64 characters per spec) + if len(name) > 64: + return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters." + + # Extract and validate description + description = frontmatter.get('description', '') + if not isinstance(description, str): + return False, f"Description must be a string, got {type(description).__name__}" + description = description.strip() + if description: + # Check for angle brackets + if '<' in description or '>' in description: + return False, "Description cannot contain angle brackets (< or >)" + # Check description length (max 1024 characters per spec) + if len(description) > 1024: + return False, f"Description is too long ({len(description)} characters). Maximum is 1024 characters." + + # Validate compatibility field if present (optional) + compatibility = frontmatter.get('compatibility', '') + if compatibility: + if not isinstance(compatibility, str): + return False, f"Compatibility must be a string, got {type(compatibility).__name__}" + if len(compatibility) > 500: + return False, f"Compatibility is too long ({len(compatibility)} characters). Maximum is 500 characters." + + return True, "Skill is valid!" + +if __name__ == "__main__": + if len(sys.argv) != 2: + print("Usage: python quick_validate.py ") + sys.exit(1) + + valid, message = validate_skill(sys.argv[1]) + print(message) + sys.exit(0 if valid else 1) diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/run_eval.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/run_eval.py new file mode 100644 index 00000000..e58c70be --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/run_eval.py @@ -0,0 +1,310 @@ +#!/usr/bin/env python3 +"""Run trigger evaluation for a skill description. + +Tests whether a skill's description causes Claude to trigger (read the skill) +for a set of queries. Outputs results as JSON. +""" + +import argparse +import json +import os +import select +import subprocess +import sys +import time +import uuid +from concurrent.futures import ProcessPoolExecutor, as_completed +from pathlib import Path + +from scripts.utils import parse_skill_md + + +def find_project_root() -> Path: + """Find the project root by walking up from cwd looking for .claude/. + + Mimics how Claude Code discovers its project root, so the command file + we create ends up where claude -p will look for it. + """ + current = Path.cwd() + for parent in [current, *current.parents]: + if (parent / ".claude").is_dir(): + return parent + return current + + +def run_single_query( + query: str, + skill_name: str, + skill_description: str, + timeout: int, + project_root: str, + model: str | None = None, +) -> bool: + """Run a single query and return whether the skill was triggered. + + Creates a command file in .claude/commands/ so it appears in Claude's + available_skills list, then runs `claude -p` with the raw query. + Uses --include-partial-messages to detect triggering early from + stream events (content_block_start) rather than waiting for the + full assistant message, which only arrives after tool execution. + """ + unique_id = uuid.uuid4().hex[:8] + clean_name = f"{skill_name}-skill-{unique_id}" + project_commands_dir = Path(project_root) / ".claude" / "commands" + command_file = project_commands_dir / f"{clean_name}.md" + + try: + project_commands_dir.mkdir(parents=True, exist_ok=True) + # Use YAML block scalar to avoid breaking on quotes in description + indented_desc = "\n ".join(skill_description.split("\n")) + command_content = ( + f"---\n" + f"description: |\n" + f" {indented_desc}\n" + f"---\n\n" + f"# {skill_name}\n\n" + f"This skill handles: {skill_description}\n" + ) + command_file.write_text(command_content) + + cmd = [ + "claude", + "-p", query, + "--output-format", "stream-json", + "--verbose", + "--include-partial-messages", + ] + if model: + cmd.extend(["--model", model]) + + # Remove CLAUDECODE env var to allow nesting claude -p inside a + # Claude Code session. The guard is for interactive terminal conflicts; + # programmatic subprocess usage is safe. + env = {k: v for k, v in os.environ.items() if k != "CLAUDECODE"} + + process = subprocess.Popen( + cmd, + stdout=subprocess.PIPE, + stderr=subprocess.DEVNULL, + cwd=project_root, + env=env, + ) + + triggered = False + start_time = time.time() + buffer = "" + # Track state for stream event detection + pending_tool_name = None + accumulated_json = "" + + try: + while time.time() - start_time < timeout: + if process.poll() is not None: + remaining = process.stdout.read() + if remaining: + buffer += remaining.decode("utf-8", errors="replace") + break + + ready, _, _ = select.select([process.stdout], [], [], 1.0) + if not ready: + continue + + chunk = os.read(process.stdout.fileno(), 8192) + if not chunk: + break + buffer += chunk.decode("utf-8", errors="replace") + + while "\n" in buffer: + line, buffer = buffer.split("\n", 1) + line = line.strip() + if not line: + continue + + try: + event = json.loads(line) + except json.JSONDecodeError: + continue + + # Early detection via stream events + if event.get("type") == "stream_event": + se = event.get("event", {}) + se_type = se.get("type", "") + + if se_type == "content_block_start": + cb = se.get("content_block", {}) + if cb.get("type") == "tool_use": + tool_name = cb.get("name", "") + if tool_name in ("Skill", "Read"): + pending_tool_name = tool_name + accumulated_json = "" + else: + return False + + elif se_type == "content_block_delta" and pending_tool_name: + delta = se.get("delta", {}) + if delta.get("type") == "input_json_delta": + accumulated_json += delta.get("partial_json", "") + if clean_name in accumulated_json: + return True + + elif se_type in ("content_block_stop", "message_stop"): + if pending_tool_name: + return clean_name in accumulated_json + if se_type == "message_stop": + return False + + # Fallback: full assistant message + elif event.get("type") == "assistant": + message = event.get("message", {}) + for content_item in message.get("content", []): + if content_item.get("type") != "tool_use": + continue + tool_name = content_item.get("name", "") + tool_input = content_item.get("input", {}) + if tool_name == "Skill" and clean_name in tool_input.get("skill", ""): + triggered = True + elif tool_name == "Read" and clean_name in tool_input.get("file_path", ""): + triggered = True + return triggered + + elif event.get("type") == "result": + return triggered + finally: + # Clean up process on any exit path (return, exception, timeout) + if process.poll() is None: + process.kill() + process.wait() + + return triggered + finally: + if command_file.exists(): + command_file.unlink() + + +def run_eval( + eval_set: list[dict], + skill_name: str, + description: str, + num_workers: int, + timeout: int, + project_root: Path, + runs_per_query: int = 1, + trigger_threshold: float = 0.5, + model: str | None = None, +) -> dict: + """Run the full eval set and return results.""" + results = [] + + with ProcessPoolExecutor(max_workers=num_workers) as executor: + future_to_info = {} + for item in eval_set: + for run_idx in range(runs_per_query): + future = executor.submit( + run_single_query, + item["query"], + skill_name, + description, + timeout, + str(project_root), + model, + ) + future_to_info[future] = (item, run_idx) + + query_triggers: dict[str, list[bool]] = {} + query_items: dict[str, dict] = {} + for future in as_completed(future_to_info): + item, _ = future_to_info[future] + query = item["query"] + query_items[query] = item + if query not in query_triggers: + query_triggers[query] = [] + try: + query_triggers[query].append(future.result()) + except Exception as e: + print(f"Warning: query failed: {e}", file=sys.stderr) + query_triggers[query].append(False) + + for query, triggers in query_triggers.items(): + item = query_items[query] + trigger_rate = sum(triggers) / len(triggers) + should_trigger = item["should_trigger"] + if should_trigger: + did_pass = trigger_rate >= trigger_threshold + else: + did_pass = trigger_rate < trigger_threshold + results.append({ + "query": query, + "should_trigger": should_trigger, + "trigger_rate": trigger_rate, + "triggers": sum(triggers), + "runs": len(triggers), + "pass": did_pass, + }) + + passed = sum(1 for r in results if r["pass"]) + total = len(results) + + return { + "skill_name": skill_name, + "description": description, + "results": results, + "summary": { + "total": total, + "passed": passed, + "failed": total - passed, + }, + } + + +def main(): + parser = argparse.ArgumentParser(description="Run trigger evaluation for a skill description") + parser.add_argument("--eval-set", required=True, help="Path to eval set JSON file") + parser.add_argument("--skill-path", required=True, help="Path to skill directory") + parser.add_argument("--description", default=None, help="Override description to test") + parser.add_argument("--num-workers", type=int, default=10, help="Number of parallel workers") + parser.add_argument("--timeout", type=int, default=30, help="Timeout per query in seconds") + parser.add_argument("--runs-per-query", type=int, default=3, help="Number of runs per query") + parser.add_argument("--trigger-threshold", type=float, default=0.5, help="Trigger rate threshold") + parser.add_argument("--model", default=None, help="Model to use for claude -p (default: user's configured model)") + parser.add_argument("--verbose", action="store_true", help="Print progress to stderr") + args = parser.parse_args() + + eval_set = json.loads(Path(args.eval_set).read_text()) + skill_path = Path(args.skill_path) + + if not (skill_path / "SKILL.md").exists(): + print(f"Error: No SKILL.md found at {skill_path}", file=sys.stderr) + sys.exit(1) + + name, original_description, content = parse_skill_md(skill_path) + description = args.description or original_description + project_root = find_project_root() + + if args.verbose: + print(f"Evaluating: {description}", file=sys.stderr) + + output = run_eval( + eval_set=eval_set, + skill_name=name, + description=description, + num_workers=args.num_workers, + timeout=args.timeout, + project_root=project_root, + runs_per_query=args.runs_per_query, + trigger_threshold=args.trigger_threshold, + model=args.model, + ) + + if args.verbose: + summary = output["summary"] + print(f"Results: {summary['passed']}/{summary['total']} passed", file=sys.stderr) + for r in output["results"]: + status = "PASS" if r["pass"] else "FAIL" + rate_str = f"{r['triggers']}/{r['runs']}" + print(f" [{status}] rate={rate_str} expected={r['should_trigger']}: {r['query'][:70]}", file=sys.stderr) + + print(json.dumps(output, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/run_loop.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/run_loop.py new file mode 100644 index 00000000..30a263d6 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/run_loop.py @@ -0,0 +1,328 @@ +#!/usr/bin/env python3 +"""Run the eval + improve loop until all pass or max iterations reached. + +Combines run_eval.py and improve_description.py in a loop, tracking history +and returning the best description found. Supports train/test split to prevent +overfitting. +""" + +import argparse +import json +import random +import sys +import tempfile +import time +import webbrowser +from pathlib import Path + +from scripts.generate_report import generate_html +from scripts.improve_description import improve_description +from scripts.run_eval import find_project_root, run_eval +from scripts.utils import parse_skill_md + + +def split_eval_set(eval_set: list[dict], holdout: float, seed: int = 42) -> tuple[list[dict], list[dict]]: + """Split eval set into train and test sets, stratified by should_trigger.""" + random.seed(seed) + + # Separate by should_trigger + trigger = [e for e in eval_set if e["should_trigger"]] + no_trigger = [e for e in eval_set if not e["should_trigger"]] + + # Shuffle each group + random.shuffle(trigger) + random.shuffle(no_trigger) + + # Calculate split points + n_trigger_test = max(1, int(len(trigger) * holdout)) + n_no_trigger_test = max(1, int(len(no_trigger) * holdout)) + + # Split + test_set = trigger[:n_trigger_test] + no_trigger[:n_no_trigger_test] + train_set = trigger[n_trigger_test:] + no_trigger[n_no_trigger_test:] + + return train_set, test_set + + +def run_loop( + eval_set: list[dict], + skill_path: Path, + description_override: str | None, + num_workers: int, + timeout: int, + max_iterations: int, + runs_per_query: int, + trigger_threshold: float, + holdout: float, + model: str, + verbose: bool, + live_report_path: Path | None = None, + log_dir: Path | None = None, +) -> dict: + """Run the eval + improvement loop.""" + project_root = find_project_root() + name, original_description, content = parse_skill_md(skill_path) + current_description = description_override or original_description + + # Split into train/test if holdout > 0 + if holdout > 0: + train_set, test_set = split_eval_set(eval_set, holdout) + if verbose: + print(f"Split: {len(train_set)} train, {len(test_set)} test (holdout={holdout})", file=sys.stderr) + else: + train_set = eval_set + test_set = [] + + history = [] + exit_reason = "unknown" + + for iteration in range(1, max_iterations + 1): + if verbose: + print(f"\n{'='*60}", file=sys.stderr) + print(f"Iteration {iteration}/{max_iterations}", file=sys.stderr) + print(f"Description: {current_description}", file=sys.stderr) + print(f"{'='*60}", file=sys.stderr) + + # Evaluate train + test together in one batch for parallelism + all_queries = train_set + test_set + t0 = time.time() + all_results = run_eval( + eval_set=all_queries, + skill_name=name, + description=current_description, + num_workers=num_workers, + timeout=timeout, + project_root=project_root, + runs_per_query=runs_per_query, + trigger_threshold=trigger_threshold, + model=model, + ) + eval_elapsed = time.time() - t0 + + # Split results back into train/test by matching queries + train_queries_set = {q["query"] for q in train_set} + train_result_list = [r for r in all_results["results"] if r["query"] in train_queries_set] + test_result_list = [r for r in all_results["results"] if r["query"] not in train_queries_set] + + train_passed = sum(1 for r in train_result_list if r["pass"]) + train_total = len(train_result_list) + train_summary = {"passed": train_passed, "failed": train_total - train_passed, "total": train_total} + train_results = {"results": train_result_list, "summary": train_summary} + + if test_set: + test_passed = sum(1 for r in test_result_list if r["pass"]) + test_total = len(test_result_list) + test_summary = {"passed": test_passed, "failed": test_total - test_passed, "total": test_total} + test_results = {"results": test_result_list, "summary": test_summary} + else: + test_results = None + test_summary = None + + history.append({ + "iteration": iteration, + "description": current_description, + "train_passed": train_summary["passed"], + "train_failed": train_summary["failed"], + "train_total": train_summary["total"], + "train_results": train_results["results"], + "test_passed": test_summary["passed"] if test_summary else None, + "test_failed": test_summary["failed"] if test_summary else None, + "test_total": test_summary["total"] if test_summary else None, + "test_results": test_results["results"] if test_results else None, + # For backward compat with report generator + "passed": train_summary["passed"], + "failed": train_summary["failed"], + "total": train_summary["total"], + "results": train_results["results"], + }) + + # Write live report if path provided + if live_report_path: + partial_output = { + "original_description": original_description, + "best_description": current_description, + "best_score": "in progress", + "iterations_run": len(history), + "holdout": holdout, + "train_size": len(train_set), + "test_size": len(test_set), + "history": history, + } + live_report_path.write_text(generate_html(partial_output, auto_refresh=True, skill_name=name)) + + if verbose: + def print_eval_stats(label, results, elapsed): + pos = [r for r in results if r["should_trigger"]] + neg = [r for r in results if not r["should_trigger"]] + tp = sum(r["triggers"] for r in pos) + pos_runs = sum(r["runs"] for r in pos) + fn = pos_runs - tp + fp = sum(r["triggers"] for r in neg) + neg_runs = sum(r["runs"] for r in neg) + tn = neg_runs - fp + total = tp + tn + fp + fn + precision = tp / (tp + fp) if (tp + fp) > 0 else 1.0 + recall = tp / (tp + fn) if (tp + fn) > 0 else 1.0 + accuracy = (tp + tn) / total if total > 0 else 0.0 + print(f"{label}: {tp+tn}/{total} correct, precision={precision:.0%} recall={recall:.0%} accuracy={accuracy:.0%} ({elapsed:.1f}s)", file=sys.stderr) + for r in results: + status = "PASS" if r["pass"] else "FAIL" + rate_str = f"{r['triggers']}/{r['runs']}" + print(f" [{status}] rate={rate_str} expected={r['should_trigger']}: {r['query'][:60]}", file=sys.stderr) + + print_eval_stats("Train", train_results["results"], eval_elapsed) + if test_summary: + print_eval_stats("Test ", test_results["results"], 0) + + if train_summary["failed"] == 0: + exit_reason = f"all_passed (iteration {iteration})" + if verbose: + print(f"\nAll train queries passed on iteration {iteration}!", file=sys.stderr) + break + + if iteration == max_iterations: + exit_reason = f"max_iterations ({max_iterations})" + if verbose: + print(f"\nMax iterations reached ({max_iterations}).", file=sys.stderr) + break + + # Improve the description based on train results + if verbose: + print(f"\nImproving description...", file=sys.stderr) + + t0 = time.time() + # Strip test scores from history so improvement model can't see them + blinded_history = [ + {k: v for k, v in h.items() if not k.startswith("test_")} + for h in history + ] + new_description = improve_description( + skill_name=name, + skill_content=content, + current_description=current_description, + eval_results=train_results, + history=blinded_history, + model=model, + log_dir=log_dir, + iteration=iteration, + ) + improve_elapsed = time.time() - t0 + + if verbose: + print(f"Proposed ({improve_elapsed:.1f}s): {new_description}", file=sys.stderr) + + current_description = new_description + + # Find the best iteration by TEST score (or train if no test set) + if test_set: + best = max(history, key=lambda h: h["test_passed"] or 0) + best_score = f"{best['test_passed']}/{best['test_total']}" + else: + best = max(history, key=lambda h: h["train_passed"]) + best_score = f"{best['train_passed']}/{best['train_total']}" + + if verbose: + print(f"\nExit reason: {exit_reason}", file=sys.stderr) + print(f"Best score: {best_score} (iteration {best['iteration']})", file=sys.stderr) + + return { + "exit_reason": exit_reason, + "original_description": original_description, + "best_description": best["description"], + "best_score": best_score, + "best_train_score": f"{best['train_passed']}/{best['train_total']}", + "best_test_score": f"{best['test_passed']}/{best['test_total']}" if test_set else None, + "final_description": current_description, + "iterations_run": len(history), + "holdout": holdout, + "train_size": len(train_set), + "test_size": len(test_set), + "history": history, + } + + +def main(): + parser = argparse.ArgumentParser(description="Run eval + improve loop") + parser.add_argument("--eval-set", required=True, help="Path to eval set JSON file") + parser.add_argument("--skill-path", required=True, help="Path to skill directory") + parser.add_argument("--description", default=None, help="Override starting description") + parser.add_argument("--num-workers", type=int, default=10, help="Number of parallel workers") + parser.add_argument("--timeout", type=int, default=30, help="Timeout per query in seconds") + parser.add_argument("--max-iterations", type=int, default=5, help="Max improvement iterations") + parser.add_argument("--runs-per-query", type=int, default=3, help="Number of runs per query") + parser.add_argument("--trigger-threshold", type=float, default=0.5, help="Trigger rate threshold") + parser.add_argument("--holdout", type=float, default=0.4, help="Fraction of eval set to hold out for testing (0 to disable)") + parser.add_argument("--model", required=True, help="Model for improvement") + parser.add_argument("--verbose", action="store_true", help="Print progress to stderr") + parser.add_argument("--report", default="auto", help="Generate HTML report at this path (default: 'auto' for temp file, 'none' to disable)") + parser.add_argument("--results-dir", default=None, help="Save all outputs (results.json, report.html, log.txt) to a timestamped subdirectory here") + args = parser.parse_args() + + eval_set = json.loads(Path(args.eval_set).read_text()) + skill_path = Path(args.skill_path) + + if not (skill_path / "SKILL.md").exists(): + print(f"Error: No SKILL.md found at {skill_path}", file=sys.stderr) + sys.exit(1) + + name, _, _ = parse_skill_md(skill_path) + + # Set up live report path + if args.report != "none": + if args.report == "auto": + timestamp = time.strftime("%Y%m%d_%H%M%S") + live_report_path = Path(tempfile.gettempdir()) / f"skill_description_report_{skill_path.name}_{timestamp}.html" + else: + live_report_path = Path(args.report) + # Open the report immediately so the user can watch + live_report_path.write_text("

Starting optimization loop...

") + webbrowser.open(str(live_report_path)) + else: + live_report_path = None + + # Determine output directory (create before run_loop so logs can be written) + if args.results_dir: + timestamp = time.strftime("%Y-%m-%d_%H%M%S") + results_dir = Path(args.results_dir) / timestamp + results_dir.mkdir(parents=True, exist_ok=True) + else: + results_dir = None + + log_dir = results_dir / "logs" if results_dir else None + + output = run_loop( + eval_set=eval_set, + skill_path=skill_path, + description_override=args.description, + num_workers=args.num_workers, + timeout=args.timeout, + max_iterations=args.max_iterations, + runs_per_query=args.runs_per_query, + trigger_threshold=args.trigger_threshold, + holdout=args.holdout, + model=args.model, + verbose=args.verbose, + live_report_path=live_report_path, + log_dir=log_dir, + ) + + # Save JSON output + json_output = json.dumps(output, indent=2) + print(json_output) + if results_dir: + (results_dir / "results.json").write_text(json_output) + + # Write final HTML report (without auto-refresh) + if live_report_path: + live_report_path.write_text(generate_html(output, auto_refresh=False, skill_name=name)) + print(f"\nReport: {live_report_path}", file=sys.stderr) + + if results_dir and live_report_path: + (results_dir / "report.html").write_text(generate_html(output, auto_refresh=False, skill_name=name)) + + if results_dir: + print(f"Results saved to: {results_dir}", file=sys.stderr) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/utils.py b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/utils.py new file mode 100644 index 00000000..51b6a07d --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/skill-creator/scripts/utils.py @@ -0,0 +1,47 @@ +"""Shared utilities for skill-creator scripts.""" + +from pathlib import Path + + + +def parse_skill_md(skill_path: Path) -> tuple[str, str, str]: + """Parse a SKILL.md file, returning (name, description, full_content).""" + content = (skill_path / "SKILL.md").read_text() + lines = content.split("\n") + + if lines[0].strip() != "---": + raise ValueError("SKILL.md missing frontmatter (no opening ---)") + + end_idx = None + for i, line in enumerate(lines[1:], start=1): + if line.strip() == "---": + end_idx = i + break + + if end_idx is None: + raise ValueError("SKILL.md missing frontmatter (no closing ---)") + + name = "" + description = "" + frontmatter_lines = lines[1:end_idx] + i = 0 + while i < len(frontmatter_lines): + line = frontmatter_lines[i] + if line.startswith("name:"): + name = line[len("name:"):].strip().strip('"').strip("'") + elif line.startswith("description:"): + value = line[len("description:"):].strip() + # Handle YAML multiline indicators (>, |, >-, |-) + if value in (">", "|", ">-", "|-"): + continuation_lines: list[str] = [] + i += 1 + while i < len(frontmatter_lines) and (frontmatter_lines[i].startswith(" ") or frontmatter_lines[i].startswith("\t")): + continuation_lines.append(frontmatter_lines[i].strip()) + i += 1 + description = " ".join(continuation_lines) + continue + else: + description = value.strip('"').strip("'") + i += 1 + + return name, description, content diff --git a/libs/hexagent_demo/backend/skills/examples/web-design-guidelines/SKILL.md b/libs/hexagent_demo/backend/skills/examples/web-design-guidelines/SKILL.md new file mode 100644 index 00000000..ceae92ab --- /dev/null +++ b/libs/hexagent_demo/backend/skills/examples/web-design-guidelines/SKILL.md @@ -0,0 +1,39 @@ +--- +name: web-design-guidelines +description: Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices". +metadata: + author: vercel + version: "1.0.0" + argument-hint: +--- + +# Web Interface Guidelines + +Review files for compliance with Web Interface Guidelines. + +## How It Works + +1. Fetch the latest guidelines from the source URL below +2. Read the specified files (or prompt user for files/pattern) +3. Check against all rules in the fetched guidelines +4. Output findings in the terse `file:line` format + +## Guidelines Source + +Fetch fresh guidelines before each review: + +``` +https://raw.githubusercontent.com/vercel-labs/web-interface-guidelines/main/command.md +``` + +Use WebFetch to retrieve the latest rules. The fetched content contains all the rules and output format instructions. + +## Usage + +When a user provides a file or pattern argument: +1. Fetch guidelines from the source URL above +2. Read the specified files +3. Apply all rules from the fetched guidelines +4. Output findings using the format specified in the guidelines + +If no files specified, ask the user which files to review. diff --git a/libs/hexagent_demo/backend/skills/public/data-insight-report/SKILL.md b/libs/hexagent_demo/backend/skills/public/data-insight-report/SKILL.md new file mode 100644 index 00000000..156c6e10 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/data-insight-report/SKILL.md @@ -0,0 +1,965 @@ +--- +name: data-insight-report +description: | + Analyze tabular data (Excel, CSV, TSV, etc.) and generate insightful ECharts visualizations embedded in comprehensive data insight reports. + Use when: analyzing spreadsheet data for insights, creating data visualization dashboards, generating interactive chart reports, + building presentation-ready data insight reports, or when user needs to transform tabular data into actionable insights with visualizations. +license: MIT +metadata: + author: Andy Huang + version: "1.3.0" +--- + +# Data Insight Report Generator + +Expert **Data Analyst & Visualization Specialist** that analyzes tabular data (Excel, CSV, TSV, etc.) and generates comprehensive data insight reports with interactive ECharts visualizations and actionable recommendations. + +## When to Use + +- Analyzing Excel/CSV/TSV data for business insights +- Creating data visualization dashboards from spreadsheets +- Generating interactive chart reports for stakeholders +- Exploring and presenting data insights visually +- Building presentation-ready data insight reports with embedded charts +- Transforming raw tabular data into actionable business recommendations + +## Supported Data Formats + +| Format | Extensions | Description | +|--------|------------|-------------| +| Excel | `.xlsx`, `.xlsm`, `.xls` | Microsoft Excel workbooks | +| CSV | `.csv` | Comma-separated values | +| TSV | `.tsv`, `.tab` | Tab-separated values | +| Other | `.ods` | OpenDocument Spreadsheet | + +--- + +## Capability Assessment - Access to Dedicated Documents + +Based on the decomposed requirements, explicitly determine whether it is necessary to read the following specialized capability documents: + +| Capability | When to Read | Document Path | +|------------|--------------|---------------| +| **data-analysis** | When performing ANY data analysis: SQL queries, pandas operations, statistics, data cleaning, transformations, pivot tables, time series, or data exploration | **Must** read `abilities/data-analysis.md` | +| **echarts-validation** | When validating ECharts chart configurations after generation, fixing chart errors, or understanding validation rules | **Must** read `abilities/echarts-validation.md` | + +### Decision Flow + +``` +User Request + │ + ├─► Need to load/inspect data files? ──► Read abilities/data-analysis.md + │ + ├─► Need SQL queries or pandas analysis? ──► Read abilities/data-analysis.md + │ + ├─► Need statistical summaries or correlations? ──► Read abilities/data-analysis.md + │ + ├─► Need data cleaning or transformations? ──► Read abilities/data-analysis.md + │ + ├─► Need to validate chart config? ──► Read abilities/echarts-validation.md + │ + └─► Only need chart templates/report format? ──► Continue with current document +``` + +--- + +## Directory Structure + +``` +data-insight-report/ +├── SKILL.md # Main skill document (this file) +├── abilities/ +│ ├── data-analysis.md # Data analysis capability (SQL + pandas + statistics) +│ └── echarts-validation.md # ECharts validation capability +└── scripts/ + ├── analyze.py # SQL-based data analysis script (DuckDB) + └── validate_echarts.py # ECharts configuration validator +``` + +--- + +## Core Capabilities + +### 1. Data Analysis (via data-analysis ability) + +**Two complementary analysis methods:** + +#### SQL Analysis (Script-Based) +- Quick data inspection via `scripts/analyze.py` +- Schema inspection, data profiling, statistical summaries +- Complex queries with JOINs, CTEs, window functions +- Export to CSV/JSON/Markdown + +#### pandas Analysis (Code-Based) +- Flexible, programmatic data manipulation +- Advanced data cleaning and transformations +- Time series analysis +- Statistical analysis (correlations, hypothesis testing, trends) +- Custom data processing pipelines + +**When to use which:** + +| Use SQL Script when... | Use pandas when... | +|----------------------|-------------------| +| Quick data inspection | Complex transformations | +| Simple aggregations | Custom statistical analysis | +| Large datasets (>100MB) | Iterative exploration | +| One-time queries | Chained operations | +| Direct file export | Conditional logic | + +**To use this capability, read `abilities/data-analysis.md` for detailed instructions.** + +### 2. ECharts Validation (via echarts-validation ability) + +- Automated JSON syntax validation +- ECharts structure validation (required fields, chart types) +- Data integrity validation (length matching, NaN/Infinity detection) +- Layout validation (best practices, performance warnings) + +**To use this capability, read `abilities/echarts-validation.md` for detailed instructions.** + +### 3. ECharts Visualization Generation + +Generate interactive charts using `skills(echart)` embedded directly in Markdown. + +**Chart Quantity Limitation:** +- **CRITICAL**: Generate **4-7 charts maximum** per report +- Focus on the most relevant, high-impact visualizations that directly address the user's question +- Avoid creating tangentially related charts that drift from the core analysis purpose +- Quality over quantity: each chart must provide clear, actionable insight + +**Supported Chart Types:** +- **Line**: Trend analysis, time-series, multi-series comparison +- **Bar**: Categorical ranking, grouped/stacked comparisons +- **Scatter**: Correlation analysis, bubble charts, distribution patterns +- **Pie/Donut**: Composition, market share, proportional breakdown +- **Heatmap**: Correlation matrices, density patterns +- **Radar**: Multi-dimensional performance profiles +- **Funnel**: Conversion rates, process flow +- **Treemap**: Hierarchical part-to-whole relationships +- **Gauge**: KPI indicators, single metrics +- **Box Plot**: Statistical distributions, outlier detection +- **Candlestick**: Financial OHLC analysis + +### 4. Insight Report Generation + +Each report contains: +- **Executive Summary**: Key findings and recommendations overview +- **Data Profile**: Dataset characteristics and quality assessment +- **Key Insights**: Actionable findings with supporting visualizations +- **Chart Sections**: Interactive ECharts + detailed insights per chart +- **Recommendations**: Data-driven action items +- **Methodology Notes**: Analysis approach and assumptions + +--- + +## CRITICAL WORKFLOW - MUST FOLLOW + +### Chart Generation Protocol (MANDATORY) + +**IMPORTANT: You MUST generate charts ONE BY ONE. Never generate all charts at once.** + +The workflow is strictly sequential: + +``` +Data Loading → Analysis → Insight Planning + │ + ├─► Read abilities/data-analysis.md if needed + │ + ▼ +Chart 1 → Generate → Validate (scripts/validate_echarts.py) → Fix (if needed) → Confirm + ↓ +Chart 2 → Generate → Validate → Fix (if needed) → Confirm + ↓ +Chart 3 → Generate → Validate → Fix (if needed) → Confirm + ↓ +... (continue for each chart) + ↓ +Final Insight Report → data_insight_report.md +``` + +--- + +## Phase 1: Data Loading & Profiling + +### Step 1.1: Read Data Analysis Capability + +**CRITICAL: Before performing data analysis, read the capability document:** + +```markdown +Read `abilities/data-analysis.md` for: +- Script usage and parameters +- SQL query patterns +- Statistical summary generation +- Data export options +``` + +### Step 1.2: Load Data + +``` +1. Detect file format based on extension +2. Use scripts/analyze.py to load and inspect data: + python scripts/analyze.py --files /path/to/data.xlsx --action inspect +3. Parse and validate data structure +``` + +### Step 1.3: Profile Data + +Generate a data profile including: +- **Basic Info**: Row count, column count, file size +- **Column Analysis**: Data types, unique values, missing values per column +- **Data Quality**: Duplicate rows, null percentages, data type consistency +- **Statistical Summary**: For numeric columns (min, max, mean, median, std) +- **Sample Data**: First/last few rows for visual confirmation + +**Use the analysis script:** +```bash +python scripts/analyze.py --files /path/to/data.xlsx --action summary --table Sheet1 +``` + +### Step 1.4: Data Cleaning + +Execute cleaning based on profile: +- Handle missing values (impute or remove) +- Remove duplicate records +- Convert data types as needed +- Detect and handle outliers +- Normalize text fields + +--- + +## Phase 2: Insight Planning + +1. Execute statistical analysis using `scripts/analyze.py`: + - Descriptive statistics (mean, median, std, distribution) + - Trend analysis (growth rates, seasonality, forecasts) + - Correlation analysis (variable relationships) + - Segmentation (group comparisons, rankings) + +2. Plan 4-7 key charts to generate (create a plan, do NOT generate yet) + +3. **Create an Insight Plan** - Document before generating: + +```markdown +## 数据洞察计划 + +### 数据概况 +- 总记录数: X +- 字段数: Y +- 时间范围: [如适用] +- 关键指标: [列出核心指标] + +### 洞察方向 +1. [洞察方向1 - 如: 销售趋势分析] +2. [洞察方向2 - 如: 产品类别表现] +3. [洞察方向3 - 如: 区域分布对比] +... + +### 图表规划 + +| 序号 | 图表类型 | 图表标题 | 数据来源 | 核心洞察 | 业务价值 | +|------|----------|----------|----------|----------|----------| +| 1 | line | 销售额趋势 | 字段A, 字段B | 月度销售趋势 | 识别增长/下滑周期 | +| 2 | pie | 产品占比 | 字段C, 字段D | 产品销售占比 | 资源分配决策 | +| ... | ... | ... | ... | ... | ... | +``` + +--- + +## Phase 3: Sequential Chart Generation (STEP BY STEP) + +### Step 3.1: Generate Chart 1 + +**Output to file**: `output_fs/charts/chart_01.md` + +```markdown +# 图表 1: [图表标题] + +## 可视化 + +```echarts +{ + "title": { "text": "[标题]" }, + "tooltip": { "trigger": "axis" }, + "legend": { "data": ["系列名称"] }, + "xAxis": { "type": "category", "data": ["分类1", "分类2"] }, + "yAxis": { "type": "value" }, + "series": [ + { "name": "系列名称", "type": "bar", "data": [100, 200] } + ] +} +``` + +## 数据洞察 + +### 关键发现 +- **发现1**: 描述数据中的关键模式 +- **发现2**: 解释趋势或异常 +- **发现3**: 对比分析结论 + +### 业务影响 +- [业务影响描述] + +### 行动建议 +- [基于数据的可执行建议] + +## 数据来源 + +- 原始数据: [文件名/Sheet名称] +- 数据范围: [具体字段或筛选条件] +- 数据处理: [如: 按月聚合/过滤异常值等] +``` + +### Step 3.2: Validate Chart 1 (MANDATORY - Use Validation Script) + +**CRITICAL: After generating each chart, you MUST run the validation script.** + +```bash +python scripts/validate_echarts.py output_fs/charts/chart_01.md +``` + +#### Validation Output Interpretation + +The script outputs a structured report: + +```markdown +## 校验报告 - [图表标题] + +### JSON语法校验 +- ✅/❌ JSON解析: [状态] +- ✅/❌ 引号检查: [状态] +- ✅/❌ 尾逗号检查: [状态] +- ✅/❌ 函数检查: [状态] + +### ECharts结构校验 +- ✅/❌ title字段: [状态] +- ✅/❌ tooltip字段: [状态] +- ✅/❌ series字段: [状态] +- ✅/❌ series[0].type: [状态] +- ✅/❌ series[0].data: [状态] + +### 数据完整性校验 +- ✅/❌ 数据长度匹配: [状态] +- ✅/❌ NaN检查: [状态] +- ✅/❌ Infinity检查: [状态] +- ✅/❌ 数值类型检查: [状态] + +### 布局校验 +- ✅/❌ grid配置: [状态] +- ✅/❌ 标题长度: [状态] +- ✅/❌ 图例项数: [状态] + +### 校验结果 +✅ 通过 / ❌ 失败 - X 个错误, Y 个警告 +``` + +#### Validation Rules + +| Category | Check | Level | Description | +|----------|-------|-------|-------------| +| JSON语法 | JSON解析 | ERROR | Valid JSON syntax | +| JSON语法 | 引号检查 | ERROR | Must use double quotes | +| JSON语法 | 尾逗号检查 | ERROR | No trailing commas | +| JSON语法 | 函数检查 | ERROR | No JavaScript functions | +| ECharts结构 | series字段 | ERROR | Required, non-empty array | +| ECharts结构 | series[].type | ERROR | Valid chart type | +| ECharts结构 | series[].data | ERROR | Must exist and be array | +| 数据完整性 | 数据长度匹配 | ERROR | xAxis/series data length match | +| 数据完整性 | NaN检查 | ERROR | No NaN values | +| 数据完整性 | Infinity检查 | ERROR | No Infinity values | +| 布局 | grid配置 | WARNING | Avoid complex positioning | +| 布局 | 标题长度 | WARNING | Under 30 characters | +| 布局 | 图例项数 | WARNING | Under 10 items | + +### Step 3.3: Fix Issues (If Validation Fails) + +**If the validation script reports errors, STOP and FIX immediately.** + +Read `abilities/echarts-validation.md` for detailed fix instructions. + +#### Quick Fix Reference + +**Fix 1: JavaScript Functions → String Templates** +```javascript +// ❌ WRONG +"tooltip": { "formatter": function(params) { return params[0].name; } } + +// ✅ CORRECT +"tooltip": { "formatter": "{b}: {c}" } +``` + +**Fix 2: Single Quotes → Double Quotes** +```javascript +// ❌ WRONG +{ 'name': 'Sales', 'type': 'bar' } + +// ✅ CORRECT +{ "name": "Sales", "type": "bar" } +``` + +**Fix 3: Trailing Commas** +```javascript +// ❌ WRONG +"data": [1, 2, 3,], +"series": [{ "name": "A" },] + +// ✅ CORRECT +"data": [1, 2, 3], +"series": [{ "name": "A" }] +``` + +**Fix 4: Data Length Mismatch** +```javascript +// ❌ WRONG: 3 categories but 4 data points +"xAxis": { "data": ["A", "B", "C"] }, +"series": [{ "data": [10, 20, 30, 40] }] + +// ✅ CORRECT: Align data +"xAxis": { "data": ["A", "B", "C", "D"] }, +"series": [{ "data": [10, 20, 30, 40] }] +``` + +**Fix 5: Layout Issues** +```javascript +// ❌ WRONG: Overly complex manual positioning +"grid": { "left": "3%", "right": "4%", "bottom": "3%", "top": "15%" } + +// ✅ CORRECT: Let ECharts handle it +"grid": { "containLabel": true } +``` + +**Fix 6: String Numbers** +```javascript +// ❌ WRONG: Numbers as strings +"data": ["100", "200", "300"] + +// ✅ CORRECT: Actual numbers +"data": [100, 200, 300] +``` + +### Step 3.4: Re-validate After Fix + +After fixing, run the validation script again: + +```bash +python scripts/validate_echarts.py output_fs/charts/chart_01.md +``` + +Repeat until validation passes with `✅ 通过`. + +### Step 3.5: Confirm and Proceed + +After validation passes, record success and proceed to next chart: + +```markdown +## 图表 1 完成 ✅ +文件: output_fs/charts/chart_01.md +状态: 已校验通过 +--- +继续生成图表 2... +``` + +### Step 3.6: Repeat for Each Chart + +Repeat steps 3.1-3.5 for each planned chart: +- Chart 2 → `output_fs/charts/chart_02.md` +- Chart 3 → `output_fs/charts/chart_03.md` +- ... +- Chart N → `output_fs/charts/chart_N.md` + +--- + +## Phase 4: Final Insight Report Generation + +After ALL charts are generated and validated individually: + +### Step 4.1: Verify All Charts + +Run validation on all charts: + +```bash +python scripts/validate_echarts.py output_fs/charts/chart_01.md +python scripts/validate_echarts.py output_fs/charts/chart_02.md +python scripts/validate_echarts.py output_fs/charts/chart_03.md +# ... etc +``` + +Create status summary: + +```markdown +## 图表完成状态汇总 + +| 图表 | 文件 | 状态 | +|------|------|------| +| 图表 1 | chart_01.md | ✅ 通过 | +| 图表 2 | chart_02.md | ✅ 通过 | +| 图表 3 | chart_03.md | ✅ 通过 | +| ... | ... | ... | +``` + +### Step 4.2: Generate Unified Insight Report + +**Output to file**: `output_fs/data_insight_report.md` + +Merge all charts and analytical insights into a single comprehensive report: + +```markdown +# 数据洞察报告 + +## 执行摘要 + +[3-5句话概述核心发现和最重要的建议] + +--- + +## 数据概况 + +### 基本信息 + +| 指标 | 数值 | +|------|------| +| 数据来源 | [文件名] | +| 总记录数 | X | +| 字段数 | Y | +| 时间范围 | YYYY-MM-DD ~ YYYY-MM-DD | +| 数据质量评分 | [高/中/低] | + +### 关键指标概览 + +| 指标名称 | 当前值 | 变化趋势 | 备注 | +|----------|--------|----------|------| +| 指标1 | XXX | ↑/↓/→ | 说明 | +| 指标2 | XXX | ↑/↓/→ | 说明 | +| ... | ... | ... | ... | + +--- + +## 核心洞察 + +### 洞察 1: [标题] + +**发现**: [关键发现描述] + +**数据支撑**: [具体数据] + +**业务影响**: [对业务的实际影响] + +**建议行动**: [可执行的具体建议] + +### 洞察 2: [标题] + +[同上结构] + +--- + +## 数据可视化分析 + +本节包含 [N] 个交互式图表，展示数据分析的关键发现。 + +--- + +### 图表 1: [标题] + +#### 可视化 + +```echarts +{ ... validated JSON ... } +``` + +#### 数据洞察 + +- **关键发现**: ... +- **趋势分析**: ... +- **业务建议**: ... + +--- + +### 图表 2: [标题] + +#### 可视化 + +```echarts +{ ... validated JSON ... } +``` + +#### 数据洞察 + +- **关键发现**: ... +- **趋势分析**: ... +- **业务建议**: ... + +--- + +... (continue for all charts) + +--- + +## 综合结论 + +### 核心洞察总结 + +1. [洞察1总结] +2. [洞察2总结] +3. [洞察3总结] + +### 行动建议优先级 + +| 优先级 | 建议行动 | 预期影响 | 实施难度 | +|--------|----------|----------|----------| +| 高 | [建议1] | [影响描述] | 低/中/高 | +| 中 | [建议2] | [影响描述] | 低/中/高 | +| 低 | [建议3] | [影响描述] | 低/中/高 | + +### 后续分析方向 + +- [可选的进一步分析建议1] +- [可选的进一步分析建议2] +- [可选的进一步分析建议3] + +--- + +## 方法论 + +### 分析方法 + +[说明使用的分析方法和技术] + +### 数据处理 + +[说明数据清洗和转换过程] + +### 局限性 + +[说明分析的局限性和假设] + +--- + +## 附录 + +### 数据质量报告 + +[数据质量详情] + +### 技术细节 + +[补充技术信息] +``` + +--- + +## ECharts JSON Configuration Rules + +**CRITICAL**: ECharts configurations MUST be valid JSON. They **MUST NOT** contain JavaScript functions. + +### Prohibited Patterns + +```javascript +// ❌ WRONG - Functions break JSON parsing +"tooltip": { + "formatter": function(params) { return params[0].name; } +} +``` + +### Correct Patterns + +```javascript +// ✅ CORRECT - Use string templates +"tooltip": { + "formatter": "{b}: {c}" +} + +// ✅ CORRECT - Or rely on default tooltip behavior +"tooltip": { "trigger": "axis" } +``` + +--- + +## Safe Chart Templates (Use These) + +### Template 1: Bar Chart + +```json +{ + "title": { "text": "图表标题" }, + "tooltip": { "trigger": "axis" }, + "legend": { "data": ["系列名称"] }, + "xAxis": { "type": "category", "data": ["类别1", "类别2", "类别3"] }, + "yAxis": { "type": "value" }, + "series": [{ "name": "系列名称", "type": "bar", "data": [100, 200, 300] }] +} +``` + +### Template 2: Line Chart + +```json +{ + "title": { "text": "图表标题" }, + "tooltip": { "trigger": "axis" }, + "legend": { "data": ["系列名称"] }, + "xAxis": { "type": "category", "data": ["一月", "二月", "三月"] }, + "yAxis": { "type": "value" }, + "series": [{ "name": "系列名称", "type": "line", "data": [100, 200, 300] }] +} +``` + +### Template 3: Pie Chart + +```json +{ + "title": { "text": "图表标题" }, + "tooltip": { "trigger": "item" }, + "legend": { "data": ["类别A", "类别B", "类别C"] }, + "series": [{ + "type": "pie", + "radius": "50%", + "data": [ + { "name": "类别A", "value": 100 }, + { "name": "类别B", "value": 200 }, + { "name": "类别C", "value": 300 } + ] + }] +} +``` + +### Template 4: Donut Chart + +```json +{ + "title": { "text": "图表标题" }, + "tooltip": { "trigger": "item" }, + "legend": { "data": ["类别A", "类别B"] }, + "series": [{ + "type": "pie", + "radius": ["40%", "70%"], + "data": [ + { "name": "类别A", "value": 100 }, + { "name": "类别B", "value": 200 } + ] + }] +} +``` + +### Template 5: Grouped Bar Chart + +```json +{ + "title": { "text": "图表标题" }, + "tooltip": { "trigger": "axis" }, + "legend": { "data": ["系列A", "系列B"] }, + "xAxis": { "type": "category", "data": ["类别1", "类别2", "类别3"] }, + "yAxis": { "type": "value" }, + "series": [ + { "name": "系列A", "type": "bar", "data": [100, 200, 300] }, + { "name": "系列B", "type": "bar", "data": [150, 250, 350] } + ] +} +``` + +--- + +## Layout Rules (Simplified) + +**CRITICAL PRINCIPLE: If unsure about layout, DO NOT configure it. Use ECharts defaults.** + +### Core Rules + +1. **Default is Best** - ECharts handles most layouts automatically. Only override when necessary. +2. **Minimal Configuration** - Only add layout properties you fully understand. +3. **Test Before Customizing** - If uncertain about positioning, omit the property entirely. + +### When to Add Layout (Only if certain) + +**Only add `grid` if:** +- Axis labels are being cut off AND you know the exact margin needed +- You need precise control over chart dimensions + +**Safe grid configuration (use sparingly):** +```json +{ "grid": { "containLabel": true } } +``` + +**DO NOT manually set `left`, `right`, `top`, `bottom` unless you have verified the values work.** + +### What NOT to Do + +❌ DO NOT add layout properties "just in case" +❌ DO NOT copy complex layout configurations from examples without understanding them +❌ DO NOT try to fix overlap issues by guessing margin values + +--- + +## Color Palette + +Professional color palette for charts: +```json +{"color": ["#5470c6", "#91cc75", "#fac858", "#ee6666", "#73c0de", "#3ba272", "#fc8452", "#9a60b4", "#ea7ccc"]} +``` + +--- + +## Data Embedding + +- Chart data arrays included directly in ECharts JSON configuration +- No external file references +- Use responsive width: 100% container +- Ensure data is properly escaped for JSON format + +--- + +## Best Practices + +1. **Chart Selection**: Choose chart type based on data characteristics + - Trends over time → Line chart + - Category comparison → Bar chart + - Part-to-whole → Pie/Donut chart + - Correlation → Scatter plot + - Distribution → Box plot or histogram + +2. **Chart Quantity Control** (CRITICAL): + - **Generate 4-7 charts maximum** per report + - Each chart must directly address the user's question or business objective + - Do NOT create charts for data exploration purposes - focus on key insights + - Avoid redundant visualizations showing similar information + - When in doubt, prioritize relevance over completeness + +3. **Sequential Generation** (MANDATORY): + - Generate ONE chart at a time + - Validate each chart with `scripts/validate_echarts.py` before proceeding + - Fix any issues immediately + - Merge only after all charts pass validation + +4. **Validation** (MANDATORY): + - **ALWAYS** run validation script after generating each chart + - Fix all ERROR level issues before proceeding + - Address WARNING level issues when possible + - Re-validate after fixes + +5. **Insight Quality**: + - Every insight should be actionable + - Support insights with specific data points + - Connect findings to business impact + - Provide clear recommendations + +6. **Accessibility**: Include clear titles, labels, and legends +7. **Responsive Design**: Use percentage-based dimensions +8. **Color Consistency**: Use consistent colors for same categories across charts +9. **Data Labels**: Show values when precision matters + +--- + +## Dependencies + +Use these skills for implementation: +- `skills(spreadsheet)` - For Excel/CSV file reading and manipulation +- `skills(echart)` - For ECharts visualization generation + +### Internal Capabilities + +- **abilities/data-analysis.md** - SQL-based data analysis with DuckDB +- **abilities/echarts-validation.md** - ECharts configuration validation rules and fixes +- **scripts/analyze.py** - Data analysis script for inspecting, querying, and summarizing data +- **scripts/validate_echarts.py** - ECharts configuration validation script + +--- + +## Example Usage + +``` +User: Analyze the sales data in data/sales.xlsx and create an insight report + +Agent: +1. Read abilities/data-analysis.md for data analysis instructions +2. Load Excel file using scripts/analyze.py --action inspect +3. Profile data structure and quality using --action summary +4. Clean data (handle missing values, duplicates, outliers) +5. Execute statistical analysis with SQL queries +6. Create Insight Plan with 4-7 charts +7. FOR EACH chart (one by one): + a. Generate chart_N.md with ECharts JSON + b. Run: python scripts/validate_echarts.py output_fs/charts/chart_N.md + c. Review validation report + d. Fix any ERROR level issues + e. Re-validate until ✅ 通过 + f. Confirm chart passes +8. Generate unified data_insight_report.md with: + - Executive summary + - Data profile + - Key insights with business impact + - All validated charts with insights + - Prioritized action recommendations + - Methodology and limitations +9. Save files to output_fs/ +``` + +``` +User: 分析 data/transactions.csv 文件，生成数据洞察报告 + +Agent: +1. 读取 abilities/data-analysis.md 了解数据分析方法 +2. 使用 scripts/analyze.py 加载 CSV 文件 +3. 分析数据结构和质量 +4. 数据清洗和预处理 +5. 执行探索性数据分析 +6. 制定洞察计划（4-7个图表） +7. 逐个生成图表: + a. 生成 chart_N.md + b. 运行校验: python scripts/validate_echarts.py output_fs/charts/chart_N.md + c. 查看校验报告 + d. 修复所有错误 + e. 重新校验直到通过 + f. 确认图表校验通过 +8. 生成完整的数据洞察报告 +9. 保存至 output_fs/data_insight_report.md +``` + +--- + +## Output Files Structure + +``` +output_fs/ +├── charts/ +│ ├── chart_01.md # Individual chart (validated) +│ ├── chart_02.md # Individual chart (validated) +│ ├── chart_03.md # Individual chart (validated) +│ └── ... +└── data_insight_report.md # Unified insight report with all charts and recommendations +``` + +--- + +## Changelog + +### v1.3.0 (Current) +- Enhanced data-analysis capability with comprehensive pandas support +- Added pandas analysis patterns: data loading, cleaning, transformation, grouping, time series +- Added statistical analysis examples: correlation, trend analysis, outlier detection, segmentation +- Added decision guidance for when to use SQL script vs pandas code +- Updated capability assessment to cover all data analysis scenarios + +### v1.2.0 +- Added echarts-validation capability with dedicated ability document +- Added scripts/validate_echarts.py for automated chart validation +- Integrated validation script into chart generation workflow +- Added validation rules reference table +- Enhanced workflow to mandate script-based validation after each chart + +### v1.1.0 +- Integrated data-analysis capability with dedicated ability document +- Added scripts/analyze.py for SQL-based data analysis +- Added abilities/ directory for modular capability documentation +- Added capability assessment section with decision flow +- Added TSV file format support +- Enhanced data profiling with DuckDB SQL engine + +### v1.0.0 +- Initial release: Renamed from `excel-echarts-report` to `data-insight-report` +- Added support for multiple data formats (Excel, CSV, TSV, ODS) +- Enhanced data profiling and quality assessment +- Added structured insight planning phase +- Improved report structure with executive summary and prioritized recommendations + +--- + +*Created for tabular data analysis with ECharts visualization* +*Version 1.3.0 - Enhanced pandas analysis with comprehensive statistical support* diff --git a/libs/hexagent_demo/backend/skills/public/data-insight-report/abilities/data-analysis.md b/libs/hexagent_demo/backend/skills/public/data-insight-report/abilities/data-analysis.md new file mode 100644 index 00000000..36aeb108 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/data-insight-report/abilities/data-analysis.md @@ -0,0 +1,646 @@ +# Data Analysis Ability + +You are an expert data analyst with expertise in SQL, Python (pandas), and statistical analysis. + +## When to Apply + +Use this ability when: +- Writing SQL queries for data extraction +- Analyzing datasets with pandas +- Performing statistical analysis +- Creating data transformations +- Identifying data patterns and insights +- Data cleaning and preparation + +## Core Competencies + +### SQL Analysis (via Script) +- Schema inspection and data profiling +- Complex queries with JOINs, subqueries, CTEs +- Window functions and aggregations +- Statistical summaries +- Result export to CSV/JSON/Markdown + +### pandas Analysis (via Code) +- Data manipulation and transformation +- Grouping, filtering, pivoting +- Time series analysis +- Handling missing data +- Custom statistical analysis +- Data visualization preparation + +### Statistics +- Descriptive statistics +- Hypothesis testing +- Correlation analysis +- Trend analysis +- Outlier detection + +--- + +## Supported Data Formats + +| Format | Extensions | Description | +|--------|------------|-------------| +| Excel | `.xlsx`, `.xls`, `.xlsm` | Microsoft Excel workbooks | +| CSV | `.csv` | Comma-separated values | +| TSV | `.tsv`, `.tab` | Tab-separated values | +| JSON | `.json` | JSON files | +| Parquet | `.parquet` | Apache Parquet files | + +--- + +## Method 1: SQL Analysis (Script-Based) + +Use `scripts/analyze.py` for quick SQL-based analysis with DuckDB. + +### Script Location + +``` +scripts/analyze.py +``` + +### Actions + +| Action | Description | +|--------|-------------| +| `inspect` | View schema, columns, types, sample data | +| `query` | Execute SQL queries | +| `summary` | Generate statistical summaries | + +### Usage Examples + +#### Inspect File Structure + +```bash +python scripts/analyze.py \ + --files /path/to/data.xlsx \ + --action inspect +``` + +Returns: sheet names, columns, data types, row counts, sample data. + +#### Execute SQL Query + +```bash +python scripts/analyze.py \ + --files /path/to/data.xlsx \ + --action query \ + --sql "SELECT category, COUNT(*) as count, AVG(amount) as avg_amount FROM Sheet1 GROUP BY category ORDER BY count DESC" +``` + +#### Generate Statistical Summary + +```bash +python scripts/analyze.py \ + --files /path/to/data.xlsx \ + --action summary \ + --table Sheet1 +``` + +#### Export Results + +```bash +python scripts/analyze.py \ + --files /path/to/data.xlsx \ + --action query \ + --sql "SELECT * FROM Sheet1 WHERE amount > 1000" \ + --output-file /path/to/output/results.csv +``` + +### SQL Analysis Patterns + +#### Basic Exploration + +```sql +-- Row count +SELECT COUNT(*) FROM Sheet1 + +-- Distinct values +SELECT DISTINCT category FROM Sheet1 + +-- Value distribution +SELECT category, COUNT(*) as cnt +FROM Sheet1 +GROUP BY category +ORDER BY cnt DESC + +-- Date range +SELECT MIN(date_col), MAX(date_col) FROM Sheet1 +``` + +#### Aggregation & Grouping + +```sql +-- Revenue by category and month +SELECT category, + DATE_TRUNC('month', order_date) as month, + SUM(revenue) as total_revenue +FROM Sales +GROUP BY category, month +ORDER BY month, total_revenue DESC + +-- Top 10 customers +SELECT customer_name, SUM(amount) as total_spend +FROM Orders +GROUP BY customer_name +ORDER BY total_spend DESC +LIMIT 10 +``` + +#### Window Functions + +```sql +-- Running total and rank +SELECT order_date, amount, + SUM(amount) OVER (ORDER BY order_date) as running_total, + RANK() OVER (ORDER BY amount DESC) as amount_rank +FROM Sales +``` + +--- + +## Method 2: pandas Analysis (Code-Based) + +Use pandas for flexible, programmatic data analysis with Python code. + +### When to Use pandas vs SQL + +| Use pandas when... | Use SQL when... | +|-------------------|-----------------| +| Need complex data transformations | Quick aggregations and filtering | +| Custom statistical analysis | Standard summaries | +| Data cleaning with conditional logic | Simple joins and grouping | +| Time series manipulation | Large datasets (DuckDB is faster) | +| Iterative exploration | One-time queries | +| Need to chain multiple operations | Export to file directly | + +### Loading Data + +```python +import pandas as pd + +# Excel +df = pd.read_excel('data.xlsx', sheet_name='Sheet1') +df = pd.read_excel('data.xlsx', sheet_name=None) # All sheets as dict + +# CSV +df = pd.read_csv('data.csv') +df = pd.read_csv('data.csv', encoding='utf-8', parse_dates=['date_col']) + +# TSV +df = pd.read_csv('data.tsv', sep='\t') + +# JSON +df = pd.read_json('data.json') +``` + +### Data Inspection + +```python +# Basic info +df.info() +df.shape +df.columns.tolist() +df.dtypes + +# Preview +df.head(10) +df.tail(5) +df.sample(5) + +# Statistical summary +df.describe() +df.describe(include='all') + +# Missing values +df.isnull().sum() +df.isnull().mean() * 100 # Percentage + +# Unique values +df['column'].nunique() +df['column'].value_counts() +``` + +### Data Cleaning + +```python +# Handle missing values +df.dropna() # Drop rows with any missing +df.dropna(subset=['col1', 'col2']) # Drop if specific columns missing +df.fillna(0) # Fill with value +df.fillna({'col1': 0, 'col2': 'unknown'}) # Fill per column +df['col'].fillna(df['col'].mean()) # Fill with mean + +# Remove duplicates +df.drop_duplicates() +df.drop_duplicates(subset=['id']) +df.duplicated().sum() # Count duplicates + +# Type conversion +df['date'] = pd.to_datetime(df['date']) +df['amount'] = pd.to_numeric(df['amount'], errors='coerce') +df['category'] = df['category'].astype('category') + +# String cleaning +df['name'] = df['name'].str.strip() +df['name'] = df['name'].str.lower() +df['name'] = df['name'].str.replace(r'\s+', ' ', regex=True) + +# Outlier handling +q1 = df['amount'].quantile(0.25) +q3 = df['amount'].quantile(0.75) +iqr = q3 - q1 +df_clean = df[(df['amount'] >= q1 - 1.5*iqr) & (df['amount'] <= q3 + 1.5*iqr)] +``` + +### Data Transformation + +```python +# Filtering +df[df['amount'] > 100] +df[(df['amount'] > 100) & (df['category'] == 'A')] +df.query('amount > 100 and category == "A"') +df[~df['category'].isin(['A', 'B'])] # Exclude + +# Sorting +df.sort_values('amount', ascending=False) +df.sort_values(['category', 'amount'], ascending=[True, False]) + +# Column operations +df['new_col'] = df['col1'] + df['col2'] +df['ratio'] = df['amount'] / df['total'] +df['log_amount'] = np.log(df['amount']) + +# Rename columns +df.rename(columns={'old_name': 'new_name'}) +df.columns = ['col1', 'col2', 'col3'] # All at once + +# Select/reorder columns +df[['col1', 'col2', 'col3']] +df.drop(columns=['col1', 'col2']) +``` + +### Grouping & Aggregation + +```python +# Basic groupby +df.groupby('category')['amount'].sum() +df.groupby('category')['amount'].agg(['sum', 'mean', 'count']) + +# Multiple columns +df.groupby(['category', 'region'])['amount'].sum() + +# Multiple aggregations +df.groupby('category').agg({ + 'amount': ['sum', 'mean', 'std'], + 'quantity': ['sum', 'count'], + 'date': ['min', 'max'] +}) + +# Custom aggregations +df.groupby('category')['amount'].agg( + total='sum', + average='mean', + count='count', + range_=lambda x: x.max() - x.min() +) + +# Transform (preserve shape) +df['category_avg'] = df.groupby('category')['amount'].transform('mean') + +# Filter groups +df.groupby('category').filter(lambda x: x['amount'].sum() > 1000) +``` + +### Pivot Tables & Cross-tabs + +```python +# Pivot table +df.pivot_table( + values='amount', + index='category', + columns='region', + aggfunc='sum', + fill_value=0 +) + +# Multiple aggregations +df.pivot_table( + values='amount', + index='category', + columns='region', + aggfunc=['sum', 'mean', 'count'] +) + +# Cross-tabulation +pd.crosstab(df['category'], df['region']) +pd.crosstab(df['category'], df['region'], normalize='index') # Row percentages +``` + +### Time Series Analysis + +```python +# Convert to datetime +df['date'] = pd.to_datetime(df['date']) + +# Set datetime index +df = df.set_index('date') + +# Resample (time-based grouping) +df.resample('M')['amount'].sum() # Monthly +df.resample('W')['amount'].mean() # Weekly +df.resample('Q')['amount'].sum() # Quarterly + +# Rolling windows +df['rolling_avg'] = df['amount'].rolling(window=7).mean() +df['rolling_sum'] = df['amount'].rolling(window=30).sum() + +# Date components +df['year'] = df['date'].dt.year +df['month'] = df['date'].dt.month +df['day'] = df['date'].dt.day +df['weekday'] = df['date'].dt.day_name() +df['quarter'] = df['date'].dt.quarter + +# Shift (lag/lead) +df['prev_amount'] = df['amount'].shift(1) +df['pct_change'] = df['amount'].pct_change() +``` + +### Statistical Analysis + +```python +import numpy as np +from scipy import stats + +# Descriptive statistics +df['amount'].describe() +df['amount'].mean() +df['amount'].median() +df['amount'].std() +df['amount'].var() +df['amount'].quantile([0.25, 0.5, 0.75]) + +# Correlation +df.corr() # Correlation matrix +df.corr()['target'] # Correlation with target +df[['col1', 'col2', 'col3']].corr() + +# Covariance +df.cov() + +# Hypothesis testing +stats.ttest_ind(df[df['group'] == 'A']['amount'], + df[df['group'] == 'B']['amount']) + +stats.chi2_contingency(pd.crosstab(df['cat1'], df['cat2'])) + +# Normality test +stats.normaltest(df['amount']) + +# Correlation test +stats.pearsonr(df['col1'], df['col2']) +stats.spearmanr(df['col1'], df['col2']) +``` + +### Data Merging + +```python +# Concatenate +pd.concat([df1, df2], axis=0) # Stack vertically +pd.concat([df1, df2], axis=1) # Side by side + +# Merge (SQL-style joins) +pd.merge(df1, df2, on='key') # Inner join +pd.merge(df1, df2, on='key', how='left') # Left join +pd.merge(df1, df2, on='key', how='right') # Right join +pd.merge(df1, df2, on='key', how='outer') # Full outer join + +# Merge on different column names +pd.merge(df1, df2, left_on='id', right_on='customer_id') + +# Join on index +df1.join(df2, on='key') +``` + +### Exporting Data + +```python +# To CSV +df.to_csv('output.csv', index=False) +df.to_csv('output.csv', index=False, encoding='utf-8-sig') + +# To Excel +df.to_excel('output.xlsx', index=False, sheet_name='Sheet1') + +# To JSON +df.to_json('output.json', orient='records', indent=2) + +# To Markdown table +print(df.to_markdown(index=False)) + +# To HTML +df.to_html('output.html', index=False) +``` + +--- + +## Method 3: Statistical Analysis Examples + +### Correlation Analysis + +```python +import pandas as pd +import numpy as np + +# Load data +df = pd.read_excel('data.xlsx') + +# Correlation matrix +corr_matrix = df.select_dtypes(include=[np.number]).corr() + +# Find highly correlated pairs +high_corr = [] +for i in range(len(corr_matrix.columns)): + for j in range(i+1, len(corr_matrix.columns)): + if abs(corr_matrix.iloc[i, j]) > 0.7: + high_corr.append({ + 'var1': corr_matrix.columns[i], + 'var2': corr_matrix.columns[j], + 'correlation': corr_matrix.iloc[i, j] + }) + +high_corr_df = pd.DataFrame(high_corr) +print(high_corr_df) +``` + +### Trend Analysis + +```python +import pandas as pd +from scipy import stats + +df = pd.read_excel('sales.xlsx') +df['date'] = pd.to_datetime(df['date']) +df = df.sort_values('date') + +# Monthly trend +monthly = df.resample('M', on='date')['amount'].sum().reset_index() + +# Linear regression for trend +x = np.arange(len(monthly)) +y = monthly['amount'].values +slope, intercept, r_value, p_value, std_err = stats.linregress(x, y) + +print(f"Trend slope: {slope:.2f} per month") +print(f"R-squared: {r_value**2:.3f}") +print(f"P-value: {p_value:.4f}") + +# Trend direction +if slope > 0 and p_value < 0.05: + print("Significant upward trend") +elif slope < 0 and p_value < 0.05: + print("Significant downward trend") +else: + print("No significant trend") +``` + +### Outlier Detection + +```python +import pandas as pd +import numpy as np + +df = pd.read_excel('data.xlsx') + +# IQR method +def detect_outliers_iqr(series, multiplier=1.5): + q1 = series.quantile(0.25) + q3 = series.quantile(0.75) + iqr = q3 - q1 + lower = q1 - multiplier * iqr + upper = q3 + multiplier * iqr + return (series < lower) | (series > upper) + +# Z-score method +def detect_outliers_zscore(series, threshold=3): + z_scores = np.abs((series - series.mean()) / series.std()) + return z_scores > threshold + +# Apply +for col in df.select_dtypes(include=[np.number]).columns: + outliers_iqr = detect_outliers_iqr(df[col]) + outliers_zscore = detect_outliers_zscore(df[col]) + print(f"{col}: {outliers_iqr.sum()} outliers (IQR), {outliers_zscore.sum()} outliers (Z-score)") +``` + +### Segmentation Analysis + +```python +import pandas as pd + +df = pd.read_excel('customers.xlsx') + +# RFM-like segmentation +df['recency_score'] = pd.qcut(df['days_since_last_purchase'], 5, labels=[5,4,3,2,1]) +df['frequency_score'] = pd.qcut(df['purchase_count'].rank(method='first'), 5, labels=[1,2,3,4,5]) +df['monetary_score'] = pd.qcut(df['total_spent'].rank(method='first'), 5, labels=[1,2,3,4,5]) + +df['rfm_score'] = df['recency_score'].astype(str) + df['frequency_score'].astype(str) + df['monetary_score'].astype(str) + +# Segment summary +segments = df.groupby('rfm_score').agg({ + 'customer_id': 'count', + 'total_spent': ['mean', 'sum'], + 'purchase_count': 'mean' +}).round(2) + +print(segments) +``` + +--- + +## Analysis Workflow Recommendation + +### For Quick Analysis (Use SQL Script) + +1. **Inspect**: `python scripts/analyze.py --files data.xlsx --action inspect` +2. **Summary**: `python scripts/analyze.py --files data.xlsx --action summary --table Sheet1` +3. **Query**: Write SQL for aggregations and filtering +4. **Export**: Use `--output-file` for results + +### For Complex Analysis (Use pandas) + +1. **Load**: `pd.read_excel()` or `pd.read_csv()` +2. **Clean**: Handle missing values, duplicates, type conversions +3. **Explore**: `describe()`, `info()`, `value_counts()` +4. **Transform**: Group, pivot, merge, calculate new columns +5. **Analyze**: Statistical tests, correlation, trends +6. **Export**: `to_csv()`, `to_excel()`, `to_markdown()` + +### When to Combine Both + +``` +1. Use SQL script for initial inspection and quick queries +2. Export subset of data for deeper pandas analysis +3. Use pandas for custom transformations and statistics +4. Use SQL for final aggregations if working with large data +``` + +--- + +## Parameters Reference + +### SQL Script Parameters + +| Parameter | Required | Description | +|-----------|----------|-------------| +| `--files` | Yes | Space-separated paths to data files | +| `--action` | Yes | One of: `inspect`, `query`, `summary` | +| `--sql` | For `query` | SQL query to execute | +| `--table` | For `summary` | Table/sheet name to summarize | +| `--output-file` | No | Path to export results (CSV/JSON/MD) | + +### Common pandas Parameters + +```python +# read_excel +pd.read_excel(file, sheet_name=0, header=0, usecols=None, dtype=None, parse_dates=None) + +# read_csv +pd.read_csv(file, sep=',', header=0, encoding=None, parse_dates=None, chunksize=None) + +# to_csv +df.to_csv(file, index=True, encoding='utf-8', sep=',') + +# to_excel +df.to_excel(file, sheet_name='Sheet1', index=True) +``` + +--- + +## Notes + +- DuckDB (SQL script) is faster for large datasets (100MB+) +- pandas is more flexible for complex transformations +- Use SQL for joins and simple aggregations +- Use pandas for custom logic and iterative analysis +- Cache is automatic for SQL script — repeated queries are instant + +--- + +## Integration with Data Insight Report + +When using this ability within the `data-insight-report` skill: + +1. Use SQL script for initial data profiling (`inspect`, `summary`) +2. Use pandas for complex transformations and statistical analysis +3. Export processed data to CSV for chart generation +4. Document findings for insight planning phase + +The analysis results feed directly into: +- Data quality assessment +- Insight planning +- Chart data preparation +- Statistical insights for the report diff --git a/libs/hexagent_demo/backend/skills/public/data-insight-report/abilities/echarts-validation.md b/libs/hexagent_demo/backend/skills/public/data-insight-report/abilities/echarts-validation.md new file mode 100644 index 00000000..fc6bd033 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/data-insight-report/abilities/echarts-validation.md @@ -0,0 +1,285 @@ +# ECharts Validation Ability + +## Overview + +This ability provides automated validation for ECharts JSON configurations to ensure they are syntactically correct, structurally valid, and follow best practices before embedding in reports. + +## Script Location + +``` +scripts/validate_echarts.py +``` + +## Core Capabilities + +- **JSON Syntax Validation**: Detects common JSON errors (single quotes, trailing commas, functions, undefined) +- **ECharts Structure Validation**: Validates required fields and chart type configurations +- **Data Integrity Validation**: Checks data length consistency, NaN/Infinity values, type correctness +- **Layout Validation**: Warns about complex layouts and performance issues + +## Usage + +### Basic Usage + +```bash +# Validate a JSON file +python scripts/validate_echarts.py chart_config.json + +# Validate a Markdown file with echarts code block +python scripts/validate_echarts.py output_fs/charts/chart_01.md + +# Validate JSON from stdin +echo '{"title":{"text":"test"},"series":[{"type":"bar","data":[1,2,3]}]}' | python scripts/validate_echarts.py - + +# Output as JSON format +python scripts/validate_echarts.py chart_config.json --format json + +# Strict mode (exit error on warnings too) +python scripts/validate_echarts.py chart_config.json --strict +``` + +### Parameters + +| Parameter | Description | +|-----------|-------------| +| `file` | Path to file containing ECharts config (JSON or Markdown with ```echarts block), or `-` for stdin | +| `--format, -f` | Output format: `markdown` (default) or `json` | +| `--strict, -s` | Exit with error code on any validation failure (including warnings) | + +### Exit Codes + +| Code | Meaning | +|------|---------| +| 0 | All validations passed | +| 1 | One or more ERROR level failures | +| 2 | All passed but WARNING level failures (only with `--strict`) | + +## Validation Categories + +### 1. JSON Syntax Validation (JSON语法校验) + +| Check | Level | Description | +|-------|-------|-------------| +| JSON解析 | ERROR | Valid JSON syntax | +| 引号检查 | ERROR | Must use double quotes, no single quotes | +| 尾逗号检查 | ERROR | No trailing commas in arrays/objects | +| 函数检查 | ERROR | No JavaScript functions allowed | +| undefined检查 | ERROR | No `undefined` values | + +### 2. ECharts Structure Validation (ECharts结构校验) + +| Check | Level | Description | +|-------|-------|-------------| +| title字段 | WARNING | Recommended to have title | +| tooltip字段 | WARNING | Recommended to have tooltip | +| series字段 | ERROR | Required, must be non-empty array | +| series[].type | ERROR | Must be valid ECharts chart type | +| series[].data | ERROR | Must exist and be array | +| xAxis/yAxis配置 | ERROR | Required for bar/line/scatter charts | +| 饼图数据格式 | WARNING | Pie data should have name/value | + +### 3. Data Integrity Validation (数据完整性校验) + +| Check | Level | Description | +|-------|-------|-------------| +| 数据长度匹配 | ERROR | xAxis data length must match series data length | +| NaN检查 | ERROR | No NaN values in data | +| Infinity检查 | ERROR | No Infinity values in data | +| 数值类型检查 | WARNING | Numeric values should be numbers, not strings | + +### 4. Layout Validation (布局校验) + +| Check | Level | Description | +|-------|-------|-------------| +| grid配置 | WARNING | Avoid complex manual positioning | +| 标题长度 | WARNING | Keep under 30 characters | +| 图例项数 | WARNING | Keep under 10 items | +| 数据量 | WARNING | Large datasets may affect performance | + +## Output Formats + +### Markdown Output (default) + +```markdown +## 校验报告 - 销售趋势图 + +### JSON语法校验 +- ✅ JSON解析: 通过 +- ✅ 引号检查: 通过 +- ✅ 尾逗号检查: 通过 +- ✅ 函数检查: 无JavaScript函数 + +### ECharts结构校验 +- ✅ title字段: 通过 +- ✅ tooltip字段: 通过 +- ✅ series字段: 通过 +- ✅ series[0].type: 'bar' - 有效 +- ✅ series[0].data: 12 个数据点 + +### 数据完整性校验 +- ✅ series[0] 数据长度匹配: 通过 +- ✅ series[0] NaN检查: 通过 +- ✅ series[0] Infinity检查: 通过 +- ✅ series[0] 数值类型检查: 所有数值为number类型 + +### 布局校验 +- ✅ grid配置: 使用默认布局 +- ✅ 标题长度: 5字符 - 合适 +- ✅ 图例项数: 3项 - 合理 + +### 校验结果 +✅ **通过** +``` + +### JSON Output (`--format json`) + +```json +{ + "chart_title": "销售趋势图", + "chart_type": "bar", + "passed": true, + "error_count": 0, + "warning_count": 0, + "results": [ + { + "level": "INFO", + "category": "JSON语法校验", + "check": "JSON解析", + "status": true, + "message": "" + } + ] +} +``` + +## Integration with Data Insight Report Workflow + +### When to Validate + +**CRITICAL: Validate each chart immediately after generating it, before moving to the next chart.** + +``` +Generate Chart 1 → Validate Chart 1 → Fix Issues → Confirm Pass + ↓ + Generate Chart 2 → ... +``` + +### Validation Workflow + +1. **Generate chart file** (e.g., `output_fs/charts/chart_01.md`) + +2. **Run validation**: + ```bash + python scripts/validate_echarts.py output_fs/charts/chart_01.md + ``` + +3. **Check result**: + - If `✅ 通过`: Proceed to next chart + - If `❌ 失败`: Review errors, fix the chart, re-validate + +4. **Fix common issues**: + - Single quotes → Double quotes + - Trailing commas → Remove + - JavaScript functions → Use string templates + - String numbers → Convert to actual numbers + - Data length mismatch → Align xAxis and series data + +## Programmatic Usage + +```python +from scripts.validate_echarts import validate_echarts_config, validate_file + +# Validate from string +config = ''' +{ + "title": { "text": "Sales" }, + "tooltip": { "trigger": "axis" }, + "xAxis": { "type": "category", "data": ["A", "B", "C"] }, + "yAxis": { "type": "value" }, + "series": [{ "type": "bar", "data": [100, 200, 300] }] +} +''' +report = validate_echarts_config(config) +print(report.to_markdown()) +print(f"Passed: {report.passed}") + +# Validate from file +report = validate_file("output_fs/charts/chart_01.md") +if not report.passed: + for error in report.errors: + print(f"ERROR: {error.check} - {error.message}") +``` + +## Common Error Fixes + +### Fix 1: Single Quotes + +```javascript +// ❌ WRONG +{ 'name': 'Sales', 'type': 'bar' } + +// ✅ CORRECT +{ "name": "Sales", "type": "bar" } +``` + +### Fix 2: Trailing Commas + +```javascript +// ❌ WRONG +"data": [1, 2, 3,], +"series": [{ "name": "A" },] + +// ✅ CORRECT +"data": [1, 2, 3], +"series": [{ "name": "A" }] +``` + +### Fix 3: JavaScript Functions + +```javascript +// ❌ WRONG +"tooltip": { "formatter": function(params) { return params[0].name; } } + +// ✅ CORRECT +"tooltip": { "formatter": "{b}: {c}" } +``` + +### Fix 4: String Numbers + +```javascript +// ❌ WRONG +"data": ["100", "200", "300"] + +// ✅ CORRECT +"data": [100, 200, 300] +``` + +### Fix 5: Data Length Mismatch + +```javascript +// ❌ WRONG: 3 categories but 4 data points +"xAxis": { "data": ["A", "B", "C"] }, +"series": [{ "data": [10, 20, 30, 40] }] + +// ✅ CORRECT: Align data +"xAxis": { "data": ["A", "B", "C", "D"] }, +"series": [{ "data": [10, 20, 30, 40] }] +``` + +### Fix 6: Complex Layout + +```javascript +// ❌ WRONG: Overly complex manual positioning +"grid": { "left": "3%", "right": "4%", "bottom": "3%", "top": "15%" } + +// ✅ CORRECT: Let ECharts handle it +"grid": { "containLabel": true } +// Or remove grid entirely +``` + +## Notes + +- The validator extracts ECharts config from Markdown files by looking for ```echarts code blocks +- Validation levels: ERROR (must fix), WARNING (should fix), INFO (passed) +- Use `--strict` flag to treat warnings as errors in CI/CD pipelines +- The script returns non-zero exit codes for use in automated workflows diff --git a/libs/hexagent_demo/backend/skills/public/data-insight-report/scripts/analyze.py b/libs/hexagent_demo/backend/skills/public/data-insight-report/scripts/analyze.py new file mode 100644 index 00000000..50636d97 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/data-insight-report/scripts/analyze.py @@ -0,0 +1,569 @@ +""" +Data Analysis Script using DuckDB. + +Analyzes Excel (.xlsx/.xls) and CSV files using DuckDB's in-process SQL engine. +Supports schema inspection, SQL queries, statistical summaries, and result export. +""" + +import argparse +import hashlib +import json +import logging +import os +import re +import sys +import tempfile + +logging.basicConfig(level=logging.INFO, format="%(message)s") +logger = logging.getLogger(__name__) + +try: + import duckdb +except ImportError: + logger.error("duckdb is not installed. Installing...") + os.system(f"{sys.executable} -m pip install duckdb openpyxl -q") + import duckdb + +try: + import openpyxl # noqa: F401 +except ImportError: + os.system(f"{sys.executable} -m pip install openpyxl -q") + +# Cache directory for persistent DuckDB databases +CACHE_DIR = os.path.join(tempfile.gettempdir(), ".data-analysis-cache") +TABLE_MAP_SUFFIX = ".table_map.json" + + +def compute_files_hash(files: list[str]) -> str: + """Compute a combined SHA256 hash of all input files for cache key.""" + hasher = hashlib.sha256() + for file_path in sorted(files): + try: + with open(file_path, "rb") as f: + while chunk := f.read(8192): + hasher.update(chunk) + except OSError: + # Include path as fallback if file can't be read + hasher.update(file_path.encode()) + return hasher.hexdigest() + + +def get_cache_db_path(files_hash: str) -> str: + """Get the path to the cached DuckDB database file.""" + os.makedirs(CACHE_DIR, exist_ok=True) + return os.path.join(CACHE_DIR, f"{files_hash}.duckdb") + + +def get_table_map_path(files_hash: str) -> str: + """Get the path to the cached table map JSON file.""" + return os.path.join(CACHE_DIR, f"{files_hash}{TABLE_MAP_SUFFIX}") + + +def save_table_map(files_hash: str, table_map: dict[str, str]) -> None: + """Save table map to a JSON file alongside the cached DB.""" + path = get_table_map_path(files_hash) + with open(path, "w", encoding="utf-8") as f: + json.dump(table_map, f, ensure_ascii=False) + + +def load_table_map(files_hash: str) -> dict[str, str] | None: + """Load table map from cache. Returns None if not found.""" + path = get_table_map_path(files_hash) + if not os.path.exists(path): + return None + try: + with open(path, "r", encoding="utf-8") as f: + return json.load(f) + except Exception: + return None + + +def sanitize_table_name(name: str) -> str: + """Sanitize a sheet/file name into a valid SQL table name.""" + sanitized = re.sub(r"[^\w]", "_", name) + if sanitized and sanitized[0].isdigit(): + sanitized = f"t_{sanitized}" + return sanitized + + +def load_files(con: duckdb.DuckDBPyConnection, files: list[str]) -> dict[str, str]: + """ + Load Excel/CSV files into DuckDB tables. + + Returns a mapping of original_name -> sanitized_table_name. + """ + con.execute("INSTALL spatial; LOAD spatial;") + table_map: dict[str, str] = {} + + for file_path in files: + if not os.path.exists(file_path): + logger.error(f"File not found: {file_path}") + continue + + ext = os.path.splitext(file_path)[1].lower() + + if ext in (".xlsx", ".xls"): + _load_excel(con, file_path, table_map) + elif ext in (".csv", ".tsv", ".tab"): + _load_csv(con, file_path, table_map) + else: + logger.warning(f"Unsupported file format: {ext} ({file_path})") + + return table_map + + +def _load_excel( + con: duckdb.DuckDBPyConnection, file_path: str, table_map: dict[str, str] +) -> None: + """Load all sheets from an Excel file into DuckDB tables.""" + import openpyxl + + wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True) + sheet_names = wb.sheetnames + wb.close() + + for sheet_name in sheet_names: + table_name = sanitize_table_name(sheet_name) + + # Handle duplicate table names + original_table_name = table_name + counter = 1 + while table_name in table_map.values(): + table_name = f"{original_table_name}_{counter}" + counter += 1 + + try: + con.execute( + f""" + CREATE TABLE "{table_name}" AS + SELECT * FROM st_read( + '{file_path}', + layer = '{sheet_name}', + open_options = ['HEADERS=FORCE', 'FIELD_TYPES=AUTO'] + ) + """ + ) + table_map[sheet_name] = table_name + row_count = con.execute(f'SELECT COUNT(*) FROM "{table_name}"').fetchone()[ + 0 + ] + logger.info( + f" Loaded sheet '{sheet_name}' -> table '{table_name}' ({row_count} rows)" + ) + except Exception as e: + logger.warning(f" Failed to load sheet '{sheet_name}': {e}") + + +def _load_csv( + con: duckdb.DuckDBPyConnection, file_path: str, table_map: dict[str, str] +) -> None: + """Load a CSV/TSV file into a DuckDB table.""" + base_name = os.path.splitext(os.path.basename(file_path))[0] + table_name = sanitize_table_name(base_name) + + # Handle duplicate table names + original_table_name = table_name + counter = 1 + while table_name in table_map.values(): + table_name = f"{original_table_name}_{counter}" + counter += 1 + + # Detect delimiter + ext = os.path.splitext(file_path)[1].lower() + delimiter = "\t" if ext in (".tsv", ".tab") else "," + + try: + con.execute( + f""" + CREATE TABLE "{table_name}" AS + SELECT * FROM read_csv_auto('{file_path}', delim='{delimiter}') + """ + ) + table_map[base_name] = table_name + row_count = con.execute(f'SELECT COUNT(*) FROM "{table_name}"').fetchone()[0] + logger.info( + f" Loaded CSV '{base_name}' -> table '{table_name}' ({row_count} rows)" + ) + except Exception as e: + logger.warning(f" Failed to load CSV '{base_name}': {e}") + + +def action_inspect(con: duckdb.DuckDBPyConnection, table_map: dict[str, str]) -> str: + """Inspect the schema of all loaded tables.""" + output_parts = [] + + for original_name, table_name in table_map.items(): + output_parts.append(f"\n{'=' * 60}") + output_parts.append(f'Table: {original_name} (SQL name: "{table_name}")') + output_parts.append(f"{'=' * 60}") + + # Get row count + row_count = con.execute(f'SELECT COUNT(*) FROM "{table_name}"').fetchone()[0] + output_parts.append(f"Rows: {row_count}") + + # Get column info + columns = con.execute(f'DESCRIBE "{table_name}"').fetchall() + output_parts.append(f"\nColumns ({len(columns)}):") + output_parts.append(f"{'Name':<30} {'Type':<15} {'Nullable'}") + output_parts.append(f"{'-' * 30} {'-' * 15} {'-' * 8}") + for col in columns: + col_name, col_type, nullable = col[0], col[1], col[2] + output_parts.append(f"{col_name:<30} {col_type:<15} {nullable}") + + # Get non-null counts per column + col_names = [col[0] for col in columns] + non_null_parts = [] + for c in col_names: + non_null_parts.append(f'COUNT("{c}") as "{c}"') + non_null_sql = f'SELECT {", ".join(non_null_parts)} FROM "{table_name}"' + try: + non_null_counts = con.execute(non_null_sql).fetchone() + output_parts.append(f"\nNon-null counts:") + for i, c in enumerate(col_names): + output_parts.append(f" {c}: {non_null_counts[i]} / {row_count}") + except Exception: + pass + + # Sample data (first 5 rows) + output_parts.append(f"\nSample data (first 5 rows):") + try: + sample = con.execute(f'SELECT * FROM "{table_name}" LIMIT 5').fetchdf() + output_parts.append(sample.to_string(index=False)) + except Exception: + sample = con.execute(f'SELECT * FROM "{table_name}" LIMIT 5').fetchall() + header = [col[0] for col in columns] + output_parts.append(" " + " | ".join(header)) + for row in sample: + output_parts.append(" " + " | ".join(str(v) for v in row)) + + result = "\n".join(output_parts) + print(result) + return result + + +def action_query( + con: duckdb.DuckDBPyConnection, + sql: str, + table_map: dict[str, str], + output_file: str | None = None, +) -> str: + """Execute a SQL query and return/export results.""" + # Replace original sheet/file names with sanitized table names in SQL + modified_sql = sql + for original_name, table_name in sorted( + table_map.items(), key=lambda x: len(x[0]), reverse=True + ): + if original_name != table_name: + # Replace occurrences not already quoted + modified_sql = re.sub( + rf"\b{re.escape(original_name)}\b", + f'"{table_name}"', + modified_sql, + ) + + try: + result = con.execute(modified_sql) + columns = [desc[0] for desc in result.description] + rows = result.fetchall() + except Exception as e: + error_msg = f"SQL Error: {e}\n\nAvailable tables:\n" + for orig, tbl in table_map.items(): + cols = con.execute(f'DESCRIBE "{tbl}"').fetchall() + col_names = [c[0] for c in cols] + error_msg += f' "{tbl}" ({orig}): {", ".join(col_names)}\n' + print(error_msg) + return error_msg + + # Format output + if output_file: + return _export_results(columns, rows, output_file) + + # Print as table + return _format_table(columns, rows) + + +def _format_table(columns: list[str], rows: list[tuple]) -> str: + """Format query results as a readable table.""" + if not rows: + msg = "Query returned 0 rows." + print(msg) + return msg + + # Calculate column widths + col_widths = [len(str(c)) for c in columns] + for row in rows: + for i, val in enumerate(row): + col_widths[i] = max(col_widths[i], len(str(val))) + + # Cap column width + max_width = 40 + col_widths = [min(w, max_width) for w in col_widths] + + # Build table + parts = [] + header = " | ".join(str(c).ljust(col_widths[i]) for i, c in enumerate(columns)) + separator = "-+-".join("-" * col_widths[i] for i in range(len(columns))) + parts.append(header) + parts.append(separator) + for row in rows: + row_str = " | ".join( + str(v)[:max_width].ljust(col_widths[i]) for i, v in enumerate(row) + ) + parts.append(row_str) + + parts.append(f"\n({len(rows)} rows)") + result = "\n".join(parts) + print(result) + return result + + +def _export_results(columns: list[str], rows: list[tuple], output_file: str) -> str: + """Export query results to a file (CSV, JSON, or Markdown).""" + os.makedirs(os.path.dirname(output_file), exist_ok=True) + ext = os.path.splitext(output_file)[1].lower() + + if ext == ".csv": + import csv + + with open(output_file, "w", newline="", encoding="utf-8") as f: + writer = csv.writer(f) + writer.writerow(columns) + writer.writerows(rows) + + elif ext == ".json": + records = [] + for row in rows: + record = {} + for i, col in enumerate(columns): + val = row[i] + # Handle non-JSON-serializable types + if hasattr(val, "isoformat"): + val = val.isoformat() + elif isinstance(val, (bytes, bytearray)): + val = val.hex() + record[col] = val + records.append(record) + with open(output_file, "w", encoding="utf-8") as f: + json.dump(records, f, indent=2, ensure_ascii=False, default=str) + + elif ext == ".md": + with open(output_file, "w", encoding="utf-8") as f: + # Header + f.write("| " + " | ".join(columns) + " |\n") + f.write("| " + " | ".join("---" for _ in columns) + " |\n") + # Rows + for row in rows: + f.write( + "| " + " | ".join(str(v).replace("|", "\\|") for v in row) + " |\n" + ) + else: + msg = f"Unsupported output format: {ext}. Use .csv, .json, or .md" + print(msg) + return msg + + msg = f"Results exported to {output_file} ({len(rows)} rows)" + print(msg) + return msg + + +def action_summary( + con: duckdb.DuckDBPyConnection, + table_name: str, + table_map: dict[str, str], +) -> str: + """Generate statistical summary for a table.""" + # Resolve table name + resolved = table_map.get(table_name, table_name) + + try: + columns = con.execute(f'DESCRIBE "{resolved}"').fetchall() + except Exception: + available = ", ".join(f'"{t}" ({o})' for o, t in table_map.items()) + msg = f"Table '{table_name}' not found. Available tables: {available}" + print(msg) + return msg + + row_count = con.execute(f'SELECT COUNT(*) FROM "{resolved}"').fetchone()[0] + + output_parts = [] + output_parts.append(f"\nStatistical Summary: {table_name}") + output_parts.append(f"Total rows: {row_count}") + output_parts.append(f"{'=' * 70}") + + numeric_types = { + "BIGINT", + "INTEGER", + "SMALLINT", + "TINYINT", + "DOUBLE", + "FLOAT", + "DECIMAL", + "HUGEINT", + "REAL", + "NUMERIC", + } + + for col in columns: + col_name, col_type = col[0], col[1].upper() + output_parts.append(f"\n--- {col_name} ({col[1]}) ---") + + # Check base type (strip parameterized parts) + base_type = re.sub(r"\(.*\)", "", col_type).strip() + + if base_type in numeric_types: + try: + stats = con.execute(f""" + SELECT + COUNT("{col_name}") as count, + AVG("{col_name}")::DOUBLE as mean, + STDDEV("{col_name}")::DOUBLE as std, + MIN("{col_name}") as min, + QUANTILE_CONT("{col_name}", 0.25) as q25, + MEDIAN("{col_name}") as median, + QUANTILE_CONT("{col_name}", 0.75) as q75, + MAX("{col_name}") as max, + COUNT(*) - COUNT("{col_name}") as null_count + FROM "{resolved}" + """).fetchone() + labels = [ + "count", + "mean", + "std", + "min", + "25%", + "50%", + "75%", + "max", + "nulls", + ] + for label, val in zip(labels, stats): + if isinstance(val, float): + output_parts.append(f" {label:<8}: {val:,.4f}") + else: + output_parts.append(f" {label:<8}: {val}") + except Exception as e: + output_parts.append(f" Error computing stats: {e}") + else: + try: + stats = con.execute(f""" + SELECT + COUNT("{col_name}") as count, + COUNT(DISTINCT "{col_name}") as unique_count, + MODE("{col_name}") as mode_val, + COUNT(*) - COUNT("{col_name}") as null_count + FROM "{resolved}" + """).fetchone() + output_parts.append(f" count : {stats[0]}") + output_parts.append(f" unique : {stats[1]}") + output_parts.append(f" top : {stats[2]}") + output_parts.append(f" nulls : {stats[3]}") + + # Show top 5 values + top_vals = con.execute(f""" + SELECT "{col_name}", COUNT(*) as freq + FROM "{resolved}" + WHERE "{col_name}" IS NOT NULL + GROUP BY "{col_name}" + ORDER BY freq DESC + LIMIT 5 + """).fetchall() + if top_vals: + output_parts.append(f" top values:") + for val, freq in top_vals: + pct = (freq / row_count * 100) if row_count > 0 else 0 + output_parts.append(f" {val}: {freq} ({pct:.1f}%)") + except Exception as e: + output_parts.append(f" Error computing stats: {e}") + + result = "\n".join(output_parts) + print(result) + return result + + +def main(): + parser = argparse.ArgumentParser(description="Analyze Excel/CSV files using DuckDB") + parser.add_argument( + "--files", + nargs="+", + required=True, + help="Paths to Excel (.xlsx/.xls) or CSV files", + ) + parser.add_argument( + "--action", + required=True, + choices=["inspect", "query", "summary"], + help="Action to perform: inspect, query, or summary", + ) + parser.add_argument( + "--sql", + type=str, + default=None, + help="SQL query to execute (required for 'query' action)", + ) + parser.add_argument( + "--table", + type=str, + default=None, + help="Table name for summary (required for 'summary' action)", + ) + parser.add_argument( + "--output-file", + type=str, + default=None, + help="Path to export results (CSV/JSON/MD)", + ) + args = parser.parse_args() + + # Validate arguments + if args.action == "query" and not args.sql: + parser.error("--sql is required for 'query' action") + if args.action == "summary" and not args.table: + parser.error("--table is required for 'summary' action") + + # Compute file hash for caching + files_hash = compute_files_hash(args.files) + db_path = get_cache_db_path(files_hash) + cached_table_map = load_table_map(files_hash) + + if cached_table_map and os.path.exists(db_path): + # Cache hit: connect to existing DB + logger.info(f"Cache hit! Using cached database: {db_path}") + con = duckdb.connect(db_path, read_only=True) + table_map = cached_table_map + logger.info( + f"Loaded {len(table_map)} table(s) from cache: {', '.join(table_map.keys())}" + ) + else: + # Cache miss: load files and persist to DB + logger.info("Loading files (first time, will cache for future use)...") + con = duckdb.connect(db_path) + table_map = load_files(con, args.files) + + if not table_map: + logger.error("No tables were loaded. Check file paths and formats.") + # Clean up empty DB file + con.close() + if os.path.exists(db_path): + os.remove(db_path) + sys.exit(1) + + # Save table map for future cache lookups + save_table_map(files_hash, table_map) + logger.info( + f"\nLoaded {len(table_map)} table(s): {', '.join(table_map.keys())}" + ) + logger.info(f"Cached database saved to: {db_path}") + + # Perform action + if args.action == "inspect": + action_inspect(con, table_map) + elif args.action == "query": + action_query(con, args.sql, table_map, args.output_file) + elif args.action == "summary": + action_summary(con, args.table, table_map) + + con.close() + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/data-insight-report/scripts/validate_echarts.py b/libs/hexagent_demo/backend/skills/public/data-insight-report/scripts/validate_echarts.py new file mode 100644 index 00000000..b6258f63 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/data-insight-report/scripts/validate_echarts.py @@ -0,0 +1,649 @@ +""" +ECharts Configuration Validator. + +Validates ECharts JSON configurations for syntax, structure, data integrity, and layout. +Used in the data-insight-report workflow to ensure chart configurations are valid before +embedding in reports. +""" + +import argparse +import json +import re +import sys +from dataclasses import dataclass, field +from enum import Enum +from typing import Any + + +class ValidationLevel(Enum): + ERROR = "ERROR" # Must fix - chart will not render + WARNING = "WARNING" # Should fix - may cause issues + INFO = "INFO" # Best practice suggestion + + +@dataclass +class ValidationResult: + """Result of a single validation check.""" + level: ValidationLevel + category: str + check: str + status: bool + message: str = "" + + +@dataclass +class ChartValidationReport: + """Complete validation report for an ECharts configuration.""" + chart_title: str + chart_type: str + results: list[ValidationResult] = field(default_factory=list) + + @property + def passed(self) -> bool: + """Check if all ERROR level validations passed.""" + return all(r.status or r.level != ValidationLevel.ERROR for r in self.results) + + @property + def errors(self) -> list[ValidationResult]: + """Get all ERROR level failures.""" + return [r for r in self.results if not r.status and r.level == ValidationLevel.ERROR] + + @property + def warnings(self) -> list[ValidationResult]: + """Get all WARNING level failures.""" + return [r for r in self.results if not r.status and r.level == ValidationLevel.WARNING] + + def add_result(self, level: ValidationLevel, category: str, check: str, + status: bool, message: str = "") -> None: + """Add a validation result to the report.""" + self.results.append(ValidationResult(level, category, check, status, message)) + + def to_markdown(self) -> str: + """Generate a Markdown report.""" + lines = [] + lines.append(f"## 校验报告 - {self.chart_title}") + lines.append("") + + # Group by category + categories = {} + for r in self.results: + if r.category not in categories: + categories[r.category] = [] + categories[r.category].append(r) + + for category, results in categories.items(): + lines.append(f"### {category}") + for r in results: + icon = "✅" if r.status else ("❌" if r.level == ValidationLevel.ERROR else "⚠️") + lines.append(f"- {icon} {r.check}: {'通过' if r.status else r.message}") + lines.append("") + + # Summary + lines.append("### 校验结果") + if self.passed: + lines.append("✅ **通过**") + else: + lines.append(f"❌ **失败** - {len(self.errors)} 个错误, {len(self.warnings)} 个警告") + if self.errors: + lines.append("") + lines.append("**需要修复的错误:**") + for e in self.errors: + lines.append(f"- {e.check}: {e.message}") + + return "\n".join(lines) + + +# Valid ECharts chart types +VALID_CHART_TYPES = { + "line", "bar", "pie", "scatter", "effectScatter", "radar", "tree", + "treemap", "sunburst", "boxplot", "candlestick", "heatmap", "map", + "parallel", "lines", "graph", "sankey", "funnel", "gauge", "pictorialBar", + "themeRiver", "custom" +} + +# Valid trigger types for tooltip +VALID_TOOLTIP_TRIGGERS = {"item", "axis", "none"} + +# Recommended max lengths +MAX_TITLE_LENGTH = 30 +MAX_LEGEND_ITEMS = 10 +MAX_SERIES_ITEMS = 1000 + + +def validate_json_syntax(config: str) -> tuple[dict | None, list[ValidationResult]]: + """Validate JSON syntax and common issues.""" + results = [] + + # Check 1: Parse as JSON + try: + data = json.loads(config) + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "JSON解析", True + )) + except json.JSONDecodeError as e: + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "JSON解析", False, f"Invalid JSON: {e}" + )) + return None, results + + # Check 2: No single quotes (should use double quotes) + if "'" in config and '"' in config: + # Mixed quotes + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "引号检查", False, + "Mixed single and double quotes detected" + )) + elif "'" in config and '"' not in config: + # Only single quotes + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "引号检查", False, + "Use double quotes instead of single quotes" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "JSON语法校验", "引号检查", True + )) + + # Check 3: No trailing commas + trailing_comma_pattern = r',\s*[\]\}]' + trailing_commas = re.findall(trailing_comma_pattern, config) + if trailing_commas: + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "尾逗号检查", False, + f"Found {len(trailing_commas)} trailing comma(s)" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "JSON语法校验", "尾逗号检查", True + )) + + # Check 4: No JavaScript functions + function_patterns = [ + r'function\s*\(', + r'=>\s*\{', + r'=>\s*[^,\}\]]+\s*\(', + ] + has_function = False + for pattern in function_patterns: + if re.search(pattern, config): + has_function = True + break + + if has_function: + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "函数检查", False, + "JavaScript functions are not allowed in JSON" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "JSON语法校验", "函数检查", True, "无JavaScript函数" + )) + + # Check 5: No undefined + if "undefined" in config.lower(): + results.append(ValidationResult( + ValidationLevel.ERROR, "JSON语法校验", "undefined检查", False, + "'undefined' is not valid JSON" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "JSON语法校验", "undefined检查", True + )) + + return data, results + + +def validate_echarts_structure(data: dict) -> list[ValidationResult]: + """Validate ECharts configuration structure.""" + results = [] + + # Check 1: Required fields + has_title = "title" in data + has_tooltip = "tooltip" in data + has_series = "series" in data and isinstance(data.get("series"), list) and len(data["series"]) > 0 + + if has_title: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", "title字段", True + )) + else: + results.append(ValidationResult( + ValidationLevel.WARNING, "ECharts结构校验", "title字段", False, + "Missing 'title' field (recommended)" + )) + + if has_tooltip: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", "tooltip字段", True + )) + else: + results.append(ValidationResult( + ValidationLevel.WARNING, "ECharts结构校验", "tooltip字段", False, + "Missing 'tooltip' field (recommended)" + )) + + if has_series: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", "series字段", True + )) + else: + results.append(ValidationResult( + ValidationLevel.ERROR, "ECharts结构校验", "series字段", False, + "Missing or empty 'series' field (required)" + )) + return results # Can't continue without series + + # Check 2: Valid chart types + series = data.get("series", []) + chart_types = set() + for i, s in enumerate(series): + chart_type = s.get("type", "").lower() + if chart_type: + chart_types.add(chart_type) + if chart_type in VALID_CHART_TYPES: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", f"series[{i}].type", True, + f"'{chart_type}' - 有效" + )) + else: + results.append(ValidationResult( + ValidationLevel.ERROR, "ECharts结构校验", f"series[{i}].type", False, + f"'{chart_type}' is not a valid ECharts chart type" + )) + + # Check 3: Data exists in series + for i, s in enumerate(series): + chart_type = s.get("type", "").lower() + data_field = s.get("data") + + if data_field is None: + results.append(ValidationResult( + ValidationLevel.ERROR, "ECharts结构校验", f"series[{i}].data", False, + "Missing 'data' field" + )) + elif not isinstance(data_field, list): + results.append(ValidationResult( + ValidationLevel.ERROR, "ECharts结构校验", f"series[{i}].data", False, + "'data' must be an array" + )) + elif len(data_field) == 0: + results.append(ValidationResult( + ValidationLevel.WARNING, "ECharts结构校验", f"series[{i}].data", False, + "'data' array is empty" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", f"series[{i}].data", True, + f"{len(data_field)} 个数据点" + )) + + # Check 4: Axis configuration for bar/line charts + needs_axis = chart_types & {"line", "bar", "scatter", "effectScatter", "boxplot", "candlestick"} + if needs_axis: + has_xaxis = "xAxis" in data + has_yaxis = "yAxis" in data + + if has_xaxis: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", "xAxis配置", True + )) + else: + results.append(ValidationResult( + ValidationLevel.ERROR, "ECharts结构校验", "xAxis配置", False, + f"'{needs_axis}' charts require xAxis" + )) + + if has_yaxis: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", "yAxis配置", True + )) + else: + results.append(ValidationResult( + ValidationLevel.ERROR, "ECharts结构校验", "yAxis配置", False, + f"'{needs_axis}' charts require yAxis" + )) + + # Check 5: Pie chart data format + if "pie" in chart_types: + for i, s in enumerate(series): + if s.get("type", "").lower() == "pie": + pie_data = s.get("data", []) + if pie_data and isinstance(pie_data, list) and len(pie_data) > 0: + # Check if data items have name and value + first_item = pie_data[0] + if isinstance(first_item, dict): + if "name" in first_item and "value" in first_item: + results.append(ValidationResult( + ValidationLevel.INFO, "ECharts结构校验", f"series[{i}] 饼图数据格式", True + )) + else: + results.append(ValidationResult( + ValidationLevel.WARNING, "ECharts结构校验", f"series[{i}] 饼图数据格式", False, + "Pie data items should have 'name' and 'value' properties" + )) + + return results + + +def validate_data_integrity(data: dict) -> list[ValidationResult]: + """Validate data integrity and consistency.""" + results = [] + + series = data.get("series", []) + if not series: + return results + + # Check xAxis data length matches series data length for bar/line + x_axis = data.get("xAxis", {}) + if isinstance(x_axis, list): + x_axis = x_axis[0] if x_axis else {} + + x_data = x_axis.get("data", []) if isinstance(x_axis, dict) else [] + + for i, s in enumerate(series): + chart_type = s.get("type", "").lower() + s_data = s.get("data", []) + + if chart_type in {"line", "bar"} and x_data: + if len(x_data) != len(s_data): + results.append(ValidationResult( + ValidationLevel.ERROR, "数据完整性校验", f"series[{i}] 数据长度匹配", False, + f"xAxis has {len(x_data)} items, but series[{i}] has {len(s_data)} items" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "数据完整性校验", f"series[{i}] 数据长度匹配", True + )) + + # Check for NaN/Infinity in data + if s_data: + has_nan = False + has_inf = False + has_string_number = False + + for item in s_data: + if isinstance(item, dict): + val = item.get("value") + else: + val = item + + if isinstance(val, float): + import math + if math.isnan(val): + has_nan = True + if math.isinf(val): + has_inf = True + elif isinstance(val, str) and val not in ("", None): + # Check if it's a string that looks like a number + try: + float(val) + has_string_number = True + except (ValueError, TypeError): + pass + + if has_nan: + results.append(ValidationResult( + ValidationLevel.ERROR, "数据完整性校验", f"series[{i}] NaN检查", False, + "Data contains NaN values" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "数据完整性校验", f"series[{i}] NaN检查", True + )) + + if has_inf: + results.append(ValidationResult( + ValidationLevel.ERROR, "数据完整性校验", f"series[{i}] Infinity检查", False, + "Data contains Infinity values" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "数据完整性校验", f"series[{i}] Infinity检查", True + )) + + if has_string_number: + results.append(ValidationResult( + ValidationLevel.WARNING, "数据完整性校验", f"series[{i}] 数值类型检查", False, + "Some numeric values are strings, should be numbers" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "数据完整性校验", f"series[{i}] 数值类型检查", True, + "所有数值为number类型" + )) + + return results + + +def validate_layout(data: dict) -> list[ValidationResult]: + """Validate layout configuration.""" + results = [] + + # Check for overly complex grid configuration + grid = data.get("grid", {}) + if grid: + # Check for manual positioning + manual_props = ["left", "right", "top", "bottom"] + set_props = [p for p in manual_props if p in grid and grid[p]] + + if len(set_props) >= 3: + results.append(ValidationResult( + ValidationLevel.WARNING, "布局校验", "grid配置", False, + f"Complex manual grid positioning ({', '.join(set_props)}), consider using containLabel: true instead" + )) + elif grid.get("containLabel"): + results.append(ValidationResult( + ValidationLevel.INFO, "布局校验", "grid配置", True, "使用 containLabel: true" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "布局校验", "grid配置", True, "使用默认布局" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "布局校验", "grid配置", True, "使用默认布局" + )) + + # Check title length + title = data.get("title", {}) + if isinstance(title, dict): + title_text = title.get("text", "") + if title_text: + if len(title_text) > MAX_TITLE_LENGTH: + results.append(ValidationResult( + ValidationLevel.WARNING, "布局校验", "标题长度", False, + f"Title is {len(title_text)} chars, consider keeping under {MAX_TITLE_LENGTH}" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "布局校验", "标题长度", True, f"{len(title_text)}字符 - 合适" + )) + + # Check legend items count + legend = data.get("legend", {}) + if isinstance(legend, dict): + legend_data = legend.get("data", []) + if legend_data: + if len(legend_data) > MAX_LEGEND_ITEMS: + results.append(ValidationResult( + ValidationLevel.WARNING, "布局校验", "图例项数", False, + f"{len(legend_data)} items, consider keeping under {MAX_LEGEND_ITEMS}" + )) + else: + results.append(ValidationResult( + ValidationLevel.INFO, "布局校验", "图例项数", True, f"{len(legend_data)}项 - 合理" + )) + + # Check series data size + series = data.get("series", []) + for i, s in enumerate(series): + s_data = s.get("data", []) + if s_data and len(s_data) > MAX_SERIES_ITEMS: + results.append(ValidationResult( + ValidationLevel.WARNING, "布局校验", f"series[{i}] 数据量", False, + f"{len(s_data)} items, large datasets may affect performance" + )) + + return results + + +def validate_echarts_config(config: str | dict) -> ChartValidationReport: + """ + Validate an ECharts configuration. + + Args: + config: ECharts configuration as JSON string or dict + + Returns: + ChartValidationReport with all validation results + """ + # Parse config if string + if isinstance(config, str): + config_str = config + data, syntax_results = validate_json_syntax(config_str) + else: + data = config + config_str = json.dumps(config, ensure_ascii=False, indent=2) + syntax_results = [ValidationResult( + ValidationLevel.INFO, "JSON语法校验", "JSON解析", True, "已解析为dict对象" + )] + + # Create report + if data: + chart_title = data.get("title", {}).get("text", "未命名图表") + chart_type = data.get("series", [{}])[0].get("type", "unknown") if data.get("series") else "unknown" + else: + chart_title = "解析失败" + chart_type = "unknown" + + report = ChartValidationReport(chart_title, chart_type) + report.results.extend(syntax_results) + + if data is None: + return report + + # Run all validations + report.results.extend(validate_echarts_structure(data)) + report.results.extend(validate_data_integrity(data)) + report.results.extend(validate_layout(data)) + + return report + + +def validate_file(file_path: str) -> ChartValidationReport: + """ + Validate an ECharts configuration from a file. + + Args: + file_path: Path to file containing ECharts JSON config + + Returns: + ChartValidationReport with all validation results + """ + with open(file_path, "r", encoding="utf-8") as f: + content = f.read() + + # Try to extract echarts code block if present + echarts_pattern = r'```echarts\s*\n(.*?)\n```' + match = re.search(echarts_pattern, content, re.DOTALL) + if match: + config_str = match.group(1) + else: + config_str = content.strip() + + return validate_echarts_config(config_str) + + +def main(): + parser = argparse.ArgumentParser( + description="Validate ECharts JSON configurations", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + # Validate a JSON file + python validate_echarts.py config.json + + # Validate a Markdown file with echarts code block + python validate_echarts.py chart.md + + # Validate JSON from stdin + echo '{"title":{"text":"test"},"series":[{"type":"bar","data":[1,2,3]}]}' | python validate_echarts.py - + + # Output as JSON + python validate_echarts.py config.json --format json + """ + ) + parser.add_argument( + "file", + help="Path to file containing ECharts config (JSON or Markdown with ```echarts block), or '-' for stdin" + ) + parser.add_argument( + "--format", "-f", + choices=["markdown", "json"], + default="markdown", + help="Output format (default: markdown)" + ) + parser.add_argument( + "--strict", "-s", + action="store_true", + help="Exit with error code on any validation failure (including warnings)" + ) + + args = parser.parse_args() + + # Read input + if args.file == "-": + content = sys.stdin.read() + # Try to extract echarts block + echarts_pattern = r'```echarts\s*\n(.*?)\n```' + match = re.search(echarts_pattern, content, re.DOTALL) + config_str = match.group(1) if match else content.strip() + report = validate_echarts_config(config_str) + else: + report = validate_file(args.file) + + # Output results + if args.format == "json": + output = { + "chart_title": report.chart_title, + "chart_type": report.chart_type, + "passed": report.passed, + "error_count": len(report.errors), + "warning_count": len(report.warnings), + "results": [ + { + "level": r.level.value, + "category": r.category, + "check": r.check, + "status": r.status, + "message": r.message + } + for r in report.results + ] + } + print(json.dumps(output, ensure_ascii=False, indent=2)) + else: + print(report.to_markdown()) + + # Exit code + if not report.passed: + sys.exit(1) + if args.strict and report.warnings: + sys.exit(2) + + +def setup_encoding(): + """Setup UTF-8 encoding for Windows console.""" + import sys + import io + if sys.platform == 'win32': + try: + sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8', errors='replace') + sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8', errors='replace') + except Exception: + pass + + +if __name__ == "__main__": + setup_encoding() + main() diff --git a/libs/hexagent_demo/backend/skills/public/deep-research/SKILL.md b/libs/hexagent_demo/backend/skills/public/deep-research/SKILL.md new file mode 100644 index 00000000..d78ad185 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/deep-research/SKILL.md @@ -0,0 +1,201 @@ +--- +name: deep-research +description: Use this skill instead of WebSearch for ANY question requiring web research. Trigger on queries like "what is X", "explain X", "compare X and Y", "research X", or before content generation tasks. Provides systematic multi-angle research methodology instead of single superficial searches. Use this proactively when the user's question needs online information. +metadata: + author: deer-flow + url: https://github.com/bytedance/deer-flow/tree/main/skills/public +--- + +# Deep Research Skill + +## Overview + +This skill provides a systematic methodology for conducting thorough web research. **Load this skill BEFORE starting any content generation task** to ensure you gather sufficient information from multiple angles, depths, and sources. + +## When to Use This Skill + +**Always load this skill when:** + +### Research Questions +- User asks "what is X", "explain X", "research X", "investigate X" +- User wants to understand a concept, technology, or topic in depth +- The question requires current, comprehensive information from multiple sources +- A single web search would be insufficient to answer properly + +### Content Generation (Pre-research) +- Creating presentations (PPT/slides) +- Creating frontend designs or UI mockups +- Writing articles, reports, or documentation +- Producing videos or multimedia content +- Any content that requires real-world information, examples, or current data + +## Core Principle + +**Never generate content based solely on general knowledge.** The quality of your output directly depends on the quality and quantity of research conducted beforehand. A single search query is NEVER enough. + +## Research Methodology + +### Phase 1: Broad Exploration + +Start with broad searches to understand the landscape: + +1. **Initial Survey**: Search for the main topic to understand the overall context +2. **Identify Dimensions**: From initial results, identify key subtopics, themes, angles, or aspects that need deeper exploration +3. **Map the Territory**: Note different perspectives, stakeholders, or viewpoints that exist + +Example: +``` +Topic: "AI in healthcare" +Initial searches: +- "AI healthcare applications 2024" +- "artificial intelligence medical diagnosis" +- "healthcare AI market trends" + +Identified dimensions: +- Diagnostic AI (radiology, pathology) +- Treatment recommendation systems +- Administrative automation +- Patient monitoring +- Regulatory landscape +- Ethical considerations +``` + +### Phase 2: Deep Dive + +For each important dimension identified, conduct targeted research: + +1. **Specific Queries**: Search with precise keywords for each subtopic +2. **Multiple Phrasings**: Try different keyword combinations and phrasings +3. **Fetch Full Content**: Use `web_fetch` to read important sources in full, not just snippets +4. **Follow References**: When sources mention other important resources, search for those too + +Example: +``` +Dimension: "Diagnostic AI in radiology" +Targeted searches: +- "AI radiology FDA approved systems" +- "chest X-ray AI detection accuracy" +- "radiology AI clinical trials results" + +Then fetch and read: +- Key research papers or summaries +- Industry reports +- Real-world case studies +``` + +### Phase 3: Diversity & Validation + +Ensure comprehensive coverage by seeking diverse information types: + +| Information Type | Purpose | Example Searches | +|-----------------|---------|------------------| +| **Facts & Data** | Concrete evidence | "statistics", "data", "numbers", "market size" | +| **Examples & Cases** | Real-world applications | "case study", "example", "implementation" | +| **Expert Opinions** | Authority perspectives | "expert analysis", "interview", "commentary" | +| **Trends & Predictions** | Future direction | "trends 2024", "forecast", "future of" | +| **Comparisons** | Context and alternatives | "vs", "comparison", "alternatives" | +| **Challenges & Criticisms** | Balanced view | "challenges", "limitations", "criticism" | + +### Phase 4: Synthesis Check + +Before proceeding to content generation, verify: + +- [ ] Have I searched from at least 3-5 different angles? +- [ ] Have I fetched and read the most important sources in full? +- [ ] Do I have concrete data, examples, and expert perspectives? +- [ ] Have I explored both positive aspects and challenges/limitations? +- [ ] Is my information current and from authoritative sources? + +**If any answer is NO, continue researching before generating content.** + +## Search Strategy Tips + +### Effective Query Patterns + +``` +# Be specific with context +❌ "AI trends" +✅ "enterprise AI adoption trends 2024" + +# Include authoritative source hints +"[topic] research paper" +"[topic] McKinsey report" +"[topic] industry analysis" + +# Search for specific content types +"[topic] case study" +"[topic] statistics" +"[topic] expert interview" + +# Use temporal qualifiers — always use the ACTUAL current year from +"[topic] 2026" # ← replace with real current year, never hardcode a past year +"[topic] latest" +"[topic] recent developments" +``` + +### Temporal Awareness + +**Always check `` in your context before forming ANY search query.** + +`` gives you the full date: year, month, day, and weekday (e.g. `2026-02-28, Saturday`). Use the right level of precision depending on what the user is asking: + +| User intent | Temporal precision needed | Example query | +|---|---|---| +| "today / this morning / just released" | **Month + Day** | `"tech news February 28 2026"` | +| "this week" | **Week range** | `"technology releases week of Feb 24 2026"` | +| "recently / latest / new" | **Month** | `"AI breakthroughs February 2026"` | +| "this year / trends" | **Year** | `"software trends 2026"` | + +**Rules:** +- When the user asks about "today" or "just released", use **month + day + year** in your search queries to get same-day results +- Never drop to year-only when day-level precision is needed — `"tech news 2026"` will NOT surface today's news +- Try multiple phrasings: numeric form (`2026-02-28`), written form (`February 28 2026`), and relative terms (`today`, `this week`) across different queries + +❌ User asks "what's new in tech today" → searching `"new technology 2026"` → misses today's news +✅ User asks "what's new in tech today" → searching `"new technology February 28 2026"` + `"tech news today Feb 28"` → gets today's results + +### When to Use web_fetch + +Use `web_fetch` to read full content when: +- A search result looks highly relevant and authoritative +- You need detailed information beyond the snippet +- The source contains data, case studies, or expert analysis +- You want to understand the full context of a finding + +### Iterative Refinement + +Research is iterative. After initial searches: +1. Review what you've learned +2. Identify gaps in your understanding +3. Formulate new, more targeted queries +4. Repeat until you have comprehensive coverage + +## Quality Bar + +Your research is sufficient when you can confidently answer: +- What are the key facts and data points? +- What are 2-3 concrete real-world examples? +- What do experts say about this topic? +- What are the current trends and future directions? +- What are the challenges or limitations? +- What makes this topic relevant or important now? + +## Common Mistakes to Avoid + +- ❌ Stopping after 1-2 searches +- ❌ Relying on search snippets without reading full sources +- ❌ Searching only one aspect of a multi-faceted topic +- ❌ Ignoring contradicting viewpoints or challenges +- ❌ Using outdated information when current data exists +- ❌ Starting content generation before research is complete + +## Output + +After completing research, you should have: +1. A comprehensive understanding of the topic from multiple angles +2. Specific facts, data points, and statistics +3. Real-world examples and case studies +4. Expert perspectives and authoritative sources +5. Current trends and relevant context + +**Only then proceed to content generation**, using the gathered information to create high-quality, well-informed content. diff --git a/libs/hexagent_demo/backend/skills/public/doc/LICENSE.txt b/libs/hexagent_demo/backend/skills/public/doc/LICENSE.txt new file mode 100644 index 00000000..13e25df8 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/doc/LICENSE.txt @@ -0,0 +1,201 @@ +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + +Copyright [yyyy] [name of copyright owner] + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. diff --git a/libs/hexagent_demo/backend/skills/public/doc/SKILL.md b/libs/hexagent_demo/backend/skills/public/doc/SKILL.md new file mode 100644 index 00000000..b31f0312 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/doc/SKILL.md @@ -0,0 +1,83 @@ +--- +name: "doc" +description: "Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks." +metadata: + author: openai + url: https://github.com/openai/skills/tree/main/skills/.curated +--- + + +# DOCX Skill + +## When to use +- Read or review DOCX content where layout matters (tables, diagrams, pagination). +- Create or edit DOCX files with professional formatting. +- Validate visual layout before delivery. + +## Workflow +1. Prefer visual review (layout, tables, diagrams). + - If `soffice` and `pdftoppm` are available, convert DOCX -> PDF -> PNGs. + - Or use `scripts/render_docx.py` (requires `pdf2image` and Poppler). + - If these tools are missing, install them or ask the user to review rendered pages locally. +2. Use `python-docx` for edits and structured creation (headings, styles, tables, lists). +3. After each meaningful change, re-render and inspect the pages. +4. If visual review is not possible, extract text with `python-docx` as a fallback and call out layout risk. +5. Keep intermediate outputs organized and clean up after final approval. + +## Temp and output conventions +- Use `tmp/docs/` for intermediate files; delete when done. +- Write final artifacts under `output/doc/` when working in this repo. +- Keep filenames stable and descriptive. + +## Dependencies (install if missing) +Prefer `uv` for dependency management. + +Python packages: +``` +uv pip install python-docx pdf2image +``` +If `uv` is unavailable: +``` +python3 -m pip install python-docx pdf2image +``` +System tools (for rendering): +``` +# macOS (Homebrew) +brew install libreoffice poppler + +# Ubuntu/Debian +sudo apt-get install -y libreoffice poppler-utils +``` + +If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally. + +## Environment +No required environment variables. + +## Rendering commands +DOCX -> PDF: +``` +soffice -env:UserInstallation=file:///tmp/lo_profile_$$ --headless --convert-to pdf --outdir $OUTDIR $INPUT_DOCX +``` + +PDF -> PNGs: +``` +pdftoppm -png $OUTDIR/$BASENAME.pdf $OUTDIR/$BASENAME +``` + +Bundled helper: +``` +python3 scripts/render_docx.py /path/to/file.docx --output_dir /tmp/docx_pages +``` + +## Quality expectations +- Deliver a client-ready document: consistent typography, spacing, margins, and clear hierarchy. +- Avoid formatting defects: clipped/overlapping text, broken tables, unreadable characters, or default-template styling. +- Charts, tables, and visuals must be legible in rendered pages with correct alignment. +- Use ASCII hyphens only. Avoid U+2011 (non-breaking hyphen) and other Unicode dashes. +- Citations and references must be human-readable; never leave tool tokens or placeholder strings. + +## Final checks +- Re-render and inspect every page at 100% zoom before final delivery. +- Fix any spacing, alignment, or pagination issues and repeat the render loop. +- Confirm there are no leftovers (temp files, duplicate renders) unless the user asks to keep them. diff --git a/libs/hexagent_demo/backend/skills/public/doc/agents/openai.yaml b/libs/hexagent_demo/backend/skills/public/doc/agents/openai.yaml new file mode 100644 index 00000000..27ce451b --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/doc/agents/openai.yaml @@ -0,0 +1,6 @@ +interface: + display_name: "Word Docs" + short_description: "Edit and review docx files" + icon_small: "./assets/doc-small.svg" + icon_large: "./assets/doc.png" + default_prompt: "Edit or review this .docx file and return the updated file plus a concise change summary." diff --git a/libs/hexagent_demo/backend/skills/public/doc/assets/doc-small.svg b/libs/hexagent_demo/backend/skills/public/doc/assets/doc-small.svg new file mode 100644 index 00000000..97289eb2 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/doc/assets/doc-small.svg @@ -0,0 +1,3 @@ + + + diff --git a/libs/hexagent_demo/backend/skills/public/doc/assets/doc.png b/libs/hexagent_demo/backend/skills/public/doc/assets/doc.png new file mode 100644 index 0000000000000000000000000000000000000000..e16517899921ddc1e7691226014b7ef0256c4d54 GIT binary patch literal 1211 zcmeAS@N?(olHy`uVBq!ia0vp^DIm``W z$lZxy-8q?;Kn_c~qpu?a!^VE@KZ&eBZh)tYV@L(#+qpaao;V1!Rqx0bYGGmIRa#{^8?C!Lsu5l}l6jH%$2O;e&&!a+A^BJ9k>npFe-VD@?J1 zNnTz)^j1g6jio8VP24UK8O$6j*92|iILNxq)vYDeOHA=i;wx*3r5&vc?rK;b(B_>j zvT?%p?b|Pu%~;aWvSn|X&mkpOm6o0M^O>4OCJG!oIA0`N^Q6-jHBQ|PQ*u{`!n$jHo(fODecLum-9 z*I&0znldSATFkLW?Wa$l&QkS?6%!Xf{P1C7M0E7*U)v-81y`+M(M(8AR(^8Gg(GFo zym@Am1b6P*#ig#UewAy||3=eD&Hwu~cP^dLvgY&W&rfEze%8~|TlP=3WeQ*P#5oU7 zyKrQAy!@=l9JHlDWX<16NlGbEJ5HAVyL4$%lrG~0rL+7qIV`QLR$Vpt&poI8^XrDT z+R94HjK-29moEoTxZqu@D|OT9q?d5Z+}E#PX9dQ_1{m}4@vXWSCS0&MAg-4)(1zvr z@82i8_nd9XXbx!l)8-b$dpdOE32WAOQ;$m?6z-nQV)$a^Lvi=cC}qk2XL=@dxb0So zJoC0V5;v%j3WW;7%5m1?_VmWbALLYCcv!t$p@S$@) zoQZ2B<2Pz8?wqi9@7@D_p^|5XLQZ6FXxenux9RCI6Zs~#kXiBPd8;B<-aNx$w###F zpxNBI^MxN{53{#n+6qjg2C@?O?%oaTyHZ|O)+DOtWH7m^tSpQ(k;SR6zh8R2;<-l8 z6Hdz}gt9r@oN#f=0T+(VJturrSLir72Cq@G^=*mJRmf-x-FHk!zG=dRFIzKsAFUGh zJQgsCf96c_GLwlM9~%`VPdeSO|DDkJr1VXSV(#yvUbRWplWWxO{V&t3SN?lu(u=;V zea!d7mL%&;oM6WDVT)(2td){bQ`=qX@AnmwJPz;JA((Oc`gxOx*jV16BTg4OJXdFm zH}uHNouhMC#m77&uk{GqI$QU*3^#wRojrTD@lD=irjKuJ{=0tyr$|nAcJ{I*3(}tK zd-mky(f0?^^iE7p{ None: + missing: list[str] = [] + for tool in ("soffice", "pdftoppm"): + if which(tool) is None: + missing.append(tool) + if missing: + tools = ", ".join(missing) + raise RuntimeError( + f"Missing required system tool(s): {tools}. Install LibreOffice and Poppler, then retry." + ) + + +def calc_dpi_via_ooxml_docx(input_path: str, max_w_px: int, max_h_px: int) -> int: + """Calculate DPI from OOXML `word/document.xml` page size (w:pgSz in twips). + + DOCX stores page dimensions in section properties as twips (1/1440 inch). + We read the first encountered section's page size and compute an isotropic DPI + that fits within the target max pixel dimensions. + """ + with ZipFile(input_path, "r") as zf: + xml = zf.read("word/document.xml") + root = ET.fromstring(xml) + ns = {"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"} + + # Common placements: w:body/w:sectPr or w:body/w:p/w:pPr/w:sectPr + sect_pr = root.find(".//w:sectPr", ns) + if sect_pr is None: + raise RuntimeError("Section properties not found in document.xml") + pg_sz = sect_pr.find("w:pgSz", ns) + if pg_sz is None: + raise RuntimeError("Page size not found in section properties") + + # Values are in twips + w_twips_str = pg_sz.get( + "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}w" + ) or pg_sz.get("w") + h_twips_str = pg_sz.get( + "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" + ) or pg_sz.get("h") + + if not w_twips_str or not h_twips_str: + raise RuntimeError("Page size attributes missing in pgSz") + + width_in = int(w_twips_str) / TWIPS_PER_INCH + height_in = int(h_twips_str) / TWIPS_PER_INCH + if width_in <= 0 or height_in <= 0: + raise RuntimeError("Invalid page size values in document.xml") + return round(min(max_w_px / width_in, max_h_px / height_in)) + + +def calc_dpi_via_pdf(input_path: str, max_w_px: int, max_h_px: int) -> int: + """Convert input to PDF and compute DPI from its page size.""" + with tempfile.TemporaryDirectory(prefix="soffice_profile_") as user_profile: + with tempfile.TemporaryDirectory(prefix="soffice_convert_") as convert_tmp_dir: + stem = splitext(basename(input_path))[0] + pdf_path = convert_to_pdf(input_path, user_profile, convert_tmp_dir, stem) + if not (pdf_path and exists(pdf_path)): + raise RuntimeError("Failed to convert input to PDF for DPI computation.") + + info = pdfinfo_from_path(pdf_path) + size_val = info.get("Page size") + if not size_val: + for k, v in info.items(): + if isinstance(v, str) and "size" in k.lower() and "pts" in v: + size_val = v + break + if not isinstance(size_val, str): + raise RuntimeError("Failed to read PDF page size for DPI computation.") + + m = re.search(r"(\d+)\s*x\s*(\d+)\s*pts", size_val) + if not m: + raise RuntimeError("Unrecognized PDF page size format.") + width_pts = int(m.group(1)) + height_pts = int(m.group(2)) + width_in = width_pts / 72.0 + height_in = height_pts / 72.0 + if width_in <= 0 or height_in <= 0: + raise RuntimeError("Invalid PDF page size values.") + return round(min(max_w_px / width_in, max_h_px / height_in)) + + +def run_cmd_no_check(cmd: list[str]) -> None: + subprocess.run( + cmd, + check=False, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + env=os.environ.copy(), + ) + + +def convert_to_pdf( + doc_path: str, + user_profile: str, + convert_tmp_dir: str, + stem: str, +) -> str: + # Try direct DOC(X) -> PDF + cmd_pdf = [ + "soffice", + "-env:UserInstallation=file://" + user_profile, + "--invisible", + "--headless", + "--norestore", + "--convert-to", + "pdf", + "--outdir", + convert_tmp_dir, + doc_path, + ] + run_cmd_no_check(cmd_pdf) + + pdf_path = join(convert_tmp_dir, f"{stem}.pdf") + if exists(pdf_path): + return pdf_path + + # Fallback: DOCX -> ODT, then ODT -> PDF + cmd_odt = [ + "soffice", + "-env:UserInstallation=file://" + user_profile, + "--invisible", + "--headless", + "--norestore", + "--convert-to", + "odt", + "--outdir", + convert_tmp_dir, + doc_path, + ] + run_cmd_no_check(cmd_odt) + + odt_path = join(convert_tmp_dir, f"{stem}.odt") + + if exists(odt_path): + cmd_odt_pdf = [ + "soffice", + "-env:UserInstallation=file://" + user_profile, + "--invisible", + "--headless", + "--norestore", + "--convert-to", + "pdf", + "--outdir", + convert_tmp_dir, + odt_path, + ] + run_cmd_no_check(cmd_odt_pdf) + if exists(pdf_path): + return pdf_path + + return "" + + +def rasterize( + doc_path: str, + out_dir: str, + dpi: int, +) -> Sequence[str]: + """Rasterise DOCX (or similar) to images placed in out_dir and return their paths. + + Images are named as page-. with pages starting at 1. + """ + makedirs(out_dir, exist_ok=True) + doc_path = abspath(doc_path) + stem = splitext(basename(doc_path))[0] + + # Use a unique user profile to avoid LibreOffice profile lock when running concurrently + with tempfile.TemporaryDirectory(prefix="soffice_profile_") as user_profile: + # Write conversion outputs into a temp directory to avoid any IO oddities + with tempfile.TemporaryDirectory(prefix="soffice_convert_") as convert_tmp_dir: + pdf_path = convert_to_pdf( + doc_path, + user_profile, + convert_tmp_dir, + stem, + ) + + if not pdf_path or not exists(pdf_path): + raise RuntimeError( + "Failed to produce PDF for rasterization (direct and ODT fallback)." + ) + paths_raw = cast( + list[str], + convert_from_path( + pdf_path, + dpi=dpi, + fmt="png", + thread_count=8, + output_folder=out_dir, + paths_only=True, + output_file="page", + ), + ) + + # Rename convert_from_path's output format f'page{thread_id:04d}-{page_num:02d}.' to 'page-.' + pages: list[tuple[int, str]] = [] + for src_path in paths_raw: + base = splitext(basename(src_path))[0] + page_num_str = base.split("-")[-1] + page_num = int(page_num_str) + dst_path = join(out_dir, f"page-{page_num}.png") + replace(src_path, dst_path) + pages.append((page_num, dst_path)) + pages.sort(key=lambda t: t[0]) + final_paths = [path for _, path in pages] + return final_paths + + +def main() -> None: + parser = argparse.ArgumentParser(description="Render DOCX-like file to PNG images.") + parser.add_argument( + "input_path", + type=str, + help="Path to the input DOCX file (or compatible).", + ) + parser.add_argument( + "--output_dir", + type=str, + default=None, + help=( + "Output directory for the rendered images. " + "Defaults to a folder next to the input named after the input file (without extension)." + ), + ) + parser.add_argument( + "--width", + type=int, + default=1600, + help=( + "Approximate maximum width in pixels after isotropic scaling (default 1600). " + "The actual value may exceed slightly." + ), + ) + parser.add_argument( + "--height", + type=int, + default=2000, + help=( + "Approximate maximum height in pixels after isotropic scaling (default 2000). " + "The actual value may exceed slightly." + ), + ) + parser.add_argument( + "--dpi", + type=int, + default=None, + help=("Override computed DPI. If provided, skips DOCX/PDF-based DPI calculation."), + ) + args = parser.parse_args() + + try: + ensure_system_tools() + + input_path = abspath(expanduser(args.input_path)) + out_dir = ( + abspath(expanduser(args.output_dir)) if args.output_dir else splitext(input_path)[0] + ) + + if args.dpi is not None: + dpi = int(args.dpi) + else: + try: + if input_path.lower().endswith((".docx", ".docm", ".dotx", ".dotm")): + dpi = calc_dpi_via_ooxml_docx(input_path, args.width, args.height) + else: + raise RuntimeError("Skip OOXML DPI; not a DOCX container") + except Exception: + dpi = calc_dpi_via_pdf(input_path, args.width, args.height) + + rasterize(input_path, out_dir, dpi) + print("Pages rendered to " + out_dir) + except RuntimeError as exc: + print(f"Error: {exc}", file=sys.stderr) + raise SystemExit(1) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/excel-xlsx/SKILL.md b/libs/hexagent_demo/backend/skills/public/excel-xlsx/SKILL.md new file mode 100644 index 00000000..9fef55e8 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/excel-xlsx/SKILL.md @@ -0,0 +1,102 @@ +--- +name: excel-xlsx +version: 1.0.2 +homepage: https://clawic.com/skills/excel-xlsx +description: "Create, inspect, and edit Microsoft Excel workbooks and XLSX files with reliable formulas, dates, types, formatting, recalculation, and template preservation. Use when (1) the task is about Excel, `.xlsx`, `.xlsm`, `.xls`, `.csv`, or `.tsv`; (2) formulas, formatting, workbook structure, or compatibility matter; (3) the file must stay reliable after edits." +changelog: Tightened formula anchoring, recalculation, and model traceability after a stricter external spreadsheet audit. +metadata: {"clawdbot":{"emoji":"📗","requires":{"bins":[]},"os":["linux","darwin","win32"]}} +--- + +## When to Use + +Use when the main artifact is a Microsoft Excel workbook or spreadsheet file, especially when formulas, dates, formatting, merged cells, workbook structure, or cross-platform behavior matter. + +## Core Rules + +### 1. Choose the workflow by job, not by habit + +- Use `pandas` for analysis, reshaping, and CSV-like tasks. +- Use `openpyxl` when formulas, styles, sheets, comments, merged cells, or workbook preservation matter. +- Treat CSV as plain data exchange, not as an Excel feature-complete format. +- Reading values, preserving a live workbook, and building a model from scratch are different spreadsheet jobs. + +### 2. Dates are serial numbers with legacy quirks + +- Excel stores dates as serial numbers, not real date objects. +- The 1900 date system includes the false leap-day bug, and some workbooks use the 1904 system. +- Time is fractional day data, so formatting and conversion both matter. +- Date correctness is not enough if the number format still displays the wrong thing to the user. + +### 3. Keep calculations in Excel when the workbook should stay live + +- Write formulas into cells instead of hardcoding derived results from Python. +- Use references to assumption cells instead of magic numbers inside formulas. +- Cached formula values can be stale, so do not trust them blindly after edits. +- Check copied formulas for wrong ranges, wrong sheets, and silent off-by-one drift before delivery. +- Absolute and relative references are part of the logic, so copied formulas can be wrong even when they still "work". +- Test new formulas on a few representative cells before filling them across a whole block. +- Verify denominators, named ranges, and precedent cells before shipping formulas that depend on them. +- A workbook should ship with zero formula errors, not with known `#REF!`, `#DIV/0!`, `#VALUE!`, `#NAME?`, or circular-reference fallout left for the user to fix. +- For model-style work, document non-obvious hardcodes, assumptions, or source inputs in comments or nearby notes. + +### 4. Protect data types before Excel mangles them + +- Long identifiers, phone numbers, ZIP codes, and leading-zero values should usually be stored as text. +- Excel silently truncates numeric precision past 15 digits. +- Mixed text-number columns need explicit handling on read and on write. +- Scientific notation, auto-parsed dates, and stripped leading zeros are common corruption, not cosmetic issues. + +### 5. Preserve workbook structure before changing content + +- Existing templates override generic styling advice. +- Only the top-left cell of a merged range stores the value. +- Hidden rows, hidden columns, named ranges, and external references can still affect formulas and outputs. +- Shared strings, defined names, and sheet-level conventions can matter even when the visible cells look simple. +- Match styles for newly filled cells instead of quietly introducing a new visual system. +- If the workbook is a template, preserve sheet order, widths, freezes, filters, print settings, validations, and visual conventions unless the task explicitly changes them. +- Conditional formatting, filters, print areas, and data validation often carry business meaning even when users only mention the numbers. +- If there is no existing style guide and the file is a model, keep editable inputs visually distinguishable from formulas, but never override an established template to force a generic house style. + +### 6. Recalculate and review before delivery + +- Formula strings alone are not enough if the recipient needs current values. +- `openpyxl` preserves formulas but does not calculate them. +- Verify no `#REF!`, `#DIV/0!`, `#VALUE!`, `#NAME?`, or circular-reference fallout remains. +- If layout matters, render or visually review the workbook before calling it finished. +- Be careful with read modes: opening a workbook for values only and then saving can flatten formulas into static values. +- If assumptions or hardcoded overrides must stay, make them obvious enough that the next editor can audit the workbook. + +### 7. Scale the workflow to the file size + +- Large workbooks can fail for boring reasons: memory spikes, padded empty rows, and slow full-sheet reads. +- Use streaming or chunked reads when the file is big enough that loading everything at once becomes fragile. +- Large-file workflows also need narrower reads, explicit dtypes, and sheet targeting to avoid accidental damage. + +## Common Traps + +- Type inference on read can leave numbers as text or convert IDs into damaged numeric values. +- Column indexing varies across tools, so off-by-one mistakes are common in generated formulas. +- Newlines in cells need wrapping to display correctly. +- External references break easily when source files move. +- Password protection in old Excel workflows is not serious security. +- `.xlsm` can contain macros, and `.xls` remains a tighter legacy format. +- Large files may need streaming reads or more careful memory handling. +- Google Sheets and LibreOffice can reinterpret dates, formulas, or styling differently from Excel. +- Dynamic array or newer Excel functions like `FILTER`, `XLOOKUP`, `SORT`, or `SEQUENCE` may fail or degrade in older viewers. +- A workbook can look fine while still carrying stale cached values from a prior recalculation. +- Saving the wrong workbook view can replace formulas with cached values and quietly destroy a live model. +- Copying formulas without checking relative references can push one bad range across an entire block. +- Hidden sheets, named ranges, validations, and merged areas often keep business logic that is invisible in a quick skim. +- A workbook can appear numerically correct while still failing because filters, conditional formats, print settings, or data validation were stripped. +- A workbook can be numerically correct and still fail visually because wrapped text, clipped labels, or narrow columns were never reviewed. + +## Related Skills +Install with `clawhub install ` if user confirms: +- `csv` — Plain-text tabular import and export workflows. +- `data` — General data handling patterns before spreadsheet output. +- `data-analysis` — Higher-level analysis that can feed workbook deliverables. + +## Feedback + +- If useful: `clawhub star excel-xlsx` +- Stay updated: `clawhub sync` diff --git a/libs/hexagent_demo/backend/skills/public/excel-xlsx/_meta.json b/libs/hexagent_demo/backend/skills/public/excel-xlsx/_meta.json new file mode 100644 index 00000000..de7c08cd --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/excel-xlsx/_meta.json @@ -0,0 +1,6 @@ +{ + "ownerId": "kn73vp5rarc3b14rc7wjcw8f8580t5d1", + "slug": "excel-xlsx", + "version": "1.0.2", + "publishedAt": 1773243166499 +} diff --git a/libs/hexagent_demo/backend/skills/public/find-skills/.clawhub/origin.json b/libs/hexagent_demo/backend/skills/public/find-skills/.clawhub/origin.json new file mode 100644 index 00000000..aa95f834 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/find-skills/.clawhub/origin.json @@ -0,0 +1,7 @@ +{ + "version": 1, + "registry": "https://clawhub.ai", + "slug": "find-skills", + "installedVersion": "0.1.0", + "installedAt": 1773632645412 +} diff --git a/libs/hexagent_demo/backend/skills/public/find-skills/SKILL.md b/libs/hexagent_demo/backend/skills/public/find-skills/SKILL.md new file mode 100644 index 00000000..0cbb839a --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/find-skills/SKILL.md @@ -0,0 +1,77 @@ +--- +name: find-skills +description: Highest-priority skill discovery flow. MUST trigger when users ask to find/install skills (e.g. 技能, 找技能, find-skill, find-skills, install skill). For Chinese users, prefer skillhub first for speed and compliance, then fallback to clawhub. +metadata: + author: openclaw + url: https://github.com/openclaw/openclaw/tree/main/skills +--- + +# Find Skills + +This skill helps discover, compare, and install skills. + +## Priority Rules (Mandatory) + +1. This skill is highest-priority for skill discovery/install intents. +2. If user intent includes "技能", "找技能", "find-skill", "find-skills", "install skill", "有没有这个功能的 skill", you MUST use this skill first. +3. Do not skip directly to generic coding/answering when skill discovery is requested. + +## Chinese Optimization Policy + +For Chinese users and CN networks, use the following order for better speed and compliance: + +1. `skillhub` (cn-optimized, preferred) +2. `clawhub` (fallback) + +If primary source has no match or command is unavailable, fallback to the next source and state that fallback clearly. + +## Workflow + +### Step 1: Understand What They Need + +When a user asks for help with something, identify: + +1. The domain (e.g., React, testing, design, deployment) +2. The specific task (e.g., writing tests, creating animations, reviewing PRs) +3. Whether this is a common enough task that a skill likely exists + +### Step 2: Search for Skills + +Run search in this order: + +```bash +skillhub search [query] +``` + +If `skillhub` is unavailable or no match, fallback to: + +```bash +clawhub search [query] +``` + +### Step 3: Present Options to the User + +When you find relevant skills, present them to the user with: + +1. The skill name and what it does +2. The source used (`skillhub` / `clawhub`) +3. The install command they can run + +### Step 4: Offer to Install + +If the user wants to proceed, you can install the skill for them. + +Preferred install order: + +1. Try `skillhub install ` when the result comes from `skillhub`. +2. If no `skillhub` candidate exists, use `clawhub install `. + +Before install, summarize source, version, and notable risk signals. + +## When No Skills Are Found + +If no relevant skills exist: + +1. Acknowledge that no existing skill was found +2. Offer to help with the task directly using your general capabilities +3. Suggest creating a custom local skill in the workspace if this is a recurring need diff --git a/libs/hexagent_demo/backend/skills/public/find-skills/_meta.json b/libs/hexagent_demo/backend/skills/public/find-skills/_meta.json new file mode 100644 index 00000000..90d2ac88 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/find-skills/_meta.json @@ -0,0 +1,6 @@ +{ + "ownerId": "kn77ajmmqw3cgnc3ay1x3e0ccd805hsw", + "slug": "find-skills", + "version": "0.1.0", + "publishedAt": 1769698710765 +} diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/SKILL.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/SKILL.md new file mode 100644 index 00000000..88569725 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/SKILL.md @@ -0,0 +1,567 @@ +--- +name: frontend-dev +description: | + Full-stack frontend development combining premium UI design, cinematic animations, + AI-generated media assets, persuasive copywriting, and visual art. Builds complete, + visually striking web pages with real media, advanced motion, and compelling copy. + Use when: building landing pages, marketing sites, product pages, dashboards, + generating media assets (image/video/audio/music), writing conversion copy, + creating generative art, or implementing cinematic scroll animations. +license: MIT +metadata: + version: "1.0.0" + category: frontend + sources: + - Framer Motion documentation + - GSAP / GreenSock documentation + - Three.js documentation + - Tailwind CSS documentation + - React / Next.js documentation + - AIDA Framework (Elmo Lewis) + - p5.js documentation +--- + +# Frontend Studio + +Build complete, production-ready frontend pages by orchestrating 5 specialized capabilities: design engineering, motion systems, AI-generated assets, persuasive copy, and generative art. + +## Invocation + +``` +/frontend-dev +``` + +The user provides their request as natural language (e.g. "build a landing page for a music streaming app"). + +## Skill Structure + +``` +frontend-dev/ +├── SKILL.md # Core skill (this file) +├── scripts/ # Asset generation scripts +│ ├── minimax_tts.py # Text-to-speech +│ ├── minimax_music.py # Music generation +│ ├── minimax_video.py # Video generation (async) +│ └── minimax_image.py # Image generation +├── references/ # Detailed guides (read as needed) +│ ├── minimax-cli-reference.md # CLI flags quick reference +│ ├── asset-prompt-guide.md # Asset prompt engineering rules +│ ├── minimax-tts-guide.md # TTS usage & voices +│ ├── minimax-music-guide.md # Music prompts & lyrics format +│ ├── minimax-video-guide.md # Camera commands & models +│ ├── minimax-image-guide.md # Ratios & batch generation +│ ├── minimax-voice-catalog.md # All voice IDs +│ ├── motion-recipes.md # Animation code snippets +│ ├── env-setup.md # Environment setup +│ └── troubleshooting.md # Common issues +├── templates/ # Visual art templates +│ ├── viewer.html # p5.js interactive art base +│ └── generator_template.js # p5.js code reference +└── canvas-fonts/ # Static art fonts (TTF + licenses) +``` + +## Project Structure + +### Assets (Universal) + +All frameworks use the same asset organization: + +``` +assets/ +├── images/ +│ ├── hero-landing-1710xxx.webp +│ ├── icon-feature-01.webp +│ └── bg-pattern.svg +├── videos/ +│ ├── hero-bg-1710xxx.mp4 +│ └── demo-preview.mp4 +└── audio/ + ├── bgm-ambient-1710xxx.mp3 + └── tts-intro-1710xxx.mp3 +``` + +**Asset naming:** `{type}-{descriptor}-{timestamp}.{ext}` + +### By Framework + +| Framework | Asset Location | Component Location | +|-----------|---------------|-------------------| +| **Pure HTML** | `./assets/` | N/A (inline or `./js/`) | +| **React/Next.js** | `public/assets/` | `src/components/` | +| **Vue/Nuxt** | `public/assets/` | `src/components/` | +| **Svelte/SvelteKit** | `static/assets/` | `src/lib/components/` | +| **Astro** | `public/assets/` | `src/components/` | + +### Pure HTML + +``` +project/ +├── index.html +├── assets/ +│ ├── images/ +│ ├── videos/ +│ └── audio/ +├── css/ +│ └── styles.css +└── js/ + └── main.js # Animations (GSAP/vanilla) +``` + +### React / Next.js + +``` +project/ +├── public/assets/ # Static assets +├── src/ +│ ├── components/ +│ │ ├── ui/ # Button, Card, Input +│ │ ├── sections/ # Hero, Features, CTA +│ │ └── motion/ # RevealSection, StaggerGrid +│ ├── lib/ +│ ├── styles/ +│ └── app/ # Pages +└── package.json +``` + +### Vue / Nuxt + +``` +project/ +├── public/assets/ +├── src/ # or root for Nuxt +│ ├── components/ +│ │ ├── ui/ +│ │ ├── sections/ +│ │ └── motion/ +│ ├── composables/ # Shared logic +│ ├── pages/ +│ └── assets/ # Processed assets (optional) +└── package.json +``` + +### Astro + +``` +project/ +├── public/assets/ +├── src/ +│ ├── components/ # .astro, .tsx, .vue, .svelte +│ ├── layouts/ +│ ├── pages/ +│ └── styles/ +└── package.json +``` + +**Component naming:** PascalCase (`HeroSection.tsx`, `HeroSection.vue`, `HeroSection.astro`) + +--- + +## Compliance + +**All rules in this skill are mandatory. Violating any rule is a blocking error — fix before proceeding or delivering.** + +--- + +## Workflow +### Phase 1: Design Architecture +1. Analyze the request — determine page type and context +2. Set design dials based on page type +3. Plan layout sections and identify asset needs + +### Phase 2: Motion Architecture +1. Select animation tools per section (see Tool Selection Matrix) +2. Plan motion sequences following performance guardrails + +### Phase 3: Asset Generation +Generate all image/video/audio assets using `scripts/`. NEVER use placeholder URLs (unsplash, picsum, placeholder.com, via.placeholder, placehold.co, etc.) or external URLs. + +1. Parse asset requirements (type, style, spec, usage) +2. Craft optimized prompts, show to user, confirm before generating +3. Execute via scripts, save to project — do NOT proceed to Phase 5 until all assets are saved locally + +### Phase 4: Copywriting & Content +Follow copywriting frameworks (AIDA, PAS, FAB) to craft all text content. Do NOT use "Lorem ipsum" — write real copy. + +### Phase 5: Build UI +Scaffold the project and build each section following Design and Motion rules. Integrate generated assets and copy. 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(https://github.com/Fonthausen/CrimsonPro) + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/CrimsonPro-Regular.ttf b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/CrimsonPro-Regular.ttf new file mode 100644 index 0000000000000000000000000000000000000000..f5666b9beb8fb808ee56e78726a5b754e67d1ae7 GIT binary patch literal 106696 zcmd3P2Ygh;_W#W6X44BHBq4#Ygb*S%1rj=>(u?#CAqAo#;e`N#Vi(22^Vy#wq98U@ ztPina@7NGg5g`_M8WoTtqU`^B&dlAtn}Yaz|M&m@c0cFdbI+VPb7tnunYwp{6hcJd z;uK;?L19tRfx;_k5bE^=ef`qvI)R6HL^ZLzbbFB~^Q-lb2jv3!0 zv)_fYs)Uex!9QpGgxm@HSH2sA=iBf+v}8f?!YNV5$032sg$T-=SG;H;=urpS8R4(heshj9ubMVaO5~gia=2%0_e&1aS|88 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License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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+SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. 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b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/Jura-OFL.txt new file mode 100644 index 00000000..c71a1f0c --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/Jura-OFL.txt @@ -0,0 +1,93 @@ +Copyright 2019 The Jura Project Authors (https://github.com/ossobuffo/jura) + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/LibreBaskerville-OFL.txt b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/LibreBaskerville-OFL.txt new file mode 100644 index 00000000..5804419b --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/LibreBaskerville-OFL.txt @@ -0,0 +1,93 @@ +Copyright 2012 The Libre Baskerville Project Authors (https://github.com/impallari/Libre-Baskerville) with Reserved Font Name Libre Baskerville. + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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(https://github.com/googlefonts/smooch-sans) + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/Tektur-Medium.ttf b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/Tektur-Medium.ttf new file mode 100644 index 0000000000000000000000000000000000000000..34fc797195169923bad8e76181d60ae02019fef0 GIT binary patch literal 76248 zcmc$H34ByVws$SJZ!g&)3ke}~0)!Ak=x6I^_*Lm zP(nx`kVZ&BZeITEz}XuKVQGZWl!B2XM(18T`7j}qb`#<}STK4__TD?+c#@FFg@jm_ zj2PYDb)R1JI^uqWR3?uu%_{w|@v~sKSHqn-WoB9Zbz}U~3F$l+@h#KJ8tX-F2uB=Z znN~Az>bnn4yMvJ1ml3kMxT>rAv79+kd;+uC;&*H7xt#A_R@sI$RM5`uFqLUb660UYXE@C0& zFI(P6-8OgvJ$}}`9pVtJO8QV*7~eAe+erZ#KM}^i6sdf&A^wOkk3D4>if47}Ug@tB 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(https://www.github.com/hyvyys/Tektur) + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/YoungSerif-Regular.ttf b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/YoungSerif-Regular.ttf new file mode 100644 index 0000000000000000000000000000000000000000..f454fbedd4c8b00833d17fffa1f89acb5149b02c GIT binary patch literal 105136 zcmce92Vhi1{{PH-+c(Lk2M8>iY#M2#7YGnGg&smr07*g;AP^D=p^Auz2w2WT@6LjX zp1p3cAvW~Tvz=!<((GV6zPZKX<6R7dD)ox-NzW)mBo1E_7%+yO-TvYyAi(v@dYaoVC9Aj z;V*|jVa4jsO^^Ju+R2y`>8J}8}^VJQT)~Ihd{s#C2z`NQSRyVIa z_qH~~)x%6))4r~A|7GKhjOD+>Sh#UbNAsEsZfbiJ^zH=wbBr_Y^DzgWOxehO$4u-m 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zp%>S4?5_2%p&%ME{J;A>GYjFn-)m+e{I|95u%Y#@fr^`b+q9o;^i37hUx!W!+j<@I zMlQ|_bxuj%)VVv+Hw4sg(KihKU#%lPOUl9T{4d13*oZ0scM%1ADZvAgE-<+FAZDKG zT3x0@U@9yhcm6<#ZjvLAW66-K+uzwllds}fzQOgcS4#wvP&!k3Iq6SmzZ zjS236k&*STPX0pOdRcRnoyv|tsJ)!rH5wRfcWJOtdi(rs(e5PX+$MM05Wl);_4lTF zMs0Sj%dm6J=JH1TluZ=9{Fm!8`$I_1NvR}8orP-+5q?;mWQ`^ZC=>_5Ic_D+aWI=s zW|32^U38UjtaS|-{X&1q(J2_GX@?B5CB>n{x*~;)w=1gZmTl$A&Sdv^6~+p$rdo7= zx;<5NIvqKOk{X!p>>EqDbjs=V@%0Y&9YH6+zP$V0I-Pviq!V2K?e+8Qnf3nwIyxaq zYuvoP#+%n0l8eR{M2@hAw15N?;<&N5Yy991$A`pmV;|M{VR78x=o(+H-~T3LgXiGe z#QoCOB`bWJU-&wjN8dK?MFveAf0Mt-u84aNBKB3wYj`4x~IR*qD1mVzh+llK5F7oo@H6s*n^w6 zRtriYBhsALxmHuJ7er**uKg_QP7cT8!%4R*5Do`iykewB6Ul99Bj@A_#q%nhs@AhC z+WO+Aws2Cga<+o5u*FPogRL test.mp3`. + +## Next steps + +- **Voice selection**: See [minimax-voice-catalog.md](minimax-voice-catalog.md) +- **TTS workflows**: See [minimax-tts-guide.md](minimax-tts-guide.md) +- **Troubleshooting**: See [troubleshooting.md](troubleshooting.md) diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-cli-reference.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-cli-reference.md new file mode 100644 index 00000000..6b6497b4 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-cli-reference.md @@ -0,0 +1,133 @@ +# Provider Reference — MiniMax + +All asset generation uses MiniMax API. Env: `MINIMAX_API_KEY` (required). + +## Audio (Sync TTS) + +**Script:** `scripts/minimax_tts.py` + +```bash +python scripts/minimax_tts.py "Hello world" -o output.mp3 +python scripts/minimax_tts.py "你好" -o hi.mp3 -v female-shaonv +python scripts/minimax_tts.py "Welcome" -o out.wav -v male-qn-jingying --speed 0.8 --format wav +``` + +**Model:** `speech-2.8-hd` (default). + +| Flag | Default | Range / Options | +|------|---------|-----------------| +| `-o` | (required) | Output file path | +| `-v` | `male-qn-qingse` | Voice ID | +| `--model` | `speech-2.8-hd` | speech-2.8-hd / speech-2.8-turbo / speech-2.6-hd / speech-2.6-turbo | +| `--speed` | 1.0 | 0.5–2.0 | +| `--volume` | 1.0 | 0.1–10 | +| `--pitch` | 0 | -12 to 12 | +| `--emotion` | (auto) | happy / sad / angry / fearful / disgusted / surprised / calm / fluent / whisper | +| `--format` | mp3 | mp3 / wav / flac | +| `--lang` | auto | Language boost | + +**Programmatic:** +```python +from minimax_tts import tts +audio_bytes = tts("Hello", voice_id="female-shaonv") +``` + + +## Video (Text-to-Video) + +**Script:** `scripts/minimax_video.py` + +```bash +python scripts/minimax_video.py "A cat playing piano" -o cat.mp4 +python scripts/minimax_video.py "Ocean waves [Truck left]" -o waves.mp4 --duration 10 +python scripts/minimax_video.py "City skyline [Push in]" -o city.mp4 --resolution 1080P +``` + +**Model:** `MiniMax-Hailuo-2.3` (default). Async: script handles create → poll → download automatically. + +| Flag | Default | Options | +|------|---------|---------| +| `-o` | (required) | Output file path (.mp4) | +| `--model` | `MiniMax-Hailuo-2.3` | MiniMax-Hailuo-2.3 / MiniMax-Hailuo-02 / T2V-01-Director / T2V-01 | +| `--duration` | 6 | 6 / 10 (10s only at 768P with Hailuo models) | +| `--resolution` | 768P | 720P / 768P / 1080P (1080P only 6s) | +| `--no-optimize` | false | Disable prompt auto-optimization | +| `--poll-interval` | 10 | Seconds between status checks | +| `--max-wait` | 600 | Max wait time in seconds | + +**Camera commands** — insert `[Command]` in prompt: `[Push in]`, `[Truck left]`, `[Pan right]`, `[Zoom out]`, `[Static shot]`, `[Tracking shot]`, etc. + +**Programmatic:** +```python +from minimax_video import generate +generate("A cat playing piano", "cat.mp4", model="MiniMax-Hailuo-2.3", duration=6) +``` + +See [minimax-video-guide.md](minimax-video-guide.md) for full camera command list and model compatibility. + +## Image (Text-to-Image) + +**Script:** `scripts/minimax_image.py` + +```bash +python scripts/minimax_image.py "A cat astronaut in space" -o cat.png +python scripts/minimax_image.py "Mountain landscape" -o hero.png --ratio 16:9 +python scripts/minimax_image.py "Product icons, flat style" -o icons.png -n 4 --seed 42 +``` + +**Model:** `image-01`. Sync: returns image URL (or base64) immediately. + +| Flag | Default | Options | +|------|---------|---------| +| `-o` | (required) | Output file path (.png/.jpg) | +| `--ratio` | 1:1 | 1:1 / 16:9 / 4:3 / 3:2 / 2:3 / 3:4 / 9:16 / 21:9 | +| `-n` | 1 | Number of images (1–9) | +| `--seed` | (random) | Seed for reproducibility | +| `--optimize` | false | Enable prompt auto-optimization | +| `--base64` | false | Return base64 instead of URL | + +**Batch output:** with `-n > 1`, files are named `out-0.png`, `out-1.png`, etc. + +**Programmatic:** +```python +from minimax_image import generate_image, download_and_save +result = generate_image("A cat in space", aspect_ratio="16:9") +download_and_save(result["data"]["image_urls"][0], "cat.png") +``` + +See [minimax-image-guide.md](minimax-image-guide.md) for ratio dimensions and details. + +## Music (Text-to-Music) + +**Script:** `scripts/minimax_music.py` + +```bash +python scripts/minimax_music.py --prompt "Indie folk, melancholic" --lyrics "[verse]\nStreetlights flicker" -o song.mp3 +python scripts/minimax_music.py --prompt "Upbeat pop, energetic" --auto-lyrics -o pop.mp3 +python scripts/minimax_music.py --prompt "Jazz piano, smooth, relaxing" --instrumental -o jazz.mp3 +``` + +**Model:** `music-2.5+` (default). Sync: returns audio hex or URL. + +| Flag | Default | Options | +|------|---------|---------| +| `-o` | (required) | Output file path (.mp3/.wav) | +| `--prompt` | (empty) | Music description: style, mood, scenario (max 2000 chars) | +| `--lyrics` | (empty) | Song lyrics with structure tags (max 3500 chars) | +| `--lyrics-file` | (empty) | Read lyrics from file | +| `--model` | `music-2.5+` | music-2.5+ / music-2.5 | +| `--instrumental` | false | Generate instrumental only (no vocals, music-2.5+ only) | +| `--auto-lyrics` | false | Auto-generate lyrics from prompt | +| `--format` | mp3 | mp3 / wav / pcm | +| `--sample-rate` | 44100 | 16000 / 24000 / 32000 / 44100 | +| `--bitrate` | 256000 | 32000 / 64000 / 128000 / 256000 | + +**Lyrics structure tags:** `[Intro]`, `[Verse]`, `[Pre Chorus]`, `[Chorus]`, `[Interlude]`, `[Bridge]`, `[Outro]`, `[Post Chorus]`, `[Transition]`, `[Break]`, `[Hook]`, `[Build Up]`, `[Inst]`, `[Solo]` + +**Programmatic:** +```python +from minimax_music import generate_music +result = generate_music(prompt="Jazz piano", is_instrumental=True) +with open("jazz.mp3", "wb") as f: + f.write(result["audio_bytes"]) +``` diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-image-guide.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-image-guide.md new file mode 100644 index 00000000..b4938acd --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-image-guide.md @@ -0,0 +1,65 @@ +# Image Generation Guide + +## CLI usage + +```bash +# Basic (1:1, 1024x1024) +python scripts/minimax_image.py "A cat astronaut floating in space" -o cat.png + +# 16:9 for hero banner +python scripts/minimax_image.py "Mountain landscape at golden hour" -o hero.png --ratio 16:9 + +# Batch: 4 images at once +python scripts/minimax_image.py "Minimalist product icon" -o icons.png -n 4 + +# With seed for reproducibility +python scripts/minimax_image.py "Abstract gradient background" -o bg.png --seed 42 + +# Enable prompt optimization +python scripts/minimax_image.py "a dog" -o dog.png --optimize + +# Base64 mode (no URL download, save directly) +python scripts/minimax_image.py "Logo concept" -o logo.png --base64 +``` + +## Programmatic usage + +```python +from minimax_image import generate_image, download_and_save + +# Generate and get URL +result = generate_image("A cat in space", aspect_ratio="16:9") +url = result["data"]["image_urls"][0] +download_and_save(url, "cat.png") + +# Generate multiple +result = generate_image("Icon design", n=4, aspect_ratio="1:1") +for i, url in enumerate(result["data"]["image_urls"]): + download_and_save(url, f"icon-{i}.png") +``` + +## Model + +Currently only `image-01`. + +## Aspect ratios & dimensions + +| Ratio | Pixels | Use case | +|-------|--------|----------| +| `1:1` | 1024x1024 | Avatar, icon, square thumbnail | +| `16:9` | 1280x720 | Hero banner, video thumbnail | +| `4:3` | 1152x864 | Standard landscape | +| `3:2` | 1248x832 | Photo-style | +| `2:3` | 832x1248 | Portrait, mobile | +| `3:4` | 864x1152 | Portrait card | +| `9:16` | 720x1280 | Mobile fullscreen, story | +| `21:9` | 1344x576 | Ultra-wide banner | + +Custom dimensions also supported: width/height in [512, 2048], must be divisible by 8. + +## Limits + +- Prompt: max 1,500 characters +- Batch: 1–9 images per request +- URL expires after 24 hours (use `--base64` to avoid expiry) +- Seed: set for reproducible results across identical prompts diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-music-guide.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-music-guide.md new file mode 100644 index 00000000..6b9df670 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-music-guide.md @@ -0,0 +1,216 @@ +# Music Generation Guide + +## CLI Usage + +```bash +# Instrumental (no vocals) +python scripts/minimax_music.py --prompt "Jazz piano, smooth, relaxing" --instrumental -o jazz.mp3 + +# With custom lyrics +python scripts/minimax_music.py --prompt "Indie folk, melancholic" --lyrics "[verse]\nStreetlights flicker\nOn empty roads" -o song.mp3 + +# Auto-generate lyrics from prompt +python scripts/minimax_music.py --prompt "Upbeat pop, energetic, summer vibes" --auto-lyrics -o pop.mp3 + +# From lyrics file +python scripts/minimax_music.py --prompt "Soulful blues, rainy night" --lyrics-file lyrics.txt -o blues.mp3 + +# Custom audio settings +python scripts/minimax_music.py --prompt "Lo-fi beats" --instrumental -o lofi.wav --format wav --sample-rate 44100 --bitrate 256000 +``` + +## Programmatic Usage + +```python +from minimax_music import generate_music + +# Instrumental +result = generate_music(prompt="Jazz piano, smooth", is_instrumental=True) +with open("jazz.mp3", "wb") as f: + f.write(result["audio_bytes"]) + +# With lyrics +result = generate_music( + prompt="Indie folk, acoustic guitar", + lyrics="[verse]\nWalking through the rain\n[chorus]\nI'll find my way home", +) + +# Auto-generate lyrics +result = generate_music( + prompt="Upbeat pop, summer anthem", + lyrics_optimizer=True, +) + +# Access metadata +print(f"Duration: {result['duration']}ms") +print(f"Sample rate: {result['sample_rate']}") +print(f"Size: {result['size']} bytes") +``` + +## Models + +| Model | Features | +|-------|----------| +| `music-2.5+` | Recommended. Supports instrumental mode, complete song structures, hi-fi audio | +| `music-2.5` | Standard model. No instrumental mode | + +## Prompt Writing + +The `prompt` parameter describes music style using comma-separated descriptors: + +| Category | Examples | +|----------|----------| +| Genre | Blues, Pop, Rock, Jazz, Electronic, Hip-hop, Folk, Classical | +| Mood | Soulful, Melancholy, Upbeat, Energetic, Peaceful, Dark, Nostalgic | +| Scenario | Rainy night, Summer day, Road trip, Late night, Sunrise | +| Instrumentation | Electric guitar, Piano, Acoustic, Synthesizer, Strings | +| Vocal type | Male vocals, Female vocals, Soft vocals, Powerful vocals | +| Tempo | Slow tempo, Fast tempo, Mid-tempo, Relaxed | + +**Example prompts:** +``` +"Soulful Blues, Rainy Night, Melancholy, Male Vocals, Slow Tempo" +"Upbeat Pop, Summer Vibes, Female Vocals, Energetic, Synth-heavy" +"Lo-fi Hip-hop, Chill, Relaxed, Instrumental, Piano samples" +"Cinematic Orchestral, Epic, Building tension, Strings and Brass" +``` + +## Lyrics Format + +Use structure tags in brackets to organize song sections: + +### Structure Tags + +| Tag | Purpose | +|-----|---------| +| `[Intro]` | Opening section (can be instrumental) | +| `[Verse]` / `[Verse 1]` | Story/narrative sections | +| `[Pre-Chorus]` | Build-up before chorus | +| `[Chorus]` | Main hook, typically repeated | +| `[Post Chorus]` | Extension after chorus | +| `[Bridge]` | Contrasting section near end | +| `[Interlude]` | Instrumental break | +| `[Solo]` | Instrumental solo (add direction: "slow, bluesy") | +| `[Outro]` | Closing section | +| `[Break]` | Short pause or transition | +| `[Hook]` | Catchy repeated phrase | +| `[Build Up]` | Tension building section | +| `[Inst]` | Instrumental section | +| `[Transition]` | Section change | + +### Backing Vocals & Directions + +Use parentheses for backing vocals or performance notes: +``` +(Ooh, yeah) +(Harmonize) +(Whispered) +(Fade out...) +``` + +### Example Lyrics + +``` +[Intro] +(Soft piano) + +[Verse 1] +Streetlights flicker on empty roads +The rain keeps falling, the wind still blows +I'm walking home with nowhere to go +Just memories of what I used to know + +[Pre-Chorus] +And I can feel it coming back to me +(Coming back to me) + +[Chorus] +Under the neon lights tonight +I'm searching for what feels right +(Oh, feels right) +These city streets will guide me home +I'm tired of feeling so alone + +[Verse 2] +Coffee shops and midnight trains +The faces change but the feeling remains +... + +[Bridge] +Maybe tomorrow will be different +Maybe I'll finally understand +(Understand...) + +[Solo] +(Slow, mournful, bluesy guitar) + +[Outro] +(Fade out...) +Under the neon lights... +``` + +## Audio Settings + +| Parameter | Options | Default | Notes | +|-----------|---------|---------|-------| +| `format` | mp3, wav, pcm | mp3 | WAV for highest quality | +| `sample_rate` | 16000, 24000, 32000, 44100 | 44100 | 44100 recommended | +| `bitrate` | 32000, 64000, 128000, 256000 | 256000 | Higher = better quality | + +## Generation Modes + +### 1. Instrumental Only +```bash +python scripts/minimax_music.py --prompt "Ambient electronic, space theme" --instrumental -o ambient.mp3 +``` +- Requires `music-2.5+` model +- Only `prompt` needed, no lyrics + +### 2. With Custom Lyrics +```bash +python scripts/minimax_music.py --prompt "Pop ballad, emotional" --lyrics "[verse]\nYour lyrics here" -o ballad.mp3 +``` +- Provide both `prompt` (style) and `lyrics` (words + structure) + +### 3. Auto-Generated Lyrics +```bash +python scripts/minimax_music.py --prompt "Rock anthem about freedom" --auto-lyrics -o rock.mp3 +``` +- System generates lyrics from prompt +- Good for quick generation when lyrics aren't critical + +## Limits + +- **Prompt:** max 2,000 characters +- **Lyrics:** 1–3,500 characters +- **Duration:** ~25-30 seconds per generation (varies) +- **URL expiration:** 24 hours (when using URL output mode) + +## Best Practices + +1. **Layer style descriptors** — Combine genre + mood + instrumentation for precise results +2. **Use structure tags** — Even simple `[verse]` `[chorus]` improves arrangement +3. **Include backing vocal cues** — `(Ooh)`, `(Yeah)` add production polish +4. **Match prompt to lyrics mood** — Conflicting prompt/lyrics produce inconsistent results +5. **Instrumental for backgrounds** — Use `--instrumental` for BGM, avoiding vocal distractions +6. **High bitrate for production** — Use 256000 for final assets, lower for drafts + +## Common Use Cases + +| Use Case | Command | +|----------|---------| +| Background music | `--prompt "Lo-fi, calm, ambient" --instrumental` | +| Landing page hero | `--prompt "Cinematic, inspiring, building" --instrumental` | +| Podcast intro | `--prompt "Upbeat, energetic, short" --instrumental` | +| Demo song | `--prompt "Pop, catchy" --auto-lyrics` | +| Custom jingle | `--prompt "Happy, bright, corporate" --lyrics "[hook]\nYour brand name"` | + +## Error Handling + +| Error Code | Meaning | Solution | +|------------|---------|----------| +| 1002 | Rate limit | Wait and retry | +| 1004 | Auth failed | Check API key | +| 1008 | Insufficient balance | Top up account | +| 1026 | Content flagged | Rephrase prompt/lyrics | +| 2013 | Invalid parameters | Check prompt/lyrics length | diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-tts-guide.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-tts-guide.md new file mode 100644 index 00000000..a663be70 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-tts-guide.md @@ -0,0 +1,78 @@ +# TTS Guide + +## CLI usage (recommended) + +```bash +# Basic +python scripts/minimax_tts.py "Hello world" -o output.mp3 + +# Custom voice and speed +python scripts/minimax_tts.py "你好世界" -o hi.mp3 -v female-shaonv --speed 0.9 + +# WAV format, high quality +python scripts/minimax_tts.py "Welcome" -o out.wav -v male-qn-jingying --format wav --sample-rate 32000 + +# With emotion (for speech-2.6 models) +python scripts/minimax_tts.py "Great news!" -o happy.mp3 -v female-shaonv --emotion happy --model speech-2.6-hd +``` + +## Programmatic usage + +```python +from minimax_tts import tts + +# Basic +audio_bytes = tts("Hello world") + +# With options +audio_bytes = tts( + text="Welcome to our product.", + voice_id="female-shaonv", + model="speech-2.8-hd", + speed=0.9, + fmt="mp3", +) + +# Save to file +with open("output.mp3", "wb") as f: + f.write(audio_bytes) +``` + +## Limits + +- **Sync TTS:** max 10,000 characters per request +- **Pause markers:** insert `<#1.5#>` for a 1.5s pause (range: 0.01–99.99s) + +## Model selection + +| Model | Best for | +|-------|----------| +| `speech-2.8-hd` | Highest quality, auto emotion (recommended) | +| `speech-2.8-turbo` | Fast, good quality | +| `speech-2.6-hd` | Manual emotion control needed | +| `speech-2.6-turbo` | Fast + manual emotion | + +## Voice selection + +See [minimax-voice-catalog.md](minimax-voice-catalog.md) for the full list. + +Common voices: + +| Voice ID | Gender | Style | +|----------|--------|-------| +| `male-qn-qingse` | Male | Young, gentle | +| `male-qn-jingying` | Male | Elite, authoritative | +| `male-qn-badao` | Male | Dominant, powerful | +| `female-shaonv` | Female | Young, bright | +| `female-yujie` | Female | Mature, elegant | +| `female-chengshu` | Female | Sophisticated | +| `presenter_male` | Male | News presenter | +| `presenter_female` | Female | News presenter | +| `audiobook_male_1` | Male | Audiobook narrator | +| `audiobook_female_1` | Female | Audiobook narrator | + +## Best practices + +- Use `speech-2.8-hd` and let emotion auto-match — don't manually set emotion unless needed +- Use 32000 sample rate for web audio (good balance of quality and file size) +- For long text (>10,000 chars), split into chunks and merge with FFmpeg diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-video-guide.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-video-guide.md new file mode 100644 index 00000000..2700a2cd --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-video-guide.md @@ -0,0 +1,82 @@ +# Video Generation Guide + +## CLI usage + +```bash +# Basic +python scripts/minimax_video.py "A cat playing piano in a cozy room" -o cat.mp4 + +# With camera control +python scripts/minimax_video.py "Ocean waves crashing on rocks [Truck left]" -o waves.mp4 + +# 10 seconds, 1080P +python scripts/minimax_video.py "City skyline at sunset [Push in]" -o city.mp4 --duration 10 --resolution 1080P + +# Disable prompt auto-optimization +python scripts/minimax_video.py "Exact prompt I want used" -o out.mp4 --no-optimize +``` + +## Programmatic usage + +```python +from minimax_video import generate, create_task, poll_task, download_video + +# Full pipeline (blocking) +generate("A cat playing piano", "cat.mp4", model="MiniMax-Hailuo-2.3", duration=6) + +# Step by step +task_id = create_task("A cat playing piano") +file_id = poll_task(task_id, interval=10, max_wait=600) +download_video(file_id, "cat.mp4") +``` + +## Models + +| Model | Resolution | Duration | Notes | +|-------|-----------|----------|-------| +| `MiniMax-Hailuo-2.3` | 768P, 1080P | 6s, 10s (768P only) | Latest, recommended | +| `MiniMax-Hailuo-02` | 768P, 1080P | 6s, 10s (768P only) | Previous gen | +| `T2V-01-Director` | 720P | 6s | Camera control optimized | +| `T2V-01` | 720P | 6s | Base model | + +## Camera commands + +Insert `[Command]` in prompt text to control camera movement: + +| Command | Effect | +|---------|--------| +| `[Truck left]` | Camera moves left | +| `[Truck right]` | Camera moves right | +| `[Push in]` | Camera moves toward subject | +| `[Pull out]` | Camera moves away from subject | +| `[Pan left]` | Camera rotates left (fixed position) | +| `[Pan right]` | Camera rotates right (fixed position) | +| `[Tilt up]` | Camera tilts upward | +| `[Tilt down]` | Camera tilts downward | +| `[Pedestal up]` | Camera rises vertically | +| `[Pedestal down]` | Camera lowers vertically | +| `[Zoom in]` | Lens zooms in | +| `[Zoom out]` | Lens zooms out | +| `[Static shot]` | No camera movement | +| `[Tracking shot]` | Camera follows subject | +| `[Shake]` | Handheld shake effect | + +Example: `"A runner sprints through a forest trail [Tracking shot]"` + +## Pipeline + +The script handles the full async flow: + +1. **Create task** — `POST /v1/video_generation` → returns `task_id` +2. **Poll status** — `GET /v1/query/video_generation?task_id=xxx` → poll until `Success` + - Status values: `Preparing` → `Queueing` → `Processing` → `Success` / `Fail` +3. **Download** — `GET /v1/files/retrieve?file_id=xxx` → get `download_url` (valid 1 hour) → save file + +Typical generation time: 1–5 minutes depending on duration and resolution. + +## Limits + +- Prompt: max 2,000 characters +- 1080P: only supports 6s duration +- 10s duration: only available at 768P with Hailuo-2.3/02 +- Download URL expires after 1 hour diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-voice-catalog.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-voice-catalog.md new file mode 100644 index 00000000..7ed8aa46 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/minimax-voice-catalog.md @@ -0,0 +1,685 @@ +# MiniMax Voice Catalog + +Complete reference for all available voices in the MiniMax Voice API. + +## Contents + +- [Voice Recommendation](#voice-recommendation) - Find voices by content type and characteristics +- [System Voices List (categorized by language)](#system-voices-list-categorized-by-language) - Complete voice database by language +- [Voice Parameters](#voice-parameters) - Configure voice settings (speed, volume, pitch, emotion) +- [Custom Voices](#custom-voices) - Voice cloning and voice design options +- [Voice Comparison Table](#voice-comparison-table) - Quick reference comparison +- [Voice IDs for Quick Reference](#voice-ids-for-quick-reference) - Most popular voices at a glance + +--- + +## 1. How to Choose a Voice + +When selecting a voice, follow this two-step decision process to ensure the voice matches the scenario, gender, age, and language of the character. + +### Step 1: Identify the Usage Scenario + +First, determine whether your content falls into one of the **three professional domains** listed in **Section 2.1**: + +| Professional Domain | Examples | +|---|---| +| **Narration & Narrator in Storytelling** | suitable for the narrator in Audiobooks, fiction narration, storytelling | +| **News & Announcements** | suitable for news broadcasts, formal announcements, press releases | +| **Documentary** | suitable for documentary narration, commentary, educational films | + +**If your content matches one of these professional domains:** +→ Prioritize selecting from the recommended voices in **Section 2.1**, filtering by scenario and the speaker's **gender**. +These voices are specifically optimized for their respective professional use cases (pacing, clarity, tone). + +**If your content does NOT fall into these three professional domains:** +→ Proceed to Step 2 below. + +### Step 2: Select by Character Traits (Gender + Age + Language) + +For non-professional scenarios, select a voice from **Section 2.2** based on the following three character traits, in strict priority order: + +1. **Gender** (highest priority, non-negotiable) + - Male characters → **must** use male voices + - Female characters → **must** use female voices + - Never mismatch gender, even if other traits seem to fit + +2. **Age** (determines which subsection to look in) + - **Children** → Section 2.2 "Children's Voices" + - **Youth** (teens, young adults) → Section 2.2 "Youthful Voices" + - **Adult** → Section 2.2 "Adult Voices" + - **Elderly** → Section 2.2 "Elderly Voices" + +3. **Language** (must match the content language) + - The voice **must** match the language of the content being generated + - Chinese content → select Chinese voices; Korean content → select Korean voices; English content → select English voices, etc. + - If no exact language match exists in Section 2.2, fall back to the full **System Voices List** (Section 3) for the target language + +After narrowing down candidates by these three traits, choose the best match based on the voice's **personality**, **tone**, and **use case** as described in each voice entry. + +### Quick Reference Decision Flow + +``` +Content Type? +├── Story/Narration/News/Documentary → Section 2.1 (filter by scenario + gender) +└── Other scenarios → Section 2.2: + ├── 1. Match Gender (mandatory) + ├── 2. Match Age Group (Children/Youth/Adult/Elderly/Professional) + ├── 3. Match Language (must match content language) + └── 4. Choose best fit by personality/tone +``` + +--- + + +## 2. Voice Recommendation + +### 2.1 By Content Type + +**Narration & Narrator in Storytelling** +- Recommended: `audiobook_female_1`, `audiobook_male_1` +- Characteristics: suitable for narrating stories, sustained performance, clear articulation, good pacing + +**News & Announcements** +- Recommended: `Chinese (Mandarin)_News_Anchor`, `Chinese (Mandarin)_Male_Announcer` +- Characteristics: Authoritative, clear, professional pacing + +**Documentary** +- Recommended: `doc_commentary` +- Characteristics: Professional, clear, consistent pacing + + +### 2.2 By Characteristics + +#### Children's Voices + +| voice_id | Name | Description | Best For | Language | +|----------|------|-------------|----------|----------| +| `clever_boy` | 聪明男童 | Smart, witty boy voice | Children's content, educational | Chinese (Mandarin) | +| `cute_boy` | 可爱男童 | Adorable young boy voice | Kids' content, animations | Chinese (Mandarin) | +| `lovely_girl` | 萌萌女童 | Cute, sweet girl voice | Children's stories, games | Chinese (Mandarin) | +| `cartoon_pig` | 卡通猪小琪 | Cartoon character voice | Animations, comedy, entertainment | Chinese (Mandarin) | +| `Korean_SweetGirl` | Sweet Girl | Sweet, adorable young girl voice | Children's content, romance | Korean | +| `Indonesian_SweetGirl` | Sweet Girl | Sweet, adorable girl voice | Children's content, friendly | Indonesian | +| `English_Sweet_Girl` | Sweet Girl | Sweet, innocent young girl voice | Children's content, friendly | English | +| `Spanish_Kind-heartedGirl` | Kind-hearted Girl | Warm, compassionate girl voice | Children's content, warm | Spanish | +| `Portuguese_Kind-heartedGirl` | Kind-hearted Girl | Warm, compassionate girl voice | Children's content, warm | Portuguese | + +#### Youthful Voices + +| voice_id | Name | Description | Best For | Language | +|----------|------|-------------|----------|----------| +| `male-qn-qingse` | 青涩青年 | Youthful, inexperienced young man voice | Campus stories, coming-of-age content | Chinese (Mandarin) | +| `male-qn-daxuesheng` | 青年大学生 | Young university student voice | Campus content, educational | Chinese (Mandarin) | +| `female-shaonv` | 少女 | Young maiden voice | Romance, youth content | Chinese (Mandarin) | +| `bingjiao_didi` | 病娇弟弟 | Tsundere young brother voice | Romance, character-driven content | Chinese (Mandarin) | +| `junlang_nanyou` | 俊朗男友 | Handsome boyfriend voice | Romance, dating content | Chinese (Mandarin) | +| `chunzhen_xuedi` | 纯真学弟 | Innocent junior student voice | Campus stories, youth content | Chinese (Mandarin) | +| `lengdan_xiongzhang` | 冷淡学长 | Cool senior student voice | Campus stories, romance | Chinese (Mandarin) | +| `diadia_xuemei` | 嗲嗲学妹 | Flirty junior girl voice | Romance, dating content | Chinese (Mandarin) | +| `danya_xuejie` | 淡雅学姐 | Elegant senior girl voice | Campus stories, romance | Chinese (Mandarin) | +| `Chinese (Mandarin)_Straightforward_Boy` | 率真弟弟 | Frank, straightforward boy voice | Casual, direct content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Sincere_Adult` | 真诚青年 | Sincere young adult voice | Honest, genuine content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Pure-hearted_Boy` | 清澈邻家弟弟 | Pure-hearted neighbor boy voice | Innocent, wholesome content | Chinese (Mandarin) | +| `Korean_CheerfulBoyfriend` | Cheerful Boyfriend | Energetic, loving boyfriend voice | Romance, dating content | Korean | +| `Korean_ShyGirl` | Shy Girl | Timid, reserved girl voice | Comedy, romance | Korean | +| `Japanese_SportyStudent` | Sporty Student | Energetic athletic student voice | Sports, youth content | Japanese | +| `Japanese_InnocentBoy` | Innocent Boy | Pure, naive young boy voice | Children's content | Japanese | +| `Spanish_SincereTeen` | SincereTeen | Honest, genuine teenager voice | Youth, authentic | Spanish | +| `Spanish_Strong-WilledBoy` | Strong-willed Boy | Determined, persistent boy voice | Youth, motivation | Spanish | + +#### Adult Voices + +| voice_id | Name | Description | Best For | Language | +|----------|------|-------------|----------|----------| +| `female-chengshu` | 成熟女性 | Mature woman voice | Sophisticated, adult content | Chinese (Mandarin) | +| `female-yujie` | 御姐 | Mature, elegant woman voice | Romance, professional content | Chinese (Mandarin) | +| `female-tianmei` | 甜美女性 | Sweet, pleasant woman voice | Soft, gentle content | Chinese (Mandarin) | +| `badao_shaoye` | 霸道少爷 | Arrogant young master voice | Drama, character roles | Chinese (Mandarin) | +| `wumei_yujie` | 妩媚御姐 | Charming mature woman voice | Romance, mature content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Gentleman` | 温润男声 | Gentle, refined male voice | Narration, storytelling | Chinese (Mandarin) | +| `Chinese (Mandarin)_Unrestrained_Young_Man` | 不羁青年 | Unrestrained young man voice | Casual, entertainment content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Southern_Young_Man` | 南方小哥 | Southern young man voice | Regional character, casual content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Gentle_Youth` | 温润青年 | Gentle young man voice | Narration, calm content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Warm_Girl` | 温暖少女 | Warm young girl voice | Friendly, supportive content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Soft_Girl` | 柔和少女 | Soft, gentle girl voice | Calm, soothing content | Chinese (Mandarin) | +| `Korean_PlayboyCharmer` | Playboy Charmer | Smooth, flirtatious male voice | Romance, entertainment | Korean | +| `Korean_CalmLady` | Calm Lady | Composed, serene female voice | Meditation, relaxation | Korean | +| `Spanish_ConfidentWoman` | Confident Woman | Self-assured, capable woman voice | Professional, empowerment | Spanish | +| `Portuguese_ConfidentWoman` | Confident Woman | Self-assured, capable woman voice | Professional, empowerment | Portuguese | + +#### Elderly Voices + +| voice_id | Name | Description | Best For | Language | +|----------|------|-------------|----------|----------| +| `Chinese (Mandarin)_Humorous_Elder` | 搞笑大爷 | Humorous old man voice | Comedy, entertainment | Chinese (Mandarin) | +| `Chinese (Mandarin)_Kind-hearted_Elder` | 花甲奶奶 | Kind elderly lady voice | Stories, warm content | Chinese (Mandarin) | +| `Chinese (Mandarin)_Kind-hearted_Antie` | 热心大婶 | Kind-hearted auntie voice | Warm, friendly content | Chinese (Mandarin) | +| `Japanese_IntellectualSenior` | Intellectual Senior | Wise, knowledgeable elder voice | Narration, educational | Japanese | +| `Korean_IntellectualSenior` | Intellectual Senior | Wise, knowledgeable elder voice | Educational, narration | Korean | +| `Spanish_Wiselady` | Wise Lady | Experienced, wise woman voice | Guidance, advice | Spanish | +| `Portuguese_Wiselady` | Wise Lady | Experienced, wise woman voice | Guidance, advice | Portuguese | +| `Spanish_SereneElder` | Serene Elder | Calm, peaceful elderly voice | Meditation, wisdom | Spanish | +| `Portuguese_SereneElder` | Serene Elder | Calm, peaceful elderly voice | Meditation, wisdom | Portuguese | +| `English_Gentle-voiced_man` | Gentle-voiced Man | Soft-spoken, kind male voice | Calm, supportive content | English | + +--- + +## System Voices List (categorized by language) + +### Chinese Mandarin Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `male-qn-qingse` | 青涩青年 | Youthful, inexperienced young man voice | Campus stories, coming-of-age content | +| `male-qn-badao` | 霸道青年 | Arrogant, dominant young man voice | Drama, romance, character roles | +| `male-qn-daxuesheng` | 青年大学生 | Young university student voice | Campus content, educational | +| `female-shaonv` | 少女 | Young maiden voice | Romance, youth content | +| `female-yujie` | 御姐 | Mature, elegant woman voice | Romance, professional content | +| `female-chengshu` | 成熟女性 | Mature woman voice | Sophisticated, adult content | +| `female-tianmei` | 甜美女性 | Sweet, pleasant woman voice | Soft, gentle content | +| `clever_boy` | 聪明男童 | Smart, witty boy voice | Children's content, educational | +| `cute_boy` | 可爱男童 | Adorable young boy voice | Kids' content, animations | +| `lovely_girl` | 萌萌女童 | Cute, sweet girl voice | Children's stories, games | +| `cartoon_pig` | 卡通猪小琪 | Cartoon character voice | Animations, comedy, entertainment | +| `bingjiao_didi` | 病娇弟弟 | Tsundere young brother voice | Romance, character-driven content | +| `junlang_nanyou` | 俊朗男友 | Handsome boyfriend voice | Romance, dating content | +| `chunzhen_xuedi` | 纯真学弟 | Innocent junior student voice | Campus stories, youth content | +| `lengdan_xiongzhang` | 冷淡学长 | Cool senior student voice | Campus stories, romance | +| `badao_shaoye` | 霸道少爷 | Arrogant young master voice | Drama, character roles | +| `tianxin_xiaoling` | 甜心小玲 | Sweet Xiao Ling voice | Character roles, animations | +| `qiaopi_mengmei` | 俏皮萌妹 | Playful cute girl voice | Comedy, light-hearted content | +| `wumei_yujie` | 妩媚御姐 | Charming mature woman voice | Romance, mature content | +| `diadia_xuemei` | 嗲嗲学妹 | Flirty junior girl voice | Romance, dating content | +| `danya_xuejie` | 淡雅学姐 | Elegant senior girl voice | Campus stories, romance | +| `Arrogant_Miss` | 嚣张小姐 | Arrogant young lady voice | Drama, character roles | +| `Robot_Armor` | 机械战甲 | Robotic armor voice | Sci-fi, game characters | +| `Chinese (Mandarin)_Reliable_Executive` | 沉稳高管 | Reliable executive voice | Corporate, business content | +| `Chinese (Mandarin)_News_Anchor` | 新闻女声 | News anchor female voice | News broadcasts, current affairs | +| `Chinese (Mandarin)_Mature_Woman` | 傲娇御姐 | Tsundere mature woman voice | Romance, character-driven content | +| `Chinese (Mandarin)_Unrestrained_Young_Man` | 不羁青年 | Unrestrained young man voice | Casual, entertainment content | +| `male-qn-jingying` | 精英青年 | Elite, ambitious young man voice | Business, professional content | +| `Chinese (Mandarin)_Kind-hearted_Antie` | 热心大婶 | Kind-hearted auntie voice | Warm, friendly content | +| `Chinese (Mandarin)_HK_Flight_Attendant` | 港普空姐 | HK accent flight attendant voice | Regional character, entertainment | +| `Chinese (Mandarin)_Humorous_Elder` | 搞笑大爷 | Humorous old man voice | Comedy, entertainment | +| `Chinese (Mandarin)_Gentleman` | 温润男声 | Gentle, refined male voice | Narration, storytelling | +| `Chinese (Mandarin)_Warm_Bestie` | 温暖闺蜜 | Warm bestie female voice | Friendly, supportive content | +| `Chinese (Mandarin)_Male_Announcer` | 播报男声 | Male announcer voice | Announcements, broadcasts | +| `Chinese (Mandarin)_Sweet_Lady` | 甜美女声 | Sweet lady voice | Soft, gentle content | +| `Chinese (Mandarin)_Southern_Young_Man` | 南方小哥 | Southern young man voice | Regional character, casual content | +| `Chinese (Mandarin)_Wise_Women` | 阅历姐姐 | Experienced wise woman voice | Advice, guidance content | +| `Chinese (Mandarin)_Gentle_Youth` | 温润青年 | Gentle young man voice | Narration, calm content | +| `Chinese (Mandarin)_Warm_Girl` | 温暖少女 | Warm young girl voice | Friendly, supportive content | +| `Chinese (Mandarin)_Kind-hearted_Elder` | 花甲奶奶 | Kind elderly lady voice | Stories, warm content | +| `Chinese (Mandarin)_Cute_Spirit` | 憨憨萌兽 | Cute cartoon spirit voice | Animations, children's content | +| `Chinese (Mandarin)_Radio_Host` | 电台男主播 | Radio host male voice | Podcasts, radio shows | +| `Chinese (Mandarin)_Lyrical_Voice` | 抒情男声 | Lyrical male singing voice | Music, singing content | +| `Chinese (Mandarin)_Straightforward_Boy` | 率真弟弟 | Frank, straightforward boy voice | Casual, direct content | +| `Chinese (Mandarin)_Sincere_Adult` | 真诚青年 | Sincere young adult voice | Honest, genuine content | +| `Chinese (Mandarin)_Gentle_Senior` | 温柔学姐 | Gentle senior girl voice | Campus stories, supportive content | +| `Chinese (Mandarin)_Stubborn_Friend` | 嘴硬竹马 | Stubborn childhood friend voice | Drama, character-driven content | +| `Chinese (Mandarin)_Crisp_Girl` | 清脆少女 | Crisp, clear young girl voice | Clear, bright content | +| `Chinese (Mandarin)_Pure-hearted_Boy` | 清澈邻家弟弟 | Pure-hearted neighbor boy voice | Innocent, wholesome content | +| `Chinese (Mandarin)_Soft_Girl` | 柔和少女 | Soft, gentle girl voice | Calm, soothing content | + +### Chinese Cantonese Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Cantonese_ProfessionalHost（F)` | 专业女主持 | Professional female host voice | Cantonese broadcasts, hosting | +| `Cantonese_GentleLady` | 温柔女声 | Gentle Cantonese female voice | Soft, warm Cantonese content | +| `Cantonese_ProfessionalHost（M)` | 专业男主持 | Professional male host voice | Cantonese broadcasts, hosting | +| `Cantonese_PlayfulMan` | 活泼男声 | Playful Cantonese male voice | Entertainment, casual content | +| `Cantonese_CuteGirl` | 可爱女孩 | Cute Cantonese girl voice | Children's content, animations | +| `Cantonese_KindWoman` | 善良女声 | Kind Cantonese female voice | Warm, friendly content | + +### English Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Santa_Claus` | Santa Claus | Festive, jolly male voice | Holiday content, children's stories | +| `Grinch` | Grinch | Whiny, mischievous voice | Comedy, entertainment, holiday | +| `Rudolph` | Rudolph | Cute, nasal reindeer voice | Children's content, holiday | +| `Arnold` | Arnold | Deep, robotic terminator voice | Sci-fi, action, character roles | +| `Charming_Santa` | Charming Santa | Smooth, charismatic Santa voice | Holiday, entertainment | +| `Charming_Lady` | Charming Lady | Elegant, sophisticated female voice | Professional, romance | +| `Sweet_Girl` | Sweet Girl | Sweet, innocent young girl voice | Children's content, friendly | +| `Cute_Elf` | Cute Elf | Playful, tiny elf voice | Fantasy, children's content | +| `Attractive_Girl` | Attractive Girl | Attractive, engaging female voice | Entertainment, marketing | +| `Serene_Woman` | Serene Woman | Calm, peaceful female voice | Meditation, relaxation | +| `English_Trustworthy_Man` | Trustworthy Man | Reliable, sincere male voice | Business, narration | +| `English_Graceful_Lady` | Graceful Lady | Elegant, refined female voice | Formal, professional | +| `English_Aussie_Bloke` | Aussie Bloke | Casual, friendly Australian male voice | Casual, entertainment | +| `English_Whispering_girl` | Whispering Girl | Soft, whisper voice | Romance, intimate content | +| `English_Diligent_Man` | Diligent Man | Hardworking, earnest male voice | Motivational, educational | +| `English_Gentle-voiced_man` | Gentle-voiced Man | Soft-spoken, kind male voice | Calm, supportive content | + +### Japanese Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Japanese_IntellectualSenior` | Intellectual Senior | Wise, knowledgeable elder voice | Narration, educational | +| `Japanese_DecisivePrincess` | Decisive Princess | Confident, royal princess voice | Animation, games, drama | +| `Japanese_LoyalKnight` | Loyal Knight | Brave, faithful knight voice | Fantasy, games, stories | +| `Japanese_DominantMan` | Dominant Man | Powerful, commanding male voice | Action, leadership | +| `Japanese_SeriousCommander` | Serious Commander | Stern, authoritative commander voice | Military, games | +| `Japanese_ColdQueen` | Cold Queen | Distant, majestic queen voice | Drama, fantasy | +| `Japanese_DependableWoman` | Dependable Woman | Reliable, supportive female voice | Supportive, guidance | +| `Japanese_GentleButler` | Gentle Butler | Polite, refined servant voice | Comedy, animation | +| `Japanese_KindLady` | Kind Lady | Warm, gentle noblewoman voice | Warm, comforting | +| `Japanese_CalmLady` | Calm Lady | Composed, serene female voice | Meditation, relaxation | +| `Japanese_OptimisticYouth` | Optimistic Youth | Cheerful, positive young person voice | Youth content, motivation | +| `Japanese_GenerousIzakayaOwner` | Generous Izakaya Owner | Friendly, welcoming tavern owner voice | Casual, comedy | +| `Japanese_SportyStudent` | Sporty Student | Energetic athletic student voice | Sports, youth content | +| `Japanese_InnocentBoy` | Innocent Boy | Pure, naive young boy voice | Children's content | +| `Japanese_GracefulMaiden` | Graceful Maiden | Elegant, gentle young woman voice | Romance, drama | + +### Korean Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Korean_SweetGirl` | Sweet Girl | Sweet, adorable young girl voice | Children's content, romance | +| `Korean_CheerfulBoyfriend` | Cheerful Boyfriend | Energetic, loving boyfriend voice | Romance, dating content | +| `Korean_EnchantingSister` | Enchanting Sister | Charming, captivating sister voice | Family, drama | +| `Korean_ShyGirl` | Shy Girl | Timid, reserved girl voice | Comedy, romance | +| `Korean_ReliableSister` | Reliable Sister | Trustworthy, dependable sister voice | Supportive, guidance | +| `Korean_StrictBoss` | Strict Boss | Authoritative, demanding boss voice | Business, drama | +| `Korean_SassyGirl` | Sassy Girl | Bold, witty girl voice | Comedy, entertainment | +| `Korean_ChildhoodFriendGirl` | Childhood Friend Girl | Familiar, friendly childhood friend voice | Romance, nostalgia | +| `Korean_PlayboyCharmer` | Playboy Charmer | Smooth, flirtatious male voice | Romance, entertainment | +| `Korean_ElegantPrincess` | Elegant Princess | Graceful, royal princess voice | Animation, fantasy | +| `Korean_BraveFemaleWarrior` | Brave Female Warrior | Courageous female warrior voice | Action, fantasy | +| `Korean_BraveYouth` | Brave Youth | Heroic young person voice | Action, youth | +| `Korean_CalmLady` | Calm Lady | Composed, serene female voice | Meditation, relaxation | +| `Korean_EnthusiasticTeen` | EnthusiasticTeen | Excited, energetic teenager voice | Youth content | +| `Korean_SoothingLady` | Soothing Lady | Calming, comforting female voice | Relaxation, support | +| `Korean_IntellectualSenior` | Intellectual Senior | Wise, knowledgeable elder voice | Educational, narration | +| `Korean_LonelyWarrior` | Lonely Warrior | Solitary, melancholic warrior voice | Drama, fantasy | +| `Korean_MatureLady` | MatureLady | Sophisticated, adult female voice | Professional, drama | +| `Korean_InnocentBoy` | Innocent Boy | Pure, naive young boy voice | Children's content | +| `Korean_CharmingSister` | Charming Sister | Attractive, delightful sister voice | Family, romance | +| `Korean_AthleticStudent` | Athletic Student | Sporty, energetic student voice | Sports, youth | +| `Korean_BraveAdventurer` | Brave Adventurer | Courageous explorer voice | Adventure, fantasy | +| `Korean_CalmGentleman` | Calm Gentleman | Composed, refined gentleman voice | Formal, professional | +| `Korean_WiseElf` | Wise Elf | Ancient, mystical elf voice | Fantasy, narration | +| `Korean_CheerfulCoolJunior` | Cheerful Cool Junior | Popular, friendly junior voice | Youth, entertainment | +| `Korean_DecisiveQueen` | Decisive Queen | Authoritative, commanding queen voice | Drama, fantasy | +| `Korean_ColdYoungMan` | Cold Young Man | Distant, aloof young man voice | Drama, romance | +| `Korean_MysteriousGirl` | Mysterious Girl | Enigmatic, secretive girl voice | Mystery, drama | +| `Korean_QuirkyGirl` | Quirky Girl | Eccentric, unique girl voice | Comedy, entertainment | +| `Korean_ConsiderateSenior` | Considerate Senior | Thoughtful, caring elder voice | Warm, supportive | +| `Korean_CheerfulLittleSister` | Cheerful Little Sister | Playful, adorable younger sister voice | Family, comedy | +| `Korean_DominantMan` | Dominant Man | Powerful, commanding male voice | Leadership, action | +| `Korean_AirheadedGirl` | Airheaded Girl | Bubbly, spacey girl voice | Comedy, entertainment | +| `Korean_ReliableYouth` | Reliable Youth | Trustworthy, dependable young person voice | Supportive, youth | +| `Korean_FriendlyBigSister` | Friendly Big Sister | Warm, protective elder sister voice | Family, support | +| `Korean_GentleBoss` | Gentle Boss | Kind, understanding boss voice | Business, supportive | +| `Korean_ColdGirl` | Cold Girl | Aloof, distant girl voice | Drama, romance | +| `Korean_HaughtyLady` | Haughty Lady | Arrogant, proud woman voice | Drama, comedy | +| `Korean_CharmingElderSister` | Charming Elder Sister | Attractive, graceful elder sister voice | Romance, family | +| `Korean_IntellectualMan` | Intellectual Man | Smart, knowledgeable male voice | Educational, professional | +| `Korean_CaringWoman` | Caring Woman | Nurturing, supportive woman voice | Supportive, warm | +| `Korean_WiseTeacher` | Wise Teacher | Experienced, knowledgeable teacher voice | Educational | +| `Korean_ConfidentBoss` | Confident Boss | Self-assured, capable boss voice | Business, leadership | +| `Korean_AthleticGirl` | Athletic Girl | Sporty, energetic girl voice | Sports, fitness | +| `Korean_PossessiveMan` | PossessiveMan | Intense, protective male voice | Romance, drama | +| `Korean_GentleWoman` | Gentle Woman | Soft-spoken, kind woman voice | Calm, supportive | +| `Korean_CockyGuy` | Cocky Guy | Confident, slightly arrogant male voice | Comedy, entertainment | +| `Korean_ThoughtfulWoman` | ThoughtfulWoman | Reflective, caring woman voice | Drama, support | +| `Korean_OptimisticYouth` | Optimistic Youth | Positive, hopeful young person voice | Motivation, youth | + +### Spanish Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Spanish_SereneWoman` | Serene Woman | Calm, peaceful female voice | Relaxation, meditation | +| `Spanish_MaturePartner` | Mature Partner | Sophisticated, adult partner voice | Romance, drama | +| `Spanish_CaptivatingStoryteller` | Captivating Storyteller | Engaging, magnetic narrator voice | Audiobooks, storytelling | +| `Spanish_Narrator` | Narrator | Professional narrative voice | Documentaries, narration | +| `Spanish_WiseScholar` | Wise Scholar | Knowledgeable, wise scholar voice | Educational, historical | +| `Spanish_Kind-heartedGirl` | Kind-hearted Girl | Warm, compassionate girl voice | Children's content, warm | +| `Spanish_DeterminedManager` | Determined Manager | Ambitious, driven manager voice | Business, motivation | +| `Spanish_BossyLeader` | Bossy Leader | Commanding, authoritative leader voice | Leadership, drama | +| `Spanish_ReservedYoungMan` | Reserved Young Man | Quiet, introverted young man voice | Drama, realistic characters | +| `Spanish_ConfidentWoman` | Confident Woman | Self-assured, capable woman voice | Professional, empowerment | +| `Spanish_ThoughtfulMan` | ThoughtfulMan | Reflective, intelligent man voice | Educational, drama | +| `Spanish_Strong-WilledBoy` | Strong-willed Boy | Determined, persistent boy voice | Youth, motivation | +| `Spanish_SophisticatedLady` | SophisticatedLady | Elegant, refined woman voice | Formal, romance | +| `Spanish_RationalMan` | Rational Man | Logical, analytical man voice | Educational, business | +| `Spanish_AnimeCharacter` | Anime Character | Exaggerated anime-style voice | Animation, entertainment | +| `Spanish_Deep-tonedMan` | Deep-toned Man | Deep, resonant male voice | Attractive, commanding | +| `Spanish_Fussyhostess` | Fussy Hostess | Particular, demanding hostess voice | Comedy, drama | +| `Spanish_SincereTeen` | SincereTeen | Honest, genuine teenager voice | Youth, authentic | +| `Spanish_FrankLady` | Frank Lady | Direct, honest woman voice | Comedy, drama | +| `Spanish_Comedian` | Comedian | Humorous, entertaining voice | Comedy, entertainment | +| `Spanish_Debator` | Debator | Argumentative, persuasive voice | Debate, discussion | +| `Spanish_ToughBoss` | Tough Boss | Harsh, demanding boss voice | Business, drama | +| `Spanish_Wiselady` | Wise Lady | Experienced, wise woman voice | Guidance, advice | +| `Spanish_Steadymentor` | Steady Mentor | Reliable, supportive mentor voice | Educational, guidance | +| `Spanish_Jovialman` | Jovial Man | Cheerful, friendly man voice | Entertainment, casual | +| `Spanish_SantaClaus` | Santa Claus | Festive Santa voice | Holiday, children | +| `Spanish_Rudolph` | Rudolph | Reindeer voice | Holiday, children | +| `Spanish_Intonategirl` | Intonate Girl | Musical, melodic girl voice | Music, singing | +| `Spanish_Arnold` | Arnold | Robotic, mechanical voice | Sci-fi, action | +| `Spanish_Ghost` | Ghost | Spooky, ethereal voice | Horror, mystery | +| `Spanish_HumorousElder` | Humorous Elder | Funny, elderly person voice | Comedy, entertainment | +| `Spanish_EnergeticBoy` | Energetic Boy | Active, lively boy voice | Youth, sports | +| `Spanish_WhimsicalGirl` | Whimsical Girl | Playful, imaginative girl voice | Children's, fantasy | +| `Spanish_StrictBoss` | Strict Boss | Strict, demanding boss voice | Business, education | +| `Spanish_ReliableMan` | Reliable Man | Trustworthy, dependable man voice | Professional, support | +| `Spanish_SereneElder` | Serene Elder | Calm, peaceful elderly voice | Meditation, wisdom | +| `Spanish_AngryMan` | Angry Man | Frustrated, irritated male voice | Drama, comedy | +| `Spanish_AssertiveQueen` | Assertive Queen | Confident, commanding queen voice | Drama, fantasy | +| `Spanish_CaringGirlfriend` | Caring Girlfriend | Nurturing, loving girlfriend voice | Romance, relationship | +| `Spanish_PowerfulSoldier` | Powerful Soldier | Strong, brave soldier voice | Action, military | +| `Spanish_PassionateWarrior` | Passionate Warrior | Fierce, dedicated warrior voice | Action, fantasy | +| `Spanish_ChattyGirl` | Chatty Girl | Talkative, sociable girl voice | Comedy, social | +| `Spanish_RomanticHusband` | Romantic Husband | Loving, romantic husband voice | Romance, family | +| `Spanish_CompellingGirl` | CompellingGirl | Persuasive, magnetic girl voice | Marketing, entertainment | +| `Spanish_PowerfulVeteran` | Powerful Veteran | Experienced, strong veteran voice | Military, drama | +| `Spanish_SensibleManager` | Sensible Manager | Practical, reasonable manager voice | Business, guidance | +| `Spanish_ThoughtfulLady` | Thoughtful Lady | Considerate, kind lady voice | Supportive, advice | + +### Portuguese Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Portuguese_SentimentalLady` | Sentimental Lady | Emotional, sensitive lady voice | Drama, romance | +| `Portuguese_BossyLeader` | Bossy Leader | Commanding, authoritative leader voice | Leadership, drama | +| `Portuguese_Wiselady` | Wise Lady | Experienced, wise woman voice | Guidance, advice | +| `Portuguese_Strong-WilledBoy` | Strong-willed Boy | Determined, persistent boy voice | Youth, motivation | +| `Portuguese_Deep-VoicedGentleman` | Deep-voiced Gentleman | Deep, rich male voice | Attractive, commanding | +| `Portuguese_UpsetGirl` | Upset Girl | Distressed, emotional girl voice | Drama, realistic | +| `Portuguese_PassionateWarrior` | Passionate Warrior | Fierce, dedicated warrior voice | Action, fantasy | +| `Portuguese_AnimeCharacter` | Anime Character | Exaggerated anime-style voice | Animation, entertainment | +| `Portuguese_ConfidentWoman` | Confident Woman | Self-assured, capable woman voice | Professional, empowerment | +| `Portuguese_AngryMan` | Angry Man | Frustrated, irritated male voice | Drama, comedy | +| `Portuguese_CaptivatingStoryteller` | Captivating Storyteller | Engaging, magnetic narrator voice | Audiobooks, storytelling | +| `Portuguese_Godfather` | Godfather | Authoritative, powerful father figure voice | Drama, powerful | +| `Portuguese_ReservedYoungMan` | Reserved Young Man | Quiet, introverted young man voice | Drama, realistic | +| `Portuguese_SmartYoungGirl` | Smart Young Girl | Intelligent, clever girl voice | Educational, youth | +| `Portuguese_Kind-heartedGirl` | Kind-hearted Girl | Warm, compassionate girl voice | Children's content, warm | +| `Portuguese_Pompouslady` | Pompous Lady | Self-important, arrogant lady voice | Comedy, drama | +| `Portuguese_Grinch` | Grinch | Whiny, mischievous voice | Comedy, entertainment | +| `Portuguese_Debator` | Debator | Argumentative, persuasive voice | Debate, discussion | +| `Portuguese_SweetGirl` | Sweet Girl | Sweet, adorable girl voice | Children's content, romance | +| `Portuguese_AttractiveGirl` | Attractive Girl | Charming, appealing girl voice | Entertainment, romance | +| `Portuguese_ThoughtfulMan` | Thoughtful Man | Reflective, intelligent man voice | Educational, drama | +| `Portuguese_PlayfulGirl` | Playful Girl | Playful, fun-loving girl voice | Comedy, children's content | +| `Portuguese_GorgeousLady` | Gorgeous Lady | Beautiful, stunning lady voice | Romance, entertainment | +| `Portuguese_LovelyLady` | Lovely Lady | Sweet, endearing lady voice | Warm, friendly | +| `Portuguese_SereneWoman` | Serene Woman | Calm, peaceful female voice | Relaxation, meditation | +| `Portuguese_SadTeen` | Sad Teen | Melancholic, teenage voice | Drama, emotional | +| `Portuguese_MaturePartner` | Mature Partner | Sophisticated, adult partner voice | Romance, drama | +| `Portuguese_Comedian` | Comedian | Humorous, entertaining voice | Comedy, entertainment | +| `Portuguese_NaughtySchoolgirl` | Naughty Schoolgirl | Mischievous, playful student voice | Comedy, school | +| `Portuguese_Narrator` | Narrator | Professional narrative voice | Documentaries, narration | +| `Portuguese_ToughBoss` | Tough Boss | Harsh, demanding boss voice | Business, drama | +| `Portuguese_Fussyhostess` | Fussy Hostess | Particular, demanding hostess voice | Comedy, drama | +| `Portuguese_Dramatist` | Dramatist | Theatrical, expressive voice | Drama, storytelling | +| `Portuguese_Steadymentor` | Steady Mentor | Reliable, supportive mentor voice | Educational, guidance | +| `Portuguese_Jovialman` | Jovial Man | Cheerful, friendly man voice | Entertainment, casual | +| `Portuguese_CharmingQueen` | Charming Queen | Elegant, captivating queen voice | Drama, fantasy | +| `Portuguese_SantaClaus` | Santa Claus | Festive Santa voice | Holiday, children | +| `Portuguese_Rudolph` | Rudolph | Reindeer voice | Holiday, children | +| `Portuguese_Arnold` | Arnold | Robotic, mechanical voice | Sci-fi, action | +| `Portuguese_CharmingSanta` | Charming Santa | Smooth, charismatic Santa voice | Holiday, entertainment | +| `Portuguese_CharmingLady` | Charming Lady | Elegant, sophisticated lady voice | Professional, romance | +| `Portuguese_Ghost` | Ghost | Spooky, ethereal voice | Horror, mystery | +| `Portuguese_HumorousElder` | Humorous Elder | Funny, elderly person voice | Comedy, entertainment | +| `Portuguese_CalmLeader` | Calm Leader | Composed, steady leader voice | Leadership, guidance | +| `Portuguese_GentleTeacher` | Gentle Teacher | Kind, patient teacher voice | Educational, supportive | +| `Portuguese_EnergeticBoy` | Energetic Boy | Active, lively boy voice | Youth, sports | +| `Portuguese_ReliableMan` | Reliable Man | Trustworthy, dependable man voice | Professional, support | +| `Portuguese_SereneElder` | Serene Elder | Calm, peaceful elderly voice | Meditation, wisdom | +| `Portuguese_GrimReaper` | Grim Reaper | Dark, ominous voice | Horror, fantasy | +| `Portuguese_AssertiveQueen` | Assertive Queen | Confident, commanding queen voice | Drama, fantasy | +| `Portuguese_WhimsicalGirl` | Whimsical Girl | Playful, imaginative girl voice | Children's, fantasy | +| `Portuguese_StressedLady` | Stressed Lady | Anxious, overwhelmed lady voice | Comedy, realistic | +| `Portuguese_FriendlyNeighbor` | Friendly Neighbor | Warm, helpful neighbor voice | Community, family | +| `Portuguese_CaringGirlfriend` | Caring Girlfriend | Nurturing, loving girlfriend voice | Romance, relationship | +| `Portuguese_PowerfulSoldier` | Powerful Soldier | Strong, brave soldier voice | Action, military | +| `Portuguese_FascinatingBoy` | Fascinating Boy | Charming, intriguing boy voice | Romance, youth | +| `Portuguese_RomanticHusband` | Romantic Husband | Loving, romantic husband voice | Romance, family | +| `Portuguese_StrictBoss` | Strict Boss | Strict, demanding boss voice | Business, education | +| `Portuguese_InspiringLady` | Inspiring Lady | Motivating, encouraging lady voice | Motivation, leadership | +| `Portuguese_PlayfulSpirit` | Playful Spirit | Cheerful, mischievous spirit voice | Fantasy, children's | +| `Portuguese_ElegantGirl` | Elegant Girl | Graceful, refined girl voice | Formal, romance | +| `Portuguese_CompellingGirl` | Compelling Girl | Persuasive, magnetic girl voice | Marketing, entertainment | +| `Portuguese_PowerfulVeteran` | Powerful Veteran | Experienced, strong veteran voice | Military, drama | +| `Portuguese_SensibleManager` | Sensible Manager | Practical, reasonable manager voice | Business, guidance | +| `Portuguese_ThoughtfulLady` | Thoughtful Lady | Considerate, kind lady voice | Supportive, advice | +| `Portuguese_TheatricalActor` | Theatrical Actor | Dramatic, expressive actor voice | Drama, entertainment | +| `Portuguese_FragileBoy` | Fragile Boy | Sensitive, vulnerable boy voice | Drama, emotional | +| `Portuguese_ChattyGirl` | Chatty Girl | Talkative, sociable girl voice | Comedy, social | +| `Portuguese_Conscientiousinstructor` | Conscientious Instructor | Careful, diligent instructor voice | Educational, training | +| `Portuguese_RationalMan` | Rational Man | Logical, analytical man voice | Educational, business | +| `Portuguese_WiseScholar` | Wise Scholar | Knowledgeable, wise scholar voice | Educational, historical | +| `Portuguese_FrankLady` | Frank Lady | Direct, honest woman voice | Comedy, drama | +| `Portuguese_DeterminedManager` | Determined Manager | Ambitious, driven manager voice | Business, motivation | + +### French Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `French_Male_Speech_New` | Level-Headed Man | Calm, reasonable male voice | Professional, narration | +| `French_Female_News Anchor` | Patient Female Presenter | Clear, patient news presenter voice | News, broadcasts | +| `French_CasualMan` | Casual Man | Relaxed, informal male voice | Casual, entertainment | +| `French_MovieLeadFemale` | Movie Lead Female | Dramatic, expressive female voice | Drama, entertainment | +| `French_FemaleAnchor` | Female Anchor | Professional female anchor voice | News, broadcasts | + +### Indonesian Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Indonesian_SweetGirl` | Sweet Girl | Sweet, adorable girl voice | Children's content, friendly | +| `Indonesian_ReservedYoungMan` | Reserved Young Man | Quiet, introverted young man voice | Drama, realistic | +| `Indonesian_CharmingGirl` | Charming Girl | Attractive, appealing girl voice | Entertainment, romance | +| `Indonesian_CalmWoman` | Calm Woman | Composed, peaceful female voice | Relaxation, meditation | +| `Indonesian_ConfidentWoman` | Confident Woman | Self-assured, capable woman voice | Professional, empowerment | +| `Indonesian_CaringMan` | Caring Man | Nurturing, supportive man voice | Supportive, family | +| `Indonesian_BossyLeader` | Bossy Leader | Commanding, authoritative leader voice | Leadership, drama | +| `Indonesian_DeterminedBoy` | Determined Boy | Ambitious, persistent boy voice | Youth, motivation | +| `Indonesian_GentleGirl` | Gentle Girl | Soft-spoken, kind girl voice | Calm, supportive | + +### German Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `German_FriendlyMan` | Friendly Man | Warm, approachable male voice | Casual, friendly | +| `German_SweetLady` | Sweet Lady | Pleasant, kind lady voice | Warm, supportive | +| `German_PlayfulMan` | Playful Man | Fun-loving, humorous male voice | Comedy, entertainment | + +### Russian Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Russian_HandsomeChildhoodFriend` | Handsome Childhood Friend | Charming childhood friend voice | Romance, nostalgia | +| `Russian_BrightHeroine` | Bright Queen | Lively, strong female lead voice | Drama, action | +| `Russian_AmbitiousWoman` | Ambitious Woman | Driven, determined woman voice | Professional, motivation | +| `Russian_ReliableMan` | Reliable Man | Trustworthy, dependable man voice | Professional, support | +| `Russian_CrazyQueen` | Crazy Girl | Wild, unpredictable female voice | Comedy, drama | +| `Russian_PessimisticGirl` | Pessimistic Girl | Gloomy, negative girl voice | Comedy, drama | +| `Russian_AttractiveGuy` | Attractive Guy | Charming, appealing male voice | Romance, entertainment | +| `Russian_Bad-temperedBoy` | Bad-tempered Boy | Irritable, grumpy boy voice | Comedy, drama | + +### Italian Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Italian_BraveHeroine` | Brave Heroine | Courageous, heroic female voice | Action, fantasy | +| `Italian_Narrator` | Narrator | Professional narrative voice | Documentaries, storytelling | +| `Italian_WanderingSorcerer` | Wandering Sorcerer | Mysterious, traveling magician voice | Fantasy, adventure | +| `Italian_DiligentLeader` | Diligent Leader | Hardworking, dedicated leader voice | Leadership, business | + +### Arabic Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Arabic_CalmWoman` | Calm Woman | Composed, peaceful female voice | Relaxation, meditation | +| `Arabic_FriendlyGuy` | Friendly Guy | Warm, approachable male voice | Casual, friendly | + +### Turkish Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Turkish_CalmWoman` | Calm Woman | Composed, peaceful female voice | Relaxation, meditation | +| `Turkish_Trustworthyman` | Trustworthy Man | Reliable, sincere male voice | Professional, business | + +### Ukrainian Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Ukrainian_CalmWoman` | Calm Woman | Composed, peaceful female voice | Relaxation, meditation | +| `Ukrainian_WiseScholar` | Wise Scholar | Knowledgeable, wise scholar voice | Educational, historical | + +### Dutch Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Dutch_kindhearted_girl` | Kind-hearted girl | Warm, compassionate girl voice | Children's content, warm | +| `Dutch_bossy_leader` | Bossy leader | Commanding, authoritative leader voice | Leadership, drama | + +### Vietnamese Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Vietnamese_kindhearted_girl` | Kind-hearted girl | Warm, compassionate girl voice | Children's content, warm | + +### Thai Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Thai_male_1_sample8` | Serene Man | Calm, peaceful male voice | Relaxation, meditation | +| `Thai_male_2_sample2` | Friendly Man | Warm, approachable male voice | Casual, friendly | +| `Thai_female_1_sample1` | Confident Woman | Self-assured, capable woman voice | Professional, empowerment | +| `Thai_female_2_sample2` | Energetic Woman | Active, lively female voice | Motivation, energy | + +### Polish Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Polish_male_1_sample4` | Male Narrator | Professional narrative voice | Documentaries, narration | +| `Polish_male_2_sample3` | Male Anchor | Professional male anchor voice | News, broadcasts | +| `Polish_female_1_sample1` | Calm Woman | Composed, peaceful female voice | Relaxation, meditation | +| `Polish_female_2_sample3` | Casual Woman | Relaxed, informal female voice | Casual, entertainment | + +### Romanian Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `Romanian_male_1_sample2` | Reliable Man | Trustworthy, dependable man voice | Professional, support | +| `Romanian_male_2_sample1` | Energetic Youth | Active, lively young person voice | Youth, motivation | +| `Romanian_female_1_sample4` | Optimistic Youth | Positive, hopeful young person voice | Motivation, youth | +| `Romanian_female_2_sample1` | Gentle Woman | Soft-spoken, kind woman voice | Calm, supportive | + +### Greek Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `greek_male_1a_v1` | Thoughtful Mentor | Reflective, wise mentor voice | Educational, guidance | +| `Greek_female_1_sample1` | Gentle Lady | Soft-spoken, kind lady voice | Calm, supportive | +| `Greek_female_2_sample3` | Girl Next Door | Friendly, approachable girl voice | Casual, friendly | + +### Czech Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `czech_male_1_v1` | Assured Presenter | Confident, professional presenter voice | Presentations, broadcasts | +| `czech_female_5_v7` | Steadfast Narrator | Reliable, consistent narrator voice | Documentaries, storytelling | +| `czech_female_2_v2` | Elegant Lady | Graceful, refined lady voice | Formal, professional | + +### Finnish Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `finnish_male_3_v1` | Upbeat Man | Cheerful, energetic male voice | Motivation, entertainment | +| `finnish_male_1_v2` | Friendly Boy | Warm, approachable boy voice | Children's content, friendly | +| `finnish_female_4_v1` | Assertive Woman | Confident, strong female voice | Professional, empowerment | + +### Hindi Voices + +| voice_id | Name | Description | Best For | +|----------|------|-------------|----------| +| `hindi_male_1_v2` | Trustworthy Advisor | Reliable, wise advisor voice | Guidance, advice | +| `hindi_female_2_v1` | Tranquil Woman | Calm, peaceful female voice | Relaxation, meditation | +| `hindi_female_1_v2` | News Anchor | Professional news anchor voice | News, broadcasts | + +--- + +## Voice Parameters + +### VoiceSetting Dataclass + +```python +from utils import VoiceSetting + +voice = VoiceSetting( + voice_id="male-qn-qingse", # Required: Voice ID + speed=1.0, # Optional: 0.5 (slower) to 2.0 (faster), default 1.0 + volume=1.0, # Optional: 0.1 (quieter) to 10.0 (louder), default 1.0 + pitch=0, # Optional: -12 (deeper) to 12 (higher), default 0 + emotion="calm", # Optional: happy, sad, angry, fearful, disgusted, surprised, calm, fluent, whisper +) +``` + +### Parameter Guidelines + +**Speed** +- 0.75: Slower, deliberate speech (news, tutorials) +- 1.0: Normal pace (most content) +- 1.25: Slightly faster (energetic content) +- 1.5+: Fast pace (time-sensitive content) + +**Volume** +- 0.8-1.0: Normal listening levels +- 1.0-1.5: Louder for attention-grabbing content +- < 0.8: Softer, intimate feeling + +**Pitch** +- -6 to -3: Deeper, more authoritative +- 0: Natural pitch +- +3 to +6: Higher, more energetic + +**Emotion** +- `calm`: Calm, neutral tone +- `fluent`: Fluent, natural tone +- `whisper`: Whisper, soft, gentle tone +- `happy`: Cheerful, upbeat tone +- `sad`: Melancholic, somber tone +- `angry`: Frustrated, intense tone +- `fearful`: Anxious, nervous tone +- `disgusted`: Repulsed, revolted tone +- `surprised`: Astonished, amazed tone + + +## Custom Voices + +### Voice Cloning + +Create custom voices from audio samples for unique brand voices. + +**Requirements:** +- Source audio: 10 seconds to 5 minutes +- Format: mp3, wav, m4a +- Size: Max 20MB +- Quality: Clear, no background noise, single speaker + +**Best Practices:** +- Use 30-60 seconds of clean speech +- Include varied intonation and emotion +- Record in quiet environment +- Consistent volume throughout + +### Voice Design + +Generate new voices through text descriptions for creative projects. + +**When to Use:** +- No existing voice matches your needs +- Need unique character voices +- Prototype before full voice cloning + +**Prompt Guidelines:** +- Include: gender, age, vocal characteristics, emotional tone, use case +- Be specific about pacing, tone, and intended audience +- Example: "A warm, grandmotherly voice with gentle pacing, perfect for bedtime stories" diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/motion-recipes.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/motion-recipes.md new file mode 100644 index 00000000..589ae9b4 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/motion-recipes.md @@ -0,0 +1,407 @@ +# Motion Recipes + +Production-ready animation code snippets. Copy and adapt as needed. + +## 1. Scroll-Triggered Reveal (Framer Motion) + +Elements fade and slide up when entering viewport. + +```tsx +"use client"; +import { motion } from "framer-motion"; + +const fadeSlideUp = { + hidden: { opacity: 0, y: 40 }, + visible: { + opacity: 1, + y: 0, + transition: { type: "spring", stiffness: 100, damping: 20 }, + }, +}; + +export function RevealSection({ children }: { children: React.ReactNode }) { + return ( + + {children} + + ); +} +``` + +## 2. Staggered List Orchestration (Framer Motion) + +Children animate sequentially with blur effect. + +```tsx +"use client"; +import { motion } from "framer-motion"; + +const container = { + hidden: {}, + visible: { transition: { staggerChildren: 0.08, delayChildren: 0.1 } }, +}; + +const item = { + hidden: { opacity: 0, y: 24, filter: "blur(4px)" }, + visible: { + opacity: 1, + y: 0, + filter: "blur(0px)", + transition: { type: "spring", stiffness: 120, damping: 20 }, + }, +}; + +export function StaggerGrid({ items }: { items: React.ReactNode[] }) { + return ( + + {items.map((child, i) => ( + + {child} + + ))} + + ); +} +``` + +## 3. GSAP ScrollTrigger Pinned Section + +Horizontal scroll panels with pinning. + +```tsx +"use client"; +import { useRef, useEffect } from "react"; +import gsap from "gsap"; +import { ScrollTrigger } from "gsap/ScrollTrigger"; + +gsap.registerPlugin(ScrollTrigger); + +export function PinnedTimeline() { + const containerRef = useRef(null); + const panelsRef = useRef(null); + + useEffect(() => { + const ctx = gsap.context(() => { + const panels = gsap.utils.toArray(".panel"); + gsap.to(panels, { + xPercent: -100 * (panels.length - 1), + ease: "none", + scrollTrigger: { + trigger: containerRef.current, + pin: true, + scrub: 1, + end: () => "+=" + (panelsRef.current?.scrollWidth ?? 0), + }, + }); + }, containerRef); + + return () => ctx.revert(); // CRITICAL: full cleanup + }, []); + + return ( +
    +
    + {/* .panel elements */} +
    +
    + ); +} +``` + +## 4. Parallax Tilt Card (Framer Motion) + +Mouse-tracking 3D perspective. Uses `useMotionValue` — never `useState`. + +```tsx +"use client"; +import { motion, useMotionValue, useTransform } from "framer-motion"; + +export function TiltCard({ children }: { children: React.ReactNode }) { + const x = useMotionValue(0.5); + const y = useMotionValue(0.5); + const rotateX = useTransform(y, [0, 1], [8, -8]); + const rotateY = useTransform(x, [0, 1], [-8, 8]); + + return ( + { + const rect = e.currentTarget.getBoundingClientRect(); + x.set((e.clientX - rect.left) / rect.width); + y.set((e.clientY - rect.top) / rect.height); + }} + onMouseLeave={() => { + x.set(0.5); + y.set(0.5); + }} + className="rounded-2xl bg-white shadow-lg" + > + {children} + + ); +} +``` + +## 5. Magnetic Button (Framer Motion) + +Cursor-attracted button. Pure `useMotionValue` — zero re-renders. + +```tsx +"use client"; +import { motion, useMotionValue, useSpring } from "framer-motion"; +import { useRef } from "react"; + +export function MagneticButton({ children }: { children: React.ReactNode }) { + const ref = useRef(null); + const x = useMotionValue(0); + const y = useMotionValue(0); + const springX = useSpring(x, { stiffness: 200, damping: 15 }); + const springY = useSpring(y, { stiffness: 200, damping: 15 }); + + return ( + { + const rect = ref.current!.getBoundingClientRect(); + const dx = e.clientX - (rect.left + rect.width / 2); + const dy = e.clientY - (rect.top + rect.height / 2); + x.set(dx * 0.3); + y.set(dy * 0.3); + }} + onMouseLeave={() => { + x.set(0); + y.set(0); + }} + > + {children} + + ); +} +``` + +## 6. Text Scramble / Decode Effect + +Matrix-style character reveal — pure JS, no library needed. + +```tsx +"use client"; +import { useEffect, useRef, useState } from "react"; + +const chars = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789"; + +export function TextScramble({ text, className }: { text: string; className?: string }) { + const [display, setDisplay] = useState(text); + const iteration = useRef(0); + + useEffect(() => { + iteration.current = 0; + const id = setInterval(() => { + setDisplay( + text + .split("") + .map((char, i) => + i < iteration.current ? char : chars[Math.floor(Math.random() * chars.length)] + ) + .join("") + ); + iteration.current += 1 / 3; + if (iteration.current >= text.length) clearInterval(id); + }, 30); + return () => clearInterval(id); + }, [text]); + + return {display}; +} +``` + +## 7. SVG Path Draw on Scroll (CSS Scroll-Driven) + +Zero-JS scroll-linked path drawing using native CSS. + +```css +@supports (animation-timeline: scroll()) { + .draw-path { + stroke-dasharray: 1; + stroke-dashoffset: 1; + animation: draw linear; + animation-timeline: scroll(); + animation-range: entry 0% cover 60%; + } + + @keyframes draw { + to { + stroke-dashoffset: 0; + } + } +} +``` + +## 8. Horizontal Scroll Hijack (GSAP) + +Vertical scroll drives horizontal panning. + +```tsx +"use client"; +import { useRef, useEffect } from "react"; +import gsap from "gsap"; +import { ScrollTrigger } from "gsap/ScrollTrigger"; + +gsap.registerPlugin(ScrollTrigger); + +export function HorizontalScroll({ children }: { children: React.ReactNode }) { + const sectionRef = useRef(null); + const trackRef = useRef(null); + + useEffect(() => { + const ctx = gsap.context(() => { + const track = trackRef.current!; + const scrollWidth = track.scrollWidth - window.innerWidth; + gsap.to(track, { + x: -scrollWidth, + ease: "none", + scrollTrigger: { + trigger: sectionRef.current, + pin: true, + scrub: 0.8, + end: () => `+=${scrollWidth}`, + }, + }); + }, sectionRef); + return () => ctx.revert(); + }, []); + + return ( +
    +
    + {children} +
    +
    + ); +} +``` + +## 9. Particle Background (React Three Fiber) + +Isolated canvas layer. Purely decorative, pointer-events-none. + +```tsx +"use client"; +import { Canvas, useFrame } from "@react-three/fiber"; +import { useRef, useMemo } from "react"; +import * as THREE from "three"; + +function Particles({ count = 800 }) { + const mesh = useRef(null); + const positions = useMemo(() => { + const arr = new Float32Array(count * 3); + for (let i = 0; i < count * 3; i++) arr[i] = (Math.random() - 0.5) * 10; + return arr; + }, [count]); + + useFrame(({ clock }) => { + if (mesh.current) mesh.current.rotation.y = clock.getElapsedTime() * 0.05; + }); + + return ( + + + + + + + ); +} + +export function ParticleCanvas() { + return ( +
    + + + +
    + ); +} +``` + +## 10. Shared Layout Morph (Framer Motion) + +Card-to-modal expansion using `layoutId`. + +```tsx +"use client"; +import { motion, AnimatePresence } from "framer-motion"; +import { useState } from "react"; + +export function MorphCard({ id, preview, detail }: { + id: string; + preview: React.ReactNode; + detail: React.ReactNode; +}) { + const [open, setOpen] = useState(false); + return ( + <> + setOpen(true)} + className="cursor-pointer rounded-2xl bg-white p-6 shadow-md"> + {preview} + + + + {open && ( + <> + setOpen(false)} + /> + + {detail} + + + )} + + + ); +} +``` + +## Scroll Animation Patterns + +### Sticky Scroll Stack +Cards pin to top and stack over each other. +- Each card: `position: sticky; top: calc(var(--index) * 2rem)` +- Depth illusion: `scale(calc(1 - var(--index) * 0.03))` + +### Split-Screen Parallax +Two viewport halves scroll at different speeds. +- Left: `translateY` at 0.5x scroll speed (GSAP `scrub`) +- Mobile: collapse to single column, disable parallax + +### Zoom Parallax +Hero image scales 1 to 1.5 on scroll. +```tsx +scrollTrigger: { trigger: heroRef, start: "top top", end: "bottom top", scrub: true } +gsap.to(imageRef, { scale: 1.5, ease: "none" }); +``` + +### Text Mask Reveal +Large typography as window into video/image background. +- `background-clip: text` + `color: transparent` +- Animate `background-position` on scroll + +### Curtain Reveal +Hero splits in half, each side slides away on scroll. +- Two halves clipped with `clip-path: inset(0 50% 0 0)` and `inset(0 0 0 50%)` +- GSAP animates `xPercent: -100` and `xPercent: 100` diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/references/troubleshooting.md b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/troubleshooting.md new file mode 100644 index 00000000..464edad6 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/references/troubleshooting.md @@ -0,0 +1,85 @@ +# Troubleshooting + +## Quick reference + +| Error | Cause | Fix | +|-------|-------|-----| +| `MINIMAX_API_KEY is not set` | Key not set | `export MINIMAX_API_KEY="key"` | +| `401 Unauthorized` | Invalid/expired key | Check key validity | +| `429 Too Many Requests` | Rate limit | Add delays between requests | +| `TimeoutError` | Network or long text | Use async TTS for long text, check network | +| `invalid params, method t2a-v2 not have model` | Wrong model name | Use `speech-2.8-hd` (hyphens, not underscores) | +| `brotli: decoder process called...` | Encoding issue | Already fixed in utils.py (Accept-Encoding header) | + +## Environment + +### API key not set + +```bash +export MINIMAX_API_KEY="" + +# Verify +echo $MINIMAX_API_KEY +``` + +### FFmpeg not found + +```bash +# macOS +brew install ffmpeg + +# Ubuntu +sudo apt install ffmpeg + +# Verify +ffmpeg -version +``` + +### Missing Python packages + +```bash +pip install requests +``` + +## API errors + +### Authentication (401) + +- Verify API key is correct and not expired +- Check for extra spaces in key value + +### Rate limiting (429) + +Add delays between requests: +```python +import time +for text in texts: + result = tts(text) + time.sleep(1) +``` + +### Invalid model name + +Valid names (use hyphens, must include -hd or -turbo): +- `speech-2.8-hd` (recommended) +- `speech-2.8-turbo` +- `speech-2.6-hd` +- `speech-2.6-turbo` + +Wrong: `speech_01`, `speech_2.6`, `speech-01` + +## Audio issues + +### Poor quality + +Re-generate with higher settings: +```bash +python scripts/minimax_tts.py "text" -o out.mp3 --sample-rate 32000 --model speech-2.8-hd +``` + +### Invalid emotion + +Valid emotions: +- All models: happy, sad, angry, fearful, disgusted, surprised, calm +- speech-2.6 only: + fluent, whisper +- speech-2.8: auto-matched (leave empty, recommended) diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_image.py b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_image.py new file mode 100644 index 00000000..53e70101 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_image.py @@ -0,0 +1,133 @@ +#!/usr/bin/env python3 +# SPDX-License-Identifier: MIT +""" +MiniMax Text-to-Image — synchronous generation. + +Usage: + python minimax_image.py "A cat in space" -o cat.png + python minimax_image.py "Mountain landscape" -o bg.png --ratio 16:9 + python minimax_image.py "Product icons" -o icons.png -n 4 --ratio 1:1 + +Env: MINIMAX_API_KEY (required) +""" + +import os +import sys +import json +import argparse +import requests + +API_KEY = os.getenv("MINIMAX_API_KEY") +API_BASE = "https://api.minimax.io/v1" + +ASPECT_RATIOS = ["1:1", "16:9", "4:3", "3:2", "2:3", "3:4", "9:16", "21:9"] + + +def _headers(): + if not API_KEY: + raise SystemExit("ERROR: MINIMAX_API_KEY is not set.\n export MINIMAX_API_KEY='your-key'") + return { + "Authorization": f"Bearer {API_KEY}", + "Content-Type": "application/json", + } + + +def generate_image( + prompt: str, + model: str = "image-01", + aspect_ratio: str = "1:1", + n: int = 1, + response_format: str = "url", + prompt_optimizer: bool = False, + seed: int = None, +) -> dict: + """Generate image(s). Returns API response dict.""" + payload = { + "model": model, + "prompt": prompt, + "aspect_ratio": aspect_ratio, + "n": n, + "response_format": response_format, + "prompt_optimizer": prompt_optimizer, + } + if seed is not None: + payload["seed"] = seed + + resp = requests.post( + f"{API_BASE}/image_generation", + headers=_headers(), + json=payload, + timeout=120, + ) + resp.raise_for_status() + data = resp.json() + + base_resp = data.get("base_resp", {}) + if base_resp.get("status_code", 0) != 0: + raise SystemExit(f"API Error [{base_resp.get('status_code')}]: {base_resp.get('status_msg')}") + + return data + + +def download_and_save(url: str, output_path: str): + """Download image from URL and save.""" + resp = requests.get(url, timeout=60) + resp.raise_for_status() + with open(output_path, "wb") as f: + f.write(resp.content) + return len(resp.content) + + +def main(): + p = argparse.ArgumentParser(description="MiniMax Text-to-Image") + p.add_argument("prompt", help="Image description (max 1500 chars)") + p.add_argument("-o", "--output", required=True, help="Output file path (.png/.jpg)") + p.add_argument("--model", default="image-01", help="Model (default: image-01)") + p.add_argument("--ratio", default="1:1", choices=ASPECT_RATIOS, help="Aspect ratio (default: 1:1)") + p.add_argument("-n", "--count", type=int, default=1, choices=range(1, 10), help="Number of images (1-9, default: 1)") + p.add_argument("--seed", type=int, default=None, help="Random seed for reproducibility") + p.add_argument("--optimize", action="store_true", help="Enable prompt auto-optimization") + p.add_argument("--base64", action="store_true", help="Use base64 response instead of URL") + args = p.parse_args() + + os.makedirs(os.path.dirname(args.output) or ".", exist_ok=True) + + fmt = "base64" if args.base64 else "url" + result = generate_image( + prompt=args.prompt, + model=args.model, + aspect_ratio=args.ratio, + n=args.count, + response_format=fmt, + prompt_optimizer=args.optimize, + seed=args.seed, + ) + + meta = result.get("metadata", {}) + print(f"Generated: {meta.get('success_count', '?')} success, {meta.get('failed_count', '?')} failed") + + if args.base64: + images = result.get("data", {}).get("image_base64", []) + import base64 + for i, b64 in enumerate(images): + path = args.output if len(images) == 1 else _numbered_path(args.output, i) + raw = base64.b64decode(b64) + with open(path, "wb") as f: + f.write(raw) + print(f"OK: {len(raw)} bytes -> {path}") + else: + urls = result.get("data", {}).get("image_urls", []) + for i, url in enumerate(urls): + path = args.output if len(urls) == 1 else _numbered_path(args.output, i) + size = download_and_save(url, path) + print(f"OK: {size} bytes -> {path}") + + +def _numbered_path(path: str, index: int) -> str: + """Insert index before extension: out.png -> out-0.png""" + base, ext = os.path.splitext(path) + return f"{base}-{index}{ext}" + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_music.py b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_music.py new file mode 100644 index 00000000..54d531a8 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_music.py @@ -0,0 +1,153 @@ +#!/usr/bin/env python3 +# SPDX-License-Identifier: MIT +""" +MiniMax Music Generation (HTTP) +Self-contained: no external dependencies beyond `requests`. + +Usage: + python minimax_music.py --prompt "Indie folk, melancholic" --lyrics "[verse]\nStreetlights flicker" -o song.mp3 + python minimax_music.py --prompt "Upbeat pop, energetic" --auto-lyrics -o pop.mp3 + python minimax_music.py --prompt "Jazz piano, smooth, relaxing" --instrumental -o jazz.mp3 + +Env: MINIMAX_API_KEY (required) +""" + +import os +import sys +import json +import argparse +import requests + +API_KEY = os.getenv("MINIMAX_API_KEY") +API_BASE = os.getenv("MINIMAX_API_BASE", "https://api.minimax.io/v1") + + +def generate_music( + prompt: str = "", + lyrics: str = "", + model: str = "music-2.5+", + is_instrumental: bool = False, + lyrics_optimizer: bool = False, + sample_rate: int = 44100, + bitrate: int = 256000, + fmt: str = "mp3", + output_format: str = "hex", + timeout: int = 600, +) -> dict: + """Synchronous HTTP music generation. Returns dict with audio bytes and metadata.""" + if not API_KEY: + raise SystemExit("ERROR: MINIMAX_API_KEY is not set.\n export MINIMAX_API_KEY='your-key'") + + payload = { + "model": model, + "audio_setting": { + "sample_rate": sample_rate, + "bitrate": bitrate, + "format": fmt, + }, + "output_format": output_format, + } + + if prompt: + payload["prompt"] = prompt + if lyrics: + payload["lyrics"] = lyrics + if is_instrumental: + payload["is_instrumental"] = True + if lyrics_optimizer: + payload["lyrics_optimizer"] = True + + resp = requests.post( + f"{API_BASE}/music_generation", + headers={ + "Authorization": f"Bearer {API_KEY}", + "Content-Type": "application/json", + }, + json=payload, + timeout=timeout, + ) + resp.raise_for_status() + data = resp.json() + + # Check API-level error + base_resp = data.get("base_resp", {}) + if base_resp.get("status_code", 0) != 0: + raise SystemExit(f"API Error [{base_resp.get('status_code')}]: {base_resp.get('status_msg')}") + + status = data.get("data", {}).get("status") + if status != 2: + raise SystemExit(f"Generation incomplete (status={status}): {json.dumps(data, indent=2)}") + + audio_data = data.get("data", {}).get("audio", "") + if not audio_data: + raise SystemExit(f"No audio in response: {json.dumps(data, indent=2)}") + + extra = data.get("extra_info", {}) + + if output_format == "hex": + audio_bytes = bytes.fromhex(audio_data) + else: + # URL mode — audio_data is a URL string + audio_bytes = None + + return { + "audio_bytes": audio_bytes, + "audio_url": audio_data if output_format == "url" else None, + "duration": extra.get("music_duration"), + "sample_rate": extra.get("music_sample_rate"), + "channels": extra.get("music_channel"), + "bitrate": extra.get("bitrate"), + "size": extra.get("music_size"), + } + + +def main(): + p = argparse.ArgumentParser(description="MiniMax Music Generation (HTTP)") + p.add_argument("-o", "--output", required=True, help="Output file path") + p.add_argument("--prompt", default="", help="Music description: style, mood, scenario (max 2000 chars)") + p.add_argument("--lyrics", default="", help="Song lyrics with structure tags (max 3500 chars)") + p.add_argument("--lyrics-file", default="", help="Read lyrics from file instead of --lyrics") + p.add_argument("--model", default="music-2.5+", choices=["music-2.5+", "music-2.5"], help="Model (default: music-2.5+)") + p.add_argument("--instrumental", action="store_true", help="Generate instrumental only (no vocals)") + p.add_argument("--auto-lyrics", action="store_true", help="Auto-generate lyrics from prompt") + p.add_argument("--format", default="mp3", dest="fmt", choices=["mp3", "wav", "pcm"], help="Audio format (default: mp3)") + p.add_argument("--sample-rate", type=int, default=44100, choices=[16000, 24000, 32000, 44100], help="Sample rate (default: 44100)") + p.add_argument("--bitrate", type=int, default=256000, choices=[32000, 64000, 128000, 256000], help="Bitrate (default: 256000)") + args = p.parse_args() + + lyrics = args.lyrics + if args.lyrics_file: + with open(args.lyrics_file, "r") as f: + lyrics = f.read() + + os.makedirs(os.path.dirname(args.output) or ".", exist_ok=True) + + result = generate_music( + prompt=args.prompt, + lyrics=lyrics, + model=args.model, + is_instrumental=args.instrumental, + lyrics_optimizer=args.auto_lyrics, + sample_rate=args.sample_rate, + bitrate=args.bitrate, + fmt=args.fmt, + ) + + if result["audio_bytes"]: + with open(args.output, "wb") as f: + f.write(result["audio_bytes"]) + size = len(result["audio_bytes"]) + else: + # URL mode — download + r = requests.get(result["audio_url"], timeout=120) + r.raise_for_status() + with open(args.output, "wb") as f: + f.write(r.content) + size = len(r.content) + + duration = result.get("duration", "?") + print(f"OK: {size} bytes -> {args.output} (duration: {duration}s)") + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_tts.py b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_tts.py new file mode 100644 index 00000000..9f78d67b --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_tts.py @@ -0,0 +1,123 @@ +#!/usr/bin/env python3 +# SPDX-License-Identifier: MIT +""" +MiniMax Sync TTS (HTTP) +Self-contained: no external dependencies beyond `requests`. + +Usage: + python minimax_tts.py "Hello world" -o output.mp3 + python minimax_tts.py "你好世界" -o hi.mp3 -v female-shaonv --model speech-2.8-hd + python minimax_tts.py "Welcome" -o out.wav -v male-qn-jingying --speed 0.8 --format wav + +Env: MINIMAX_API_KEY (required) +""" + +import os +import sys +import json +import argparse +import requests + +API_KEY = os.getenv("MINIMAX_API_KEY") +API_BASE = os.getenv("MINIMAX_API_BASE", "https://api.minimax.io/v1") + + +def tts( + text: str, + voice_id: str = "male-qn-qingse", + model: str = "speech-2.8-hd", + speed: float = 1.0, + volume: float = 1.0, + pitch: int = 0, + emotion: str = "", + sample_rate: int = 32000, + bitrate: int = 128000, + fmt: str = "mp3", + language_boost: str = "auto", + timeout: int = 120, +) -> bytes: + """Synchronous HTTP TTS. Returns raw audio bytes.""" + if not API_KEY: + raise SystemExit("ERROR: MINIMAX_API_KEY is not set.\n export MINIMAX_API_KEY='your-key'") + + voice_setting = {"voice_id": voice_id, "speed": speed, "vol": volume, "pitch": pitch} + if emotion: + voice_setting["emotion"] = emotion + + payload = { + "model": model, + "text": text, + "stream": False, + "voice_setting": voice_setting, + "audio_setting": { + "sample_rate": sample_rate, + "bitrate": bitrate, + "format": fmt, + "channel": 1, + }, + "language_boost": language_boost, + "output_format": "hex", + } + + resp = requests.post( + f"{API_BASE}/t2a_v2", + headers={ + "Authorization": f"Bearer {API_KEY}", + "Content-Type": "application/json", + }, + json=payload, + timeout=timeout, + ) + resp.raise_for_status() + data = resp.json() + + # Check API-level error + base_resp = data.get("base_resp", {}) + if base_resp.get("status_code", 0) != 0: + raise SystemExit(f"API Error [{base_resp.get('status_code')}]: {base_resp.get('status_msg')}") + + audio_hex = data.get("data", {}).get("audio", "") + if not audio_hex: + raise SystemExit(f"No audio in response: {json.dumps(data, indent=2)}") + + return bytes.fromhex(audio_hex) + + +def main(): + p = argparse.ArgumentParser(description="MiniMax Sync TTS (HTTP)") + p.add_argument("text", help="Text to synthesize (max 10000 chars)") + p.add_argument("-o", "--output", required=True, help="Output file path") + p.add_argument("-v", "--voice", default="male-qn-qingse", help="Voice ID") + p.add_argument("--model", default="speech-2.8-hd", help="Model (default: speech-2.8-hd)") + p.add_argument("--speed", type=float, default=1.0, help="Speed 0.5-2.0") + p.add_argument("--volume", type=float, default=1.0, help="Volume 0.1-10") + p.add_argument("--pitch", type=int, default=0, help="Pitch -12 to 12") + p.add_argument("--emotion", default="", help="Emotion tag (happy/sad/angry/...)") + p.add_argument("--format", default="mp3", dest="fmt", help="Audio format (mp3/wav/flac)") + p.add_argument("--sample-rate", type=int, default=32000, help="Sample rate") + p.add_argument("--lang", default="auto", help="Language boost") + args = p.parse_args() + + os.makedirs(os.path.dirname(args.output) or ".", exist_ok=True) + + audio = tts( + text=args.text, + voice_id=args.voice, + model=args.model, + speed=args.speed, + volume=args.volume, + pitch=args.pitch, + emotion=args.emotion, + fmt=args.fmt, + sample_rate=args.sample_rate, + language_boost=args.lang, + ) + + with open(args.output, "wb") as f: + f.write(audio) + + print(f"OK: {len(audio)} bytes -> {args.output}") + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_video.py b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_video.py new file mode 100644 index 00000000..8fa997c2 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/scripts/minimax_video.py @@ -0,0 +1,183 @@ +#!/usr/bin/env python3 +# SPDX-License-Identifier: MIT +""" +MiniMax Text-to-Video — async generation with polling and download. + +Usage: + python minimax_video.py "A cat playing piano" -o cat.mp4 + python minimax_video.py "Ocean waves [Truck left]" -o waves.mp4 --model MiniMax-Hailuo-2.3 --duration 10 + python minimax_video.py "City skyline at sunset [Push in]" -o city.mp4 --resolution 1080P + +Env: MINIMAX_API_KEY (required) +""" + +import os +import sys +import json +import time +import argparse +import requests + +API_KEY = os.getenv("MINIMAX_API_KEY") +API_BASE = "https://api.minimax.io/v1" + + +def _headers(): + if not API_KEY: + raise SystemExit("ERROR: MINIMAX_API_KEY is not set.\n export MINIMAX_API_KEY='your-key'") + return { + "Authorization": f"Bearer {API_KEY}", + "Content-Type": "application/json", + } + + +def _check_resp(data): + base_resp = data.get("base_resp", {}) + code = base_resp.get("status_code", 0) + if code != 0: + msg = base_resp.get("status_msg", "Unknown error") + raise SystemExit(f"API Error [{code}]: {msg}") + + +def create_task( + prompt: str, + model: str = "MiniMax-Hailuo-2.3", + duration: int = 6, + resolution: str = "768P", + prompt_optimizer: bool = True, +) -> str: + """Submit a video generation task. Returns task_id.""" + payload = { + "model": model, + "prompt": prompt, + "duration": duration, + "resolution": resolution, + "prompt_optimizer": prompt_optimizer, + } + + resp = requests.post( + f"{API_BASE}/video_generation", + headers=_headers(), + json=payload, + timeout=30, + ) + resp.raise_for_status() + data = resp.json() + _check_resp(data) + + task_id = data.get("task_id") + if not task_id: + raise SystemExit(f"No task_id in response: {json.dumps(data, indent=2)}") + return task_id + + +def poll_task(task_id: str, interval: int = 10, max_wait: int = 600) -> str: + """Poll task status until Success. Returns file_id.""" + elapsed = 0 + while elapsed < max_wait: + resp = requests.get( + f"{API_BASE}/query/video_generation", + headers=_headers(), + params={"task_id": task_id}, + timeout=30, + ) + resp.raise_for_status() + data = resp.json() + _check_resp(data) + + status = data.get("status", "") + file_id = data.get("file_id", "") + + if status == "Success": + if not file_id: + raise SystemExit("Task succeeded but no file_id returned") + print(f" Done! file_id={file_id}") + return file_id + elif status == "Fail": + raise SystemExit(f"Video generation failed: {json.dumps(data, indent=2)}") + else: + print(f" [{elapsed}s] Status: {status}...") + time.sleep(interval) + elapsed += interval + + raise SystemExit(f"Timeout after {max_wait}s. task_id={task_id}, check manually.") + + +def download_video(file_id: str, output_path: str): + """Retrieve download URL via file_id and save the video.""" + resp = requests.get( + f"{API_BASE}/files/retrieve", + headers=_headers(), + params={"file_id": file_id}, + timeout=30, + ) + resp.raise_for_status() + data = resp.json() + _check_resp(data) + + download_url = data.get("file", {}).get("download_url", "") + if not download_url: + raise SystemExit(f"No download_url in response: {json.dumps(data, indent=2)}") + + print(f" Downloading from {download_url[:80]}...") + video_resp = requests.get(download_url, timeout=300) + video_resp.raise_for_status() + + os.makedirs(os.path.dirname(output_path) or ".", exist_ok=True) + with open(output_path, "wb") as f: + f.write(video_resp.content) + + print(f"OK: {len(video_resp.content)} bytes -> {output_path}") + + +def generate( + prompt: str, + output_path: str, + model: str = "MiniMax-Hailuo-2.3", + duration: int = 6, + resolution: str = "768P", + prompt_optimizer: bool = True, + poll_interval: int = 10, + max_wait: int = 600, +): + """Full pipeline: create task -> poll -> download.""" + print(f"Creating video task...") + print(f" Model: {model} | Duration: {duration}s | Resolution: {resolution}") + print(f" Prompt: {prompt[:100]}{'...' if len(prompt) > 100 else ''}") + + task_id = create_task(prompt, model, duration, resolution, prompt_optimizer) + print(f" task_id={task_id}") + print(f"Waiting for generation...") + + file_id = poll_task(task_id, poll_interval, max_wait) + download_video(file_id, output_path) + + +def main(): + p = argparse.ArgumentParser(description="MiniMax Text-to-Video") + p.add_argument("prompt", help="Video description (max 2000 chars). Use [Camera Command] for camera control.") + p.add_argument("-o", "--output", required=True, help="Output file path (.mp4)") + p.add_argument("--model", default="MiniMax-Hailuo-2.3", + choices=["MiniMax-Hailuo-2.3", "MiniMax-Hailuo-02", "T2V-01-Director", "T2V-01"], + help="Model (default: MiniMax-Hailuo-2.3)") + p.add_argument("--duration", type=int, default=6, choices=[6, 10], help="Duration in seconds (default: 6)") + p.add_argument("--resolution", default="768P", choices=["720P", "768P", "1080P"], help="Resolution (default: 768P)") + p.add_argument("--no-optimize", action="store_true", help="Disable prompt auto-optimization") + p.add_argument("--poll-interval", type=int, default=10, help="Poll interval in seconds (default: 10)") + p.add_argument("--max-wait", type=int, default=600, help="Max wait time in seconds (default: 600)") + args = p.parse_args() + + generate( + prompt=args.prompt, + output_path=args.output, + model=args.model, + duration=args.duration, + resolution=args.resolution, + prompt_optimizer=not args.no_optimize, + poll_interval=args.poll_interval, + max_wait=args.max_wait, + ) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/templates/generator_template.js b/libs/hexagent_demo/backend/skills/public/frontend-dev/templates/generator_template.js new file mode 100644 index 00000000..ab5cb995 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/templates/generator_template.js @@ -0,0 +1,223 @@ +/** + * ═══════════════════════════════════════════════════════════════════════════ + * P5.JS GENERATIVE ART - BEST PRACTICES + * ═══════════════════════════════════════════════════════════════════════════ + * + * This file shows STRUCTURE and PRINCIPLES for p5.js generative art. + * It does NOT prescribe what art you should create. + * + * Your algorithmic philosophy should guide what you build. + * These are just best practices for how to structure your code. + * + * ═══════════════════════════════════════════════════════════════════════════ + */ + +// ============================================================================ +// 1. PARAMETER ORGANIZATION +// ============================================================================ +// Keep all tunable parameters in one object +// This makes it easy to: +// - Connect to UI controls +// - Reset to defaults +// - Serialize/save configurations + +let params = { + // Define parameters that match YOUR algorithm + // Examples (customize for your art): + // - Counts: how many elements (particles, circles, branches, etc.) + // - Scales: size, speed, spacing + // - Probabilities: likelihood of events + // - Angles: rotation, direction + // - Colors: palette arrays + + seed: 12345, + // define colorPalette as an array -- choose whatever colors you'd like ['#d97757', '#6a9bcc', '#788c5d', '#b0aea5'] + // Add YOUR parameters here based on your algorithm +}; + +// ============================================================================ +// 2. SEEDED RANDOMNESS (Critical for reproducibility) +// ============================================================================ +// ALWAYS use seeded random for Art Blocks-style reproducible output + +function initializeSeed(seed) { + randomSeed(seed); + noiseSeed(seed); + // Now all random() and noise() calls will be deterministic +} + +// ============================================================================ +// 3. P5.JS LIFECYCLE +// ============================================================================ + +function setup() { + createCanvas(800, 800); + + // Initialize seed first + initializeSeed(params.seed); + + // Set up your generative system + // This is where you initialize: + // - Arrays of objects + // - Grid structures + // - Initial positions + // - Starting states + + // For static art: call noLoop() at the end of setup + // For animated art: let draw() keep running +} + +function draw() { + // Option 1: Static generation (runs once, then stops) + // - Generate everything in setup() + // - Call noLoop() in setup() + // - draw() doesn't do much or can be empty + + // Option 2: Animated generation (continuous) + // - Update your system each frame + // - Common patterns: particle movement, growth, evolution + // - Can optionally call noLoop() after N frames + + // Option 3: User-triggered regeneration + // - Use noLoop() by default + // - Call redraw() when parameters change +} + +// ============================================================================ +// 4. CLASS STRUCTURE (When you need objects) +// ============================================================================ +// Use classes when your algorithm involves multiple entities +// Examples: particles, agents, cells, nodes, etc. + +class Entity { + constructor() { + // Initialize entity properties + // Use random() here - it will be seeded + } + + update() { + // Update entity state + // This might involve: + // - Physics calculations + // - Behavioral rules + // - Interactions with neighbors + } + + display() { + // Render the entity + // Keep rendering logic separate from update logic + } +} + +// ============================================================================ +// 5. PERFORMANCE CONSIDERATIONS +// ============================================================================ + +// For large numbers of elements: +// - Pre-calculate what you can +// - Use simple collision detection (spatial hashing if needed) +// - Limit expensive operations (sqrt, trig) when possible +// - Consider using p5 vectors efficiently + +// For smooth animation: +// - Aim for 60fps +// - Profile if things are slow +// - Consider reducing particle counts or simplifying calculations + +// ============================================================================ +// 6. UTILITY FUNCTIONS +// ============================================================================ + +// Color utilities +function hexToRgb(hex) { + const result = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(hex); + return result ? { + r: parseInt(result[1], 16), + g: parseInt(result[2], 16), + b: parseInt(result[3], 16) + } : null; +} + +function colorFromPalette(index) { + return params.colorPalette[index % params.colorPalette.length]; +} + +// Mapping and easing +function mapRange(value, inMin, inMax, outMin, outMax) { + return outMin + (outMax - outMin) * ((value - inMin) / (inMax - inMin)); +} + +function easeInOutCubic(t) { + return t < 0.5 ? 4 * t * t * t : 1 - Math.pow(-2 * t + 2, 3) / 2; +} + +// Constrain to bounds +function wrapAround(value, max) { + if (value < 0) return max; + if (value > max) return 0; + return value; +} + +// ============================================================================ +// 7. PARAMETER UPDATES (Connect to UI) +// ============================================================================ + +function updateParameter(paramName, value) { + params[paramName] = value; + // Decide if you need to regenerate or just update + // Some params can update in real-time, others need full regeneration +} + +function regenerate() { + // Reinitialize your generative system + // Useful when parameters change significantly + initializeSeed(params.seed); + // Then regenerate your system +} + +// ============================================================================ +// 8. COMMON P5.JS PATTERNS +// ============================================================================ + +// Drawing with transparency for trails/fading +function fadeBackground(opacity) { + fill(250, 249, 245, opacity); // brand light with alpha + noStroke(); + rect(0, 0, width, height); +} + +// Using noise for organic variation +function getNoiseValue(x, y, scale = 0.01) { + return noise(x * scale, y * scale); +} + +// Creating vectors from angles +function vectorFromAngle(angle, magnitude = 1) { + return createVector(cos(angle), sin(angle)).mult(magnitude); +} + +// ============================================================================ +// 9. EXPORT FUNCTIONS +// ============================================================================ + +function exportImage() { + saveCanvas('generative-art-' + params.seed, 'png'); +} + +// ============================================================================ +// REMEMBER +// ============================================================================ +// +// These are TOOLS and PRINCIPLES, not a recipe. +// Your algorithmic philosophy should guide WHAT you create. +// This structure helps you create it WELL. +// +// Focus on: +// - Clean, readable code +// - Parameterized for exploration +// - Seeded for reproducibility +// - Performant execution +// +// The art itself is entirely up to you! +// +// ============================================================================ diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/templates/viewer.html b/libs/hexagent_demo/backend/skills/public/frontend-dev/templates/viewer.html new file mode 100644 index 00000000..ed59e5ad --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/templates/viewer.html @@ -0,0 +1,599 @@ + + + + + + + Generative Art Viewer + + + + + + + +
    + +
    + +

    TITLE - EDIT

    +
    SUBHEADER - EDIT
    + + +
    +

    Seed

    + +
    + + +
    + +
    + + +
    +

    Parameters

    + + +
    + +
    + + 5000 +
    +
    + + +
    + +
    + + 0.5 +
    +
    + + +
    + +
    + + 0.005 +
    +
    + + +
    + +
    + + 8 +
    +
    +
    + + +
    +

    Colors

    + + +
    + +
    + + #d97757 +
    +
    + + +
    + +
    + + #6a9bcc +
    +
    + + +
    + +
    + + #788c5d +
    +
    +
    + + +
    +

    Actions

    +
    + +
    +
    +
    + + +
    +
    +
    Initializing generative art...
    +
    +
    +
    + + + + diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/LICENSE.txt b/libs/hexagent_demo/backend/skills/public/mcp-builder/LICENSE.txt new file mode 100644 index 00000000..d6456956 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/LICENSE.txt @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK). +description_zh: "MCP 服务器开发指南，集成外部 API 和服务" +description_en: "Guide for creating MCP servers to integrate external APIs and services" +version: 1.0.0 +license: Complete terms in LICENSE.txt +metadata: + author: codebuddy + url: https://www.codebuddy.cn/docs/ide/Features/Skills +--- + +# MCP Server Development Guide + +## Overview + +Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks. + +--- + +# Process + +## 🚀 High-Level Workflow + +Creating a high-quality MCP server involves four main phases: + +### Phase 1: Deep Research and Planning + +#### 1.1 Understand Modern MCP Design + +**API Coverage vs. Workflow Tools:** +Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage. + +**Tool Naming and Discoverability:** +Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., `github_create_issue`, `github_list_repos`) and action-oriented naming. + +**Context Management:** +Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently. + +**Actionable Error Messages:** +Error messages should guide agents toward solutions with specific suggestions and next steps. + +#### 1.2 Study MCP Protocol Documentation + +**Navigate the MCP specification:** + +Start with the sitemap to find relevant pages: `https://modelcontextprotocol.io/sitemap.xml` + +Then fetch specific pages with `.md` suffix for markdown format (e.g., `https://modelcontextprotocol.io/specification/draft.md`). + +Key pages to review: +- Specification overview and architecture +- Transport mechanisms (streamable HTTP, stdio) +- Tool, resource, and prompt definitions + +#### 1.3 Study Framework Documentation + +**Recommended stack:** +- **Language**: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code, benefiting from its broad usage, static typing and good linting tools) +- **Transport**: Streamable HTTP for remote servers, using stateless JSON (simpler to scale and maintain, as opposed to stateful sessions and streaming responses). stdio for local servers. + +**Load framework documentation:** + +- **MCP Best Practices**: [📋 View Best Practices](./reference/mcp_best_practices.md) - Core guidelines + +**For TypeScript (recommended):** +- **TypeScript SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md` +- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - TypeScript patterns and examples + +**For Python:** +- **Python SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` +- [🐍 Python Guide](./reference/python_mcp_server.md) - Python patterns and examples + +#### 1.4 Plan Your Implementation + +**Understand the API:** +Review the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed. + +**Tool Selection:** +Prioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations. + +--- + +### Phase 2: Implementation + +#### 2.1 Set Up Project Structure + +See language-specific guides for project setup: +- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - Project structure, package.json, tsconfig.json +- [🐍 Python Guide](./reference/python_mcp_server.md) - Module organization, dependencies + +#### 2.2 Implement Core Infrastructure + +Create shared utilities: +- API client with authentication +- Error handling helpers +- Response formatting (JSON/Markdown) +- Pagination support + +#### 2.3 Implement Tools + +For each tool: + +**Input Schema:** +- Use Zod (TypeScript) or Pydantic (Python) +- Include constraints and clear descriptions +- Add examples in field descriptions + +**Output Schema:** +- Define `outputSchema` where possible for structured data +- Use `structuredContent` in tool responses (TypeScript SDK feature) +- Helps clients understand and process tool outputs + +**Tool Description:** +- Concise summary of functionality +- Parameter descriptions +- Return type schema + +**Implementation:** +- Async/await for I/O operations +- Proper error handling with actionable messages +- Support pagination where applicable +- Return both text content and structured data when using modern SDKs + +**Annotations:** +- `readOnlyHint`: true/false +- `destructiveHint`: true/false +- `idempotentHint`: true/false +- `openWorldHint`: true/false + +--- + +### Phase 3: Review and Test + +#### 3.1 Code Quality + +Review for: +- No duplicated code (DRY principle) +- Consistent error handling +- Full type coverage +- Clear tool descriptions + +#### 3.2 Build and Test + +**TypeScript:** +- Run `npm run build` to verify compilation +- Test with MCP Inspector: `npx @modelcontextprotocol/inspector` + +**Python:** +- Verify syntax: `python -m py_compile your_server.py` +- Test with MCP Inspector + +See language-specific guides for detailed testing approaches and quality checklists. + +--- + +### Phase 4: Create Evaluations + +After implementing your MCP server, create comprehensive evaluations to test its effectiveness. + +**Load [✅ Evaluation Guide](./reference/evaluation.md) for complete evaluation guidelines.** + +#### 4.1 Understand Evaluation Purpose + +Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions. + +#### 4.2 Create 10 Evaluation Questions + +To create effective evaluations, follow the process outlined in the evaluation guide: + +1. **Tool Inspection**: List available tools and understand their capabilities +2. **Content Exploration**: Use READ-ONLY operations to explore available data +3. **Question Generation**: Create 10 complex, realistic questions +4. **Answer Verification**: Solve each question yourself to verify answers + +#### 4.3 Evaluation Requirements + +Ensure each question is: +- **Independent**: Not dependent on other questions +- **Read-only**: Only non-destructive operations required +- **Complex**: Requiring multiple tool calls and deep exploration +- **Realistic**: Based on real use cases humans would care about +- **Verifiable**: Single, clear answer that can be verified by string comparison +- **Stable**: Answer won't change over time + +#### 4.4 Output Format + +Create an XML file with this structure: + +```xml + + + Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat? + 3 + + + +``` + +--- + +# Reference Files + +## 📚 Documentation Library + +Load these resources as needed during development: + +### Core MCP Documentation (Load First) +- **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix +- [📋 MCP Best Practices](./reference/mcp_best_practices.md) - Universal MCP guidelines including: + - Server and tool naming conventions + - Response format guidelines (JSON vs Markdown) + - Pagination best practices + - Transport selection (streamable HTTP vs stdio) + - Security and error handling standards + +### SDK Documentation (Load During Phase 1/2) +- **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` +- **TypeScript SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md` + +### Language-Specific Implementation Guides (Load During Phase 2) +- [🐍 Python Implementation Guide](./reference/python_mcp_server.md) - Complete Python/FastMCP guide with: + - Server initialization patterns + - Pydantic model examples + - Tool registration with `@mcp.tool` + - Complete working examples + - Quality checklist + +- [⚡ TypeScript Implementation Guide](./reference/node_mcp_server.md) - Complete TypeScript guide with: + - Project structure + - Zod schema patterns + - Tool registration with `server.registerTool` + - Complete working examples + - Quality checklist + +### Evaluation Guide (Load During Phase 4) +- [✅ Evaluation Guide](./reference/evaluation.md) - Complete evaluation creation guide with: + - Question creation guidelines + - Answer verification strategies + - XML format specifications + - Example questions and answers + - Running an evaluation with the provided scripts diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/evaluation.md b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/evaluation.md new file mode 100644 index 00000000..1beeb205 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/evaluation.md @@ -0,0 +1,602 @@ +# MCP Server Evaluation Guide + +## Overview + +This document provides guidance on creating comprehensive evaluations for MCP servers. Evaluations test whether LLMs can effectively use your MCP server to answer realistic, complex questions using only the tools provided. + +--- + +## Quick Reference + +### Evaluation Requirements +- Create 10 human-readable questions +- Questions must be READ-ONLY, INDEPENDENT, NON-DESTRUCTIVE +- Each question requires multiple tool calls (potentially dozens) +- Answers must be single, verifiable values +- Answers must be STABLE (won't change over time) + +### Output Format +```xml + + + Your question here + Single verifiable answer + + +``` + +--- + +## Purpose of Evaluations + +The measure of quality of an MCP server is NOT how well or comprehensively the server implements tools, but how well these implementations (input/output schemas, docstrings/descriptions, functionality) enable LLMs with no other context and access ONLY to the MCP servers to answer realistic and difficult questions. + +## Evaluation Overview + +Create 10 human-readable questions requiring ONLY READ-ONLY, INDEPENDENT, NON-DESTRUCTIVE, and IDEMPOTENT operations to answer. Each question should be: +- Realistic +- Clear and concise +- Unambiguous +- Complex, requiring potentially dozens of tool calls or steps +- Answerable with a single, verifiable value that you identify in advance + +## Question Guidelines + +### Core Requirements + +1. **Questions MUST be independent** + - Each question should NOT depend on the answer to any other question + - Should not assume prior write operations from processing another question + +2. **Questions MUST require ONLY NON-DESTRUCTIVE AND IDEMPOTENT tool use** + - Should not instruct or require modifying state to arrive at the correct answer + +3. **Questions must be REALISTIC, CLEAR, CONCISE, and COMPLEX** + - Must require another LLM to use multiple (potentially dozens of) tools or steps to answer + +### Complexity and Depth + +4. **Questions must require deep exploration** + - Consider multi-hop questions requiring multiple sub-questions and sequential tool calls + - Each step should benefit from information found in previous questions + +5. **Questions may require extensive paging** + - May need paging through multiple pages of results + - May require querying old data (1-2 years out-of-date) to find niche information + - The questions must be DIFFICULT + +6. **Questions must require deep understanding** + - Rather than surface-level knowledge + - May pose complex ideas as True/False questions requiring evidence + - May use multiple-choice format where LLM must search different hypotheses + +7. **Questions must not be solvable with straightforward keyword search** + - Do not include specific keywords from the target content + - Use synonyms, related concepts, or paraphrases + - Require multiple searches, analyzing multiple related items, extracting context, then deriving the answer + +### Tool Testing + +8. **Questions should stress-test tool return values** + - May elicit tools returning large JSON objects or lists, overwhelming the LLM + - Should require understanding multiple modalities of data: + - IDs and names + - Timestamps and datetimes (months, days, years, seconds) + - File IDs, names, extensions, and mimetypes + - URLs, GIDs, etc. + - Should probe the tool's ability to return all useful forms of data + +9. **Questions should MOSTLY reflect real human use cases** + - The kinds of information retrieval tasks that HUMANS assisted by an LLM would care about + +10. **Questions may require dozens of tool calls** + - This challenges LLMs with limited context + - Encourages MCP server tools to reduce information returned + +11. **Include ambiguous questions** + - May be ambiguous OR require difficult decisions on which tools to call + - Force the LLM to potentially make mistakes or misinterpret + - Ensure that despite AMBIGUITY, there is STILL A SINGLE VERIFIABLE ANSWER + +### Stability + +12. **Questions must be designed so the answer DOES NOT CHANGE** + - Do not ask questions that rely on "current state" which is dynamic + - For example, do not count: + - Number of reactions to a post + - Number of replies to a thread + - Number of members in a channel + +13. **DO NOT let the MCP server RESTRICT the kinds of questions you create** + - Create challenging and complex questions + - Some may not be solvable with the available MCP server tools + - Questions may require specific output formats (datetime vs. epoch time, JSON vs. MARKDOWN) + - Questions may require dozens of tool calls to complete + +## Answer Guidelines + +### Verification + +1. **Answers must be VERIFIABLE via direct string comparison** + - If the answer can be re-written in many formats, clearly specify the output format in the QUESTION + - Examples: "Use YYYY/MM/DD.", "Respond True or False.", "Answer A, B, C, or D and nothing else." + - Answer should be a single VERIFIABLE value such as: + - User ID, user name, display name, first name, last name + - Channel ID, channel name + - Message ID, string + - URL, title + - Numerical quantity + - Timestamp, datetime + - Boolean (for True/False questions) + - Email address, phone number + - File ID, file name, file extension + - Multiple choice answer + - Answers must not require special formatting or complex, structured output + - Answer will be verified using DIRECT STRING COMPARISON + +### Readability + +2. **Answers should generally prefer HUMAN-READABLE formats** + - Examples: names, first name, last name, datetime, file name, message string, URL, yes/no, true/false, a/b/c/d + - Rather than opaque IDs (though IDs are acceptable) + - The VAST MAJORITY of answers should be human-readable + +### Stability + +3. **Answers must be STABLE/STATIONARY** + - Look at old content (e.g., conversations that have ended, projects that have launched, questions answered) + - Create QUESTIONS based on "closed" concepts that will always return the same answer + - Questions may ask to consider a fixed time window to insulate from non-stationary answers + - Rely on context UNLIKELY to change + - Example: if finding a paper name, be SPECIFIC enough so answer is not confused with papers published later + +4. **Answers must be CLEAR and UNAMBIGUOUS** + - Questions must be designed so there is a single, clear answer + - Answer can be derived from using the MCP server tools + +### Diversity + +5. **Answers must be DIVERSE** + - Answer should be a single VERIFIABLE value in diverse modalities and formats + - User concept: user ID, user name, display name, first name, last name, email address, phone number + - Channel concept: channel ID, channel name, channel topic + - Message concept: message ID, message string, timestamp, month, day, year + +6. **Answers must NOT be complex structures** + - Not a list of values + - Not a complex object + - Not a list of IDs or strings + - Not natural language text + - UNLESS the answer can be straightforwardly verified using DIRECT STRING COMPARISON + - And can be realistically reproduced + - It should be unlikely that an LLM would return the same list in any other order or format + +## Evaluation Process + +### Step 1: Documentation Inspection + +Read the documentation of the target API to understand: +- Available endpoints and functionality +- If ambiguity exists, fetch additional information from the web +- Parallelize this step AS MUCH AS POSSIBLE +- Ensure each subagent is ONLY examining documentation from the file system or on the web + +### Step 2: Tool Inspection + +List the tools available in the MCP server: +- Inspect the MCP server directly +- Understand input/output schemas, docstrings, and descriptions +- WITHOUT calling the tools themselves at this stage + +### Step 3: Developing Understanding + +Repeat steps 1 & 2 until you have a good understanding: +- Iterate multiple times +- Think about the kinds of tasks you want to create +- Refine your understanding +- At NO stage should you READ the code of the MCP server implementation itself +- Use your intuition and understanding to create reasonable, realistic, but VERY challenging tasks + +### Step 4: Read-Only Content Inspection + +After understanding the API and tools, USE the MCP server tools: +- Inspect content using READ-ONLY and NON-DESTRUCTIVE operations ONLY +- Goal: identify specific content (e.g., users, channels, messages, projects, tasks) for creating realistic questions +- Should NOT call any tools that modify state +- Will NOT read the code of the MCP server implementation itself +- Parallelize this step with individual sub-agents pursuing independent explorations +- Ensure each subagent is only performing READ-ONLY, NON-DESTRUCTIVE, and IDEMPOTENT operations +- BE CAREFUL: SOME TOOLS may return LOTS OF DATA which would cause you to run out of CONTEXT +- Make INCREMENTAL, SMALL, AND TARGETED tool calls for exploration +- In all tool call requests, use the `limit` parameter to limit results (<10) +- Use pagination + +### Step 5: Task Generation + +After inspecting the content, create 10 human-readable questions: +- An LLM should be able to answer these with the MCP server +- Follow all question and answer guidelines above + +## Output Format + +Each QA pair consists of a question and an answer. The output should be an XML file with this structure: + +```xml + + + Find the project created in Q2 2024 with the highest number of completed tasks. What is the project name? + Website Redesign + + + Search for issues labeled as "bug" that were closed in March 2024. Which user closed the most issues? Provide their username. + sarah_dev + + + Look for pull requests that modified files in the /api directory and were merged between January 1 and January 31, 2024. How many different contributors worked on these PRs? + 7 + + + Find the repository with the most stars that was created before 2023. What is the repository name? + data-pipeline + + +``` + +## Evaluation Examples + +### Good Questions + +**Example 1: Multi-hop question requiring deep exploration (GitHub MCP)** +```xml + + Find the repository that was archived in Q3 2023 and had previously been the most forked project in the organization. What was the primary programming language used in that repository? + Python + +``` + +This question is good because: +- Requires multiple searches to find archived repositories +- Needs to identify which had the most forks before archival +- Requires examining repository details for the language +- Answer is a simple, verifiable value +- Based on historical (closed) data that won't change + +**Example 2: Requires understanding context without keyword matching (Project Management MCP)** +```xml + + Locate the initiative focused on improving customer onboarding that was completed in late 2023. The project lead created a retrospective document after completion. What was the lead's role title at that time? + Product Manager + +``` + +This question is good because: +- Doesn't use specific project name ("initiative focused on improving customer onboarding") +- Requires finding completed projects from specific timeframe +- Needs to identify the project lead and their role +- Requires understanding context from retrospective documents +- Answer is human-readable and stable +- Based on completed work (won't change) + +**Example 3: Complex aggregation requiring multiple steps (Issue Tracker MCP)** +```xml + + Among all bugs reported in January 2024 that were marked as critical priority, which assignee resolved the highest percentage of their assigned bugs within 48 hours? Provide the assignee's username. + alex_eng + +``` + +This question is good because: +- Requires filtering bugs by date, priority, and status +- Needs to group by assignee and calculate resolution rates +- Requires understanding timestamps to determine 48-hour windows +- Tests pagination (potentially many bugs to process) +- Answer is a single username +- Based on historical data from specific time period + +**Example 4: Requires synthesis across multiple data types (CRM MCP)** +```xml + + Find the account that upgraded from the Starter to Enterprise plan in Q4 2023 and had the highest annual contract value. What industry does this account operate in? + Healthcare + +``` + +This question is good because: +- Requires understanding subscription tier changes +- Needs to identify upgrade events in specific timeframe +- Requires comparing contract values +- Must access account industry information +- Answer is simple and verifiable +- Based on completed historical transactions + +### Poor Questions + +**Example 1: Answer changes over time** +```xml + + How many open issues are currently assigned to the engineering team? + 47 + +``` + +This question is poor because: +- The answer will change as issues are created, closed, or reassigned +- Not based on stable/stationary data +- Relies on "current state" which is dynamic + +**Example 2: Too easy with keyword search** +```xml + + Find the pull request with title "Add authentication feature" and tell me who created it. + developer123 + +``` + +This question is poor because: +- Can be solved with a straightforward keyword search for exact title +- Doesn't require deep exploration or understanding +- No synthesis or analysis needed + +**Example 3: Ambiguous answer format** +```xml + + List all the repositories that have Python as their primary language. + repo1, repo2, repo3, data-pipeline, ml-tools + +``` + +This question is poor because: +- Answer is a list that could be returned in any order +- Difficult to verify with direct string comparison +- LLM might format differently (JSON array, comma-separated, newline-separated) +- Better to ask for a specific aggregate (count) or superlative (most stars) + +## Verification Process + +After creating evaluations: + +1. **Examine the XML file** to understand the schema +2. **Load each task instruction** and in parallel using the MCP server and tools, identify the correct answer by attempting to solve the task YOURSELF +3. **Flag any operations** that require WRITE or DESTRUCTIVE operations +4. **Accumulate all CORRECT answers** and replace any incorrect answers in the document +5. **Remove any ``** that require WRITE or DESTRUCTIVE operations + +Remember to parallelize solving tasks to avoid running out of context, then accumulate all answers and make changes to the file at the end. + +## Tips for Creating Quality Evaluations + +1. **Think Hard and Plan Ahead** before generating tasks +2. **Parallelize Where Opportunity Arises** to speed up the process and manage context +3. **Focus on Realistic Use Cases** that humans would actually want to accomplish +4. **Create Challenging Questions** that test the limits of the MCP server's capabilities +5. **Ensure Stability** by using historical data and closed concepts +6. **Verify Answers** by solving the questions yourself using the MCP server tools +7. **Iterate and Refine** based on what you learn during the process + +--- + +# Running Evaluations + +After creating your evaluation file, you can use the provided evaluation harness to test your MCP server. + +## Setup + +1. **Install Dependencies** + + ```bash + pip install -r scripts/requirements.txt + ``` + + Or install manually: + ```bash + pip install anthropic mcp + ``` + +2. **Set API Key** + + ```bash + export ANTHROPIC_API_KEY=your_api_key_here + ``` + +## Evaluation File Format + +Evaluation files use XML format with `` elements: + +```xml + + + Find the project created in Q2 2024 with the highest number of completed tasks. What is the project name? + Website Redesign + + + Search for issues labeled as "bug" that were closed in March 2024. Which user closed the most issues? Provide their username. + sarah_dev + + +``` + +## Running Evaluations + +The evaluation script (`scripts/evaluation.py`) supports three transport types: + +**Important:** +- **stdio transport**: The evaluation script automatically launches and manages the MCP server process for you. Do not run the server manually. +- **sse/http transports**: You must start the MCP server separately before running the evaluation. The script connects to the already-running server at the specified URL. + +### 1. Local STDIO Server + +For locally-run MCP servers (script launches the server automatically): + +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a my_mcp_server.py \ + evaluation.xml +``` + +With environment variables: +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a my_mcp_server.py \ + -e API_KEY=abc123 \ + -e DEBUG=true \ + evaluation.xml +``` + +### 2. Server-Sent Events (SSE) + +For SSE-based MCP servers (you must start the server first): + +```bash +python scripts/evaluation.py \ + -t sse \ + -u https://example.com/mcp \ + -H "Authorization: Bearer token123" \ + -H "X-Custom-Header: value" \ + evaluation.xml +``` + +### 3. HTTP (Streamable HTTP) + +For HTTP-based MCP servers (you must start the server first): + +```bash +python scripts/evaluation.py \ + -t http \ + -u https://example.com/mcp \ + -H "Authorization: Bearer token123" \ + evaluation.xml +``` + +## Command-Line Options + +``` +usage: evaluation.py [-h] [-t {stdio,sse,http}] [-m MODEL] [-c COMMAND] + [-a ARGS [ARGS ...]] [-e ENV [ENV ...]] [-u URL] + [-H HEADERS [HEADERS ...]] [-o OUTPUT] + eval_file + +positional arguments: + eval_file Path to evaluation XML file + +optional arguments: + -h, --help Show help message + -t, --transport Transport type: stdio, sse, or http (default: stdio) + -m, --model Claude model to use (default: claude-3-7-sonnet-20250219) + -o, --output Output file for report (default: print to stdout) + +stdio options: + -c, --command Command to run MCP server (e.g., python, node) + -a, --args Arguments for the command (e.g., server.py) + -e, --env Environment variables in KEY=VALUE format + +sse/http options: + -u, --url MCP server URL + -H, --header HTTP headers in 'Key: Value' format +``` + +## Output + +The evaluation script generates a detailed report including: + +- **Summary Statistics**: + - Accuracy (correct/total) + - Average task duration + - Average tool calls per task + - Total tool calls + +- **Per-Task Results**: + - Prompt and expected response + - Actual response from the agent + - Whether the answer was correct (✅/❌) + - Duration and tool call details + - Agent's summary of its approach + - Agent's feedback on the tools + +### Save Report to File + +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a my_server.py \ + -o evaluation_report.md \ + evaluation.xml +``` + +## Complete Example Workflow + +Here's a complete example of creating and running an evaluation: + +1. **Create your evaluation file** (`my_evaluation.xml`): + +```xml + + + Find the user who created the most issues in January 2024. What is their username? + alice_developer + + + Among all pull requests merged in Q1 2024, which repository had the highest number? Provide the repository name. + backend-api + + + Find the project that was completed in December 2023 and had the longest duration from start to finish. How many days did it take? + 127 + + +``` + +2. **Install dependencies**: + +```bash +pip install -r scripts/requirements.txt +export ANTHROPIC_API_KEY=your_api_key +``` + +3. **Run evaluation**: + +```bash +python scripts/evaluation.py \ + -t stdio \ + -c python \ + -a github_mcp_server.py \ + -e GITHUB_TOKEN=ghp_xxx \ + -o github_eval_report.md \ + my_evaluation.xml +``` + +4. **Review the report** in `github_eval_report.md` to: + - See which questions passed/failed + - Read the agent's feedback on your tools + - Identify areas for improvement + - Iterate on your MCP server design + +## Troubleshooting + +### Connection Errors + +If you get connection errors: +- **STDIO**: Verify the command and arguments are correct +- **SSE/HTTP**: Check the URL is accessible and headers are correct +- Ensure any required API keys are set in environment variables or headers + +### Low Accuracy + +If many evaluations fail: +- Review the agent's feedback for each task +- Check if tool descriptions are clear and comprehensive +- Verify input parameters are well-documented +- Consider whether tools return too much or too little data +- Ensure error messages are actionable + +### Timeout Issues + +If tasks are timing out: +- Use a more capable model (e.g., `claude-3-7-sonnet-20250219`) +- Check if tools are returning too much data +- Verify pagination is working correctly +- Consider simplifying complex questions diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/mcp_best_practices.md b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/mcp_best_practices.md new file mode 100644 index 00000000..b9d343cc --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/mcp_best_practices.md @@ -0,0 +1,249 @@ +# MCP Server Best Practices + +## Quick Reference + +### Server Naming +- **Python**: `{service}_mcp` (e.g., `slack_mcp`) +- **Node/TypeScript**: `{service}-mcp-server` (e.g., `slack-mcp-server`) + +### Tool Naming +- Use snake_case with service prefix +- Format: `{service}_{action}_{resource}` +- Example: `slack_send_message`, `github_create_issue` + +### Response Formats +- Support both JSON and Markdown formats +- JSON for programmatic processing +- Markdown for human readability + +### Pagination +- Always respect `limit` parameter +- Return `has_more`, `next_offset`, `total_count` +- Default to 20-50 items + +### Transport +- **Streamable HTTP**: For remote servers, multi-client scenarios +- **stdio**: For local integrations, command-line tools +- Avoid SSE (deprecated in favor of streamable HTTP) + +--- + +## Server Naming Conventions + +Follow these standardized naming patterns: + +**Python**: Use format `{service}_mcp` (lowercase with underscores) +- Examples: `slack_mcp`, `github_mcp`, `jira_mcp` + +**Node/TypeScript**: Use format `{service}-mcp-server` (lowercase with hyphens) +- Examples: `slack-mcp-server`, `github-mcp-server`, `jira-mcp-server` + +The name should be general, descriptive of the service being integrated, easy to infer from the task description, and without version numbers. + +--- + +## Tool Naming and Design + +### Tool Naming + +1. **Use snake_case**: `search_users`, `create_project`, `get_channel_info` +2. **Include service prefix**: Anticipate that your MCP server may be used alongside other MCP servers + - Use `slack_send_message` instead of just `send_message` + - Use `github_create_issue` instead of just `create_issue` +3. **Be action-oriented**: Start with verbs (get, list, search, create, etc.) +4. **Be specific**: Avoid generic names that could conflict with other servers + +### Tool Design + +- Tool descriptions must narrowly and unambiguously describe functionality +- Descriptions must precisely match actual functionality +- Provide tool annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) +- Keep tool operations focused and atomic + +--- + +## Response Formats + +All tools that return data should support multiple formats: + +### JSON Format (`response_format="json"`) +- Machine-readable structured data +- Include all available fields and metadata +- Consistent field names and types +- Use for programmatic processing + +### Markdown Format (`response_format="markdown"`, typically default) +- Human-readable formatted text +- Use headers, lists, and formatting for clarity +- Convert timestamps to human-readable format +- Show display names with IDs in parentheses +- Omit verbose metadata + +--- + +## Pagination + +For tools that list resources: + +- **Always respect the `limit` parameter** +- **Implement pagination**: Use `offset` or cursor-based pagination +- **Return pagination metadata**: Include `has_more`, `next_offset`/`next_cursor`, `total_count` +- **Never load all results into memory**: Especially important for large datasets +- **Default to reasonable limits**: 20-50 items is typical + +Example pagination response: +```json +{ + "total": 150, + "count": 20, + "offset": 0, + "items": [...], + "has_more": true, + "next_offset": 20 +} +``` + +--- + +## Transport Options + +### Streamable HTTP + +**Best for**: Remote servers, web services, multi-client scenarios + +**Characteristics**: +- Bidirectional communication over HTTP +- Supports multiple simultaneous clients +- Can be deployed as a web service +- Enables server-to-client notifications + +**Use when**: +- Serving multiple clients simultaneously +- Deploying as a cloud service +- Integration with web applications + +### stdio + +**Best for**: Local integrations, command-line tools + +**Characteristics**: +- Standard input/output stream communication +- Simple setup, no network configuration needed +- Runs as a subprocess of the client + +**Use when**: +- Building tools for local development environments +- Integrating with desktop applications +- Single-user, single-session scenarios + +**Note**: stdio servers should NOT log to stdout (use stderr for logging) + +### Transport Selection + +| Criterion | stdio | Streamable HTTP | +|-----------|-------|-----------------| +| **Deployment** | Local | Remote | +| **Clients** | Single | Multiple | +| **Complexity** | Low | Medium | +| **Real-time** | No | Yes | + +--- + +## Security Best Practices + +### Authentication and Authorization + +**OAuth 2.1**: +- Use secure OAuth 2.1 with certificates from recognized authorities +- Validate access tokens before processing requests +- Only accept tokens specifically intended for your server + +**API Keys**: +- Store API keys in environment variables, never in code +- Validate keys on server startup +- Provide clear error messages when authentication fails + +### Input Validation + +- Sanitize file paths to prevent directory traversal +- Validate URLs and external identifiers +- Check parameter sizes and ranges +- Prevent command injection in system calls +- Use schema validation (Pydantic/Zod) for all inputs + +### Error Handling + +- Don't expose internal errors to clients +- Log security-relevant errors server-side +- Provide helpful but not revealing error messages +- Clean up resources after errors + +### DNS Rebinding Protection + +For streamable HTTP servers running locally: +- Enable DNS rebinding protection +- Validate the `Origin` header on all incoming connections +- Bind to `127.0.0.1` rather than `0.0.0.0` + +--- + +## Tool Annotations + +Provide annotations to help clients understand tool behavior: + +| Annotation | Type | Default | Description | +|-----------|------|---------|-------------| +| `readOnlyHint` | boolean | false | Tool does not modify its environment | +| `destructiveHint` | boolean | true | Tool may perform destructive updates | +| `idempotentHint` | boolean | false | Repeated calls with same args have no additional effect | +| `openWorldHint` | boolean | true | Tool interacts with external entities | + +**Important**: Annotations are hints, not security guarantees. Clients should not make security-critical decisions based solely on annotations. + +--- + +## Error Handling + +- Use standard JSON-RPC error codes +- Report tool errors within result objects (not protocol-level errors) +- Provide helpful, specific error messages with suggested next steps +- Don't expose internal implementation details +- Clean up resources properly on errors + +Example error handling: +```typescript +try { + const result = performOperation(); + return { content: [{ type: "text", text: result }] }; +} catch (error) { + return { + isError: true, + content: [{ + type: "text", + text: `Error: ${error.message}. Try using filter='active_only' to reduce results.` + }] + }; +} +``` + +--- + +## Testing Requirements + +Comprehensive testing should cover: + +- **Functional testing**: Verify correct execution with valid/invalid inputs +- **Integration testing**: Test interaction with external systems +- **Security testing**: Validate auth, input sanitization, rate limiting +- **Performance testing**: Check behavior under load, timeouts +- **Error handling**: Ensure proper error reporting and cleanup + +--- + +## Documentation Requirements + +- Provide clear documentation of all tools and capabilities +- Include working examples (at least 3 per major feature) +- Document security considerations +- Specify required permissions and access levels +- Document rate limits and performance characteristics diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/node_mcp_server.md b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/node_mcp_server.md new file mode 100644 index 00000000..bc5561d4 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/node_mcp_server.md @@ -0,0 +1,970 @@ +# Node/TypeScript MCP Server Implementation Guide + +## Overview + +This document provides Node/TypeScript-specific best practices and examples for implementing MCP servers using the MCP TypeScript SDK. It covers project structure, server setup, tool registration patterns, input validation with Zod, error handling, and complete working examples. + +--- + +## Quick Reference + +### Key Imports +```typescript +import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; +import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js"; +import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; +import express from "express"; +import { z } from "zod"; +``` + +### Server Initialization +```typescript +const server = new McpServer({ + name: "service-mcp-server", + version: "1.0.0" +}); +``` + +### Tool Registration Pattern +```typescript +server.registerTool( + "tool_name", + { + title: "Tool Display Name", + description: "What the tool does", + inputSchema: { param: z.string() }, + outputSchema: { result: z.string() } + }, + async ({ param }) => { + const output = { result: `Processed: ${param}` }; + return { + content: [{ type: "text", text: JSON.stringify(output) }], + structuredContent: output // Modern pattern for structured data + }; + } +); +``` + +--- + +## MCP TypeScript SDK + +The official MCP TypeScript SDK provides: +- `McpServer` class for server initialization +- `registerTool` method for tool registration +- Zod schema integration for runtime input validation +- Type-safe tool handler implementations + +**IMPORTANT - Use Modern APIs Only:** +- **DO use**: `server.registerTool()`, `server.registerResource()`, `server.registerPrompt()` +- **DO NOT use**: Old deprecated APIs such as `server.tool()`, `server.setRequestHandler(ListToolsRequestSchema, ...)`, or manual handler registration +- The `register*` methods provide better type safety, automatic schema handling, and are the recommended approach + +See the MCP SDK documentation in the references for complete details. + +## Server Naming Convention + +Node/TypeScript MCP servers must follow this naming pattern: +- **Format**: `{service}-mcp-server` (lowercase with hyphens) +- **Examples**: `github-mcp-server`, `jira-mcp-server`, `stripe-mcp-server` + +The name should be: +- General (not tied to specific features) +- Descriptive of the service/API being integrated +- Easy to infer from the task description +- Without version numbers or dates + +## Project Structure + +Create the following structure for Node/TypeScript MCP servers: + +``` +{service}-mcp-server/ +├── package.json +├── tsconfig.json +├── README.md +├── src/ +│ ├── index.ts # Main entry point with McpServer initialization +│ ├── types.ts # TypeScript type definitions and interfaces +│ ├── tools/ # Tool implementations (one file per domain) +│ ├── services/ # API clients and shared utilities +│ ├── schemas/ # Zod validation schemas +│ └── constants.ts # Shared constants (API_URL, CHARACTER_LIMIT, etc.) +└── dist/ # Built JavaScript files (entry point: dist/index.js) +``` + +## Tool Implementation + +### Tool Naming + +Use snake_case for tool names (e.g., "search_users", "create_project", "get_channel_info") with clear, action-oriented names. + +**Avoid Naming Conflicts**: Include the service context to prevent overlaps: +- Use "slack_send_message" instead of just "send_message" +- Use "github_create_issue" instead of just "create_issue" +- Use "asana_list_tasks" instead of just "list_tasks" + +### Tool Structure + +Tools are registered using the `registerTool` method with the following requirements: +- Use Zod schemas for runtime input validation and type safety +- The `description` field must be explicitly provided - JSDoc comments are NOT automatically extracted +- Explicitly provide `title`, `description`, `inputSchema`, and `annotations` +- The `inputSchema` must be a Zod schema object (not a JSON schema) +- Type all parameters and return values explicitly + +```typescript +import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; +import { z } from "zod"; + +const server = new McpServer({ + name: "example-mcp", + version: "1.0.0" +}); + +// Zod schema for input validation +const UserSearchInputSchema = z.object({ + query: z.string() + .min(2, "Query must be at least 2 characters") + .max(200, "Query must not exceed 200 characters") + .describe("Search string to match against names/emails"), + limit: z.number() + .int() + .min(1) + .max(100) + .default(20) + .describe("Maximum results to return"), + offset: z.number() + .int() + .min(0) + .default(0) + .describe("Number of results to skip for pagination"), + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format: 'markdown' for human-readable or 'json' for machine-readable") +}).strict(); + +// Type definition from Zod schema +type UserSearchInput = z.infer; + +server.registerTool( + "example_search_users", + { + title: "Search Example Users", + description: `Search for users in the Example system by name, email, or team. + +This tool searches across all user profiles in the Example platform, supporting partial matches and various search filters. It does NOT create or modify users, only searches existing ones. + +Args: + - query (string): Search string to match against names/emails + - limit (number): Maximum results to return, between 1-100 (default: 20) + - offset (number): Number of results to skip for pagination (default: 0) + - response_format ('markdown' | 'json'): Output format (default: 'markdown') + +Returns: + For JSON format: Structured data with schema: + { + "total": number, // Total number of matches found + "count": number, // Number of results in this response + "offset": number, // Current pagination offset + "users": [ + { + "id": string, // User ID (e.g., "U123456789") + "name": string, // Full name (e.g., "John Doe") + "email": string, // Email address + "team": string, // Team name (optional) + "active": boolean // Whether user is active + } + ], + "has_more": boolean, // Whether more results are available + "next_offset": number // Offset for next page (if has_more is true) + } + +Examples: + - Use when: "Find all marketing team members" -> params with query="team:marketing" + - Use when: "Search for John's account" -> params with query="john" + - Don't use when: You need to create a user (use example_create_user instead) + +Error Handling: + - Returns "Error: Rate limit exceeded" if too many requests (429 status) + - Returns "No users found matching ''" if search returns empty`, + inputSchema: UserSearchInputSchema, + annotations: { + readOnlyHint: true, + destructiveHint: false, + idempotentHint: true, + openWorldHint: true + } + }, + async (params: UserSearchInput) => { + try { + // Input validation is handled by Zod schema + // Make API request using validated parameters + const data = await makeApiRequest( + "users/search", + "GET", + undefined, + { + q: params.query, + limit: params.limit, + offset: params.offset + } + ); + + const users = data.users || []; + const total = data.total || 0; + + if (!users.length) { + return { + content: [{ + type: "text", + text: `No users found matching '${params.query}'` + }] + }; + } + + // Prepare structured output + const output = { + total, + count: users.length, + offset: params.offset, + users: users.map((user: any) => ({ + id: user.id, + name: user.name, + email: user.email, + ...(user.team ? { team: user.team } : {}), + active: user.active ?? true + })), + has_more: total > params.offset + users.length, + ...(total > params.offset + users.length ? { + next_offset: params.offset + users.length + } : {}) + }; + + // Format text representation based on requested format + let textContent: string; + if (params.response_format === ResponseFormat.MARKDOWN) { + const lines = [`# User Search Results: '${params.query}'`, "", + `Found ${total} users (showing ${users.length})`, ""]; + for (const user of users) { + lines.push(`## ${user.name} (${user.id})`); + lines.push(`- **Email**: ${user.email}`); + if (user.team) lines.push(`- **Team**: ${user.team}`); + lines.push(""); + } + textContent = lines.join("\n"); + } else { + textContent = JSON.stringify(output, null, 2); + } + + return { + content: [{ type: "text", text: textContent }], + structuredContent: output // Modern pattern for structured data + }; + } catch (error) { + return { + content: [{ + type: "text", + text: handleApiError(error) + }] + }; + } + } +); +``` + +## Zod Schemas for Input Validation + +Zod provides runtime type validation: + +```typescript +import { z } from "zod"; + +// Basic schema with validation +const CreateUserSchema = z.object({ + name: z.string() + .min(1, "Name is required") + .max(100, "Name must not exceed 100 characters"), + email: z.string() + .email("Invalid email format"), + age: z.number() + .int("Age must be a whole number") + .min(0, "Age cannot be negative") + .max(150, "Age cannot be greater than 150") +}).strict(); // Use .strict() to forbid extra fields + +// Enums +enum ResponseFormat { + MARKDOWN = "markdown", + JSON = "json" +} + +const SearchSchema = z.object({ + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format") +}); + +// Optional fields with defaults +const PaginationSchema = z.object({ + limit: z.number() + .int() + .min(1) + .max(100) + .default(20) + .describe("Maximum results to return"), + offset: z.number() + .int() + .min(0) + .default(0) + .describe("Number of results to skip") +}); +``` + +## Response Format Options + +Support multiple output formats for flexibility: + +```typescript +enum ResponseFormat { + MARKDOWN = "markdown", + JSON = "json" +} + +const inputSchema = z.object({ + query: z.string(), + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format: 'markdown' for human-readable or 'json' for machine-readable") +}); +``` + +**Markdown format**: +- Use headers, lists, and formatting for clarity +- Convert timestamps to human-readable format +- Show display names with IDs in parentheses +- Omit verbose metadata +- Group related information logically + +**JSON format**: +- Return complete, structured data suitable for programmatic processing +- Include all available fields and metadata +- Use consistent field names and types + +## Pagination Implementation + +For tools that list resources: + +```typescript +const ListSchema = z.object({ + limit: z.number().int().min(1).max(100).default(20), + offset: z.number().int().min(0).default(0) +}); + +async function listItems(params: z.infer) { + const data = await apiRequest(params.limit, params.offset); + + const response = { + total: data.total, + count: data.items.length, + offset: params.offset, + items: data.items, + has_more: data.total > params.offset + data.items.length, + next_offset: data.total > params.offset + data.items.length + ? params.offset + data.items.length + : undefined + }; + + return JSON.stringify(response, null, 2); +} +``` + +## Character Limits and Truncation + +Add a CHARACTER_LIMIT constant to prevent overwhelming responses: + +```typescript +// At module level in constants.ts +export const CHARACTER_LIMIT = 25000; // Maximum response size in characters + +async function searchTool(params: SearchInput) { + let result = generateResponse(data); + + // Check character limit and truncate if needed + if (result.length > CHARACTER_LIMIT) { + const truncatedData = data.slice(0, Math.max(1, data.length / 2)); + response.data = truncatedData; + response.truncated = true; + response.truncation_message = + `Response truncated from ${data.length} to ${truncatedData.length} items. ` + + `Use 'offset' parameter or add filters to see more results.`; + result = JSON.stringify(response, null, 2); + } + + return result; +} +``` + +## Error Handling + +Provide clear, actionable error messages: + +```typescript +import axios, { AxiosError } from "axios"; + +function handleApiError(error: unknown): string { + if (error instanceof AxiosError) { + if (error.response) { + switch (error.response.status) { + case 404: + return "Error: Resource not found. Please check the ID is correct."; + case 403: + return "Error: Permission denied. You don't have access to this resource."; + case 429: + return "Error: Rate limit exceeded. Please wait before making more requests."; + default: + return `Error: API request failed with status ${error.response.status}`; + } + } else if (error.code === "ECONNABORTED") { + return "Error: Request timed out. Please try again."; + } + } + return `Error: Unexpected error occurred: ${error instanceof Error ? error.message : String(error)}`; +} +``` + +## Shared Utilities + +Extract common functionality into reusable functions: + +```typescript +// Shared API request function +async function makeApiRequest( + endpoint: string, + method: "GET" | "POST" | "PUT" | "DELETE" = "GET", + data?: any, + params?: any +): Promise { + try { + const response = await axios({ + method, + url: `${API_BASE_URL}/${endpoint}`, + data, + params, + timeout: 30000, + headers: { + "Content-Type": "application/json", + "Accept": "application/json" + } + }); + return response.data; + } catch (error) { + throw error; + } +} +``` + +## Async/Await Best Practices + +Always use async/await for network requests and I/O operations: + +```typescript +// Good: Async network request +async function fetchData(resourceId: string): Promise { + const response = await axios.get(`${API_URL}/resource/${resourceId}`); + return response.data; +} + +// Bad: Promise chains +function fetchData(resourceId: string): Promise { + return axios.get(`${API_URL}/resource/${resourceId}`) + .then(response => response.data); // Harder to read and maintain +} +``` + +## TypeScript Best Practices + +1. **Use Strict TypeScript**: Enable strict mode in tsconfig.json +2. **Define Interfaces**: Create clear interface definitions for all data structures +3. **Avoid `any`**: Use proper types or `unknown` instead of `any` +4. **Zod for Runtime Validation**: Use Zod schemas to validate external data +5. **Type Guards**: Create type guard functions for complex type checking +6. **Error Handling**: Always use try-catch with proper error type checking +7. **Null Safety**: Use optional chaining (`?.`) and nullish coalescing (`??`) + +```typescript +// Good: Type-safe with Zod and interfaces +interface UserResponse { + id: string; + name: string; + email: string; + team?: string; + active: boolean; +} + +const UserSchema = z.object({ + id: z.string(), + name: z.string(), + email: z.string().email(), + team: z.string().optional(), + active: z.boolean() +}); + +type User = z.infer; + +async function getUser(id: string): Promise { + const data = await apiCall(`/users/${id}`); + return UserSchema.parse(data); // Runtime validation +} + +// Bad: Using any +async function getUser(id: string): Promise { + return await apiCall(`/users/${id}`); // No type safety +} +``` + +## Package Configuration + +### package.json + +```json +{ + "name": "{service}-mcp-server", + "version": "1.0.0", + "description": "MCP server for {Service} API integration", + "type": "module", + "main": "dist/index.js", + "scripts": { + "start": "node dist/index.js", + "dev": "tsx watch src/index.ts", + "build": "tsc", + "clean": "rm -rf dist" + }, + "engines": { + "node": ">=18" + }, + "dependencies": { + "@modelcontextprotocol/sdk": "^1.6.1", + "axios": "^1.7.9", + "zod": "^3.23.8" + }, + "devDependencies": { + "@types/node": "^22.10.0", + "tsx": "^4.19.2", + "typescript": "^5.7.2" + } +} +``` + +### tsconfig.json + +```json +{ + "compilerOptions": { + "target": "ES2022", + "module": "Node16", + "moduleResolution": "Node16", + "lib": ["ES2022"], + "outDir": "./dist", + "rootDir": "./src", + "strict": true, + "esModuleInterop": true, + "skipLibCheck": true, + "forceConsistentCasingInFileNames": true, + "declaration": true, + "declarationMap": true, + "sourceMap": true, + "allowSyntheticDefaultImports": true + }, + "include": ["src/**/*"], + "exclude": ["node_modules", "dist"] +} +``` + +## Complete Example + +```typescript +#!/usr/bin/env node +/** + * MCP Server for Example Service. + * + * This server provides tools to interact with Example API, including user search, + * project management, and data export capabilities. + */ + +import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; +import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; +import { z } from "zod"; +import axios, { AxiosError } from "axios"; + +// Constants +const API_BASE_URL = "https://api.example.com/v1"; +const CHARACTER_LIMIT = 25000; + +// Enums +enum ResponseFormat { + MARKDOWN = "markdown", + JSON = "json" +} + +// Zod schemas +const UserSearchInputSchema = z.object({ + query: z.string() + .min(2, "Query must be at least 2 characters") + .max(200, "Query must not exceed 200 characters") + .describe("Search string to match against names/emails"), + limit: z.number() + .int() + .min(1) + .max(100) + .default(20) + .describe("Maximum results to return"), + offset: z.number() + .int() + .min(0) + .default(0) + .describe("Number of results to skip for pagination"), + response_format: z.nativeEnum(ResponseFormat) + .default(ResponseFormat.MARKDOWN) + .describe("Output format: 'markdown' for human-readable or 'json' for machine-readable") +}).strict(); + +type UserSearchInput = z.infer; + +// Shared utility functions +async function makeApiRequest( + endpoint: string, + method: "GET" | "POST" | "PUT" | "DELETE" = "GET", + data?: any, + params?: any +): Promise { + try { + const response = await axios({ + method, + url: `${API_BASE_URL}/${endpoint}`, + data, + params, + timeout: 30000, + headers: { + "Content-Type": "application/json", + "Accept": "application/json" + } + }); + return response.data; + } catch (error) { + throw error; + } +} + +function handleApiError(error: unknown): string { + if (error instanceof AxiosError) { + if (error.response) { + switch (error.response.status) { + case 404: + return "Error: Resource not found. Please check the ID is correct."; + case 403: + return "Error: Permission denied. You don't have access to this resource."; + case 429: + return "Error: Rate limit exceeded. Please wait before making more requests."; + default: + return `Error: API request failed with status ${error.response.status}`; + } + } else if (error.code === "ECONNABORTED") { + return "Error: Request timed out. Please try again."; + } + } + return `Error: Unexpected error occurred: ${error instanceof Error ? error.message : String(error)}`; +} + +// Create MCP server instance +const server = new McpServer({ + name: "example-mcp", + version: "1.0.0" +}); + +// Register tools +server.registerTool( + "example_search_users", + { + title: "Search Example Users", + description: `[Full description as shown above]`, + inputSchema: UserSearchInputSchema, + annotations: { + readOnlyHint: true, + destructiveHint: false, + idempotentHint: true, + openWorldHint: true + } + }, + async (params: UserSearchInput) => { + // Implementation as shown above + } +); + +// Main function +// For stdio (local): +async function runStdio() { + if (!process.env.EXAMPLE_API_KEY) { + console.error("ERROR: EXAMPLE_API_KEY environment variable is required"); + process.exit(1); + } + + const transport = new StdioServerTransport(); + await server.connect(transport); + console.error("MCP server running via stdio"); +} + +// For streamable HTTP (remote): +async function runHTTP() { + if (!process.env.EXAMPLE_API_KEY) { + console.error("ERROR: EXAMPLE_API_KEY environment variable is required"); + process.exit(1); + } + + const app = express(); + app.use(express.json()); + + app.post('/mcp', async (req, res) => { + const transport = new StreamableHTTPServerTransport({ + sessionIdGenerator: undefined, + enableJsonResponse: true + }); + res.on('close', () => transport.close()); + await server.connect(transport); + await transport.handleRequest(req, res, req.body); + }); + + const port = parseInt(process.env.PORT || '3000'); + app.listen(port, () => { + console.error(`MCP server running on http://localhost:${port}/mcp`); + }); +} + +// Choose transport based on environment +const transport = process.env.TRANSPORT || 'stdio'; +if (transport === 'http') { + runHTTP().catch(error => { + console.error("Server error:", error); + process.exit(1); + }); +} else { + runStdio().catch(error => { + console.error("Server error:", error); + process.exit(1); + }); +} +``` + +--- + +## Advanced MCP Features + +### Resource Registration + +Expose data as resources for efficient, URI-based access: + +```typescript +import { ResourceTemplate } from "@modelcontextprotocol/sdk/types.js"; + +// Register a resource with URI template +server.registerResource( + { + uri: "file://documents/{name}", + name: "Document Resource", + description: "Access documents by name", + mimeType: "text/plain" + }, + async (uri: string) => { + // Extract parameter from URI + const match = uri.match(/^file:\/\/documents\/(.+)$/); + if (!match) { + throw new Error("Invalid URI format"); + } + + const documentName = match[1]; + const content = await loadDocument(documentName); + + return { + contents: [{ + uri, + mimeType: "text/plain", + text: content + }] + }; + } +); + +// List available resources dynamically +server.registerResourceList(async () => { + const documents = await getAvailableDocuments(); + return { + resources: documents.map(doc => ({ + uri: `file://documents/${doc.name}`, + name: doc.name, + mimeType: "text/plain", + description: doc.description + })) + }; +}); +``` + +**When to use Resources vs Tools:** +- **Resources**: For data access with simple URI-based parameters +- **Tools**: For complex operations requiring validation and business logic +- **Resources**: When data is relatively static or template-based +- **Tools**: When operations have side effects or complex workflows + +### Transport Options + +The TypeScript SDK supports two main transport mechanisms: + +#### Streamable HTTP (Recommended for Remote Servers) + +```typescript +import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js"; +import express from "express"; + +const app = express(); +app.use(express.json()); + +app.post('/mcp', async (req, res) => { + // Create new transport for each request (stateless, prevents request ID collisions) + const transport = new StreamableHTTPServerTransport({ + sessionIdGenerator: undefined, + enableJsonResponse: true + }); + + res.on('close', () => transport.close()); + + await server.connect(transport); + await transport.handleRequest(req, res, req.body); +}); + +app.listen(3000); +``` + +#### stdio (For Local Integrations) + +```typescript +import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; + +const transport = new StdioServerTransport(); +await server.connect(transport); +``` + +**Transport selection:** +- **Streamable HTTP**: Web services, remote access, multiple clients +- **stdio**: Command-line tools, local development, subprocess integration + +### Notification Support + +Notify clients when server state changes: + +```typescript +// Notify when tools list changes +server.notification({ + method: "notifications/tools/list_changed" +}); + +// Notify when resources change +server.notification({ + method: "notifications/resources/list_changed" +}); +``` + +Use notifications sparingly - only when server capabilities genuinely change. + +--- + +## Code Best Practices + +### Code Composability and Reusability + +Your implementation MUST prioritize composability and code reuse: + +1. **Extract Common Functionality**: + - Create reusable helper functions for operations used across multiple tools + - Build shared API clients for HTTP requests instead of duplicating code + - Centralize error handling logic in utility functions + - Extract business logic into dedicated functions that can be composed + - Extract shared markdown or JSON field selection & formatting functionality + +2. **Avoid Duplication**: + - NEVER copy-paste similar code between tools + - If you find yourself writing similar logic twice, extract it into a function + - Common operations like pagination, filtering, field selection, and formatting should be shared + - Authentication/authorization logic should be centralized + +## Building and Running + +Always build your TypeScript code before running: + +```bash +# Build the project +npm run build + +# Run the server +npm start + +# Development with auto-reload +npm run dev +``` + +Always ensure `npm run build` completes successfully before considering the implementation complete. + +## Quality Checklist + +Before finalizing your Node/TypeScript MCP server implementation, ensure: + +### Strategic Design +- [ ] Tools enable complete workflows, not just API endpoint wrappers +- [ ] Tool names reflect natural task subdivisions +- [ ] Response formats optimize for agent context efficiency +- [ ] Human-readable identifiers used where appropriate +- [ ] Error messages guide agents toward correct usage + +### Implementation Quality +- [ ] FOCUSED IMPLEMENTATION: Most important and valuable tools implemented +- [ ] All tools registered using `registerTool` with complete configuration +- [ ] All tools include `title`, `description`, `inputSchema`, and `annotations` +- [ ] Annotations correctly set (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) +- [ ] All tools use Zod schemas for runtime input validation with `.strict()` enforcement +- [ ] All Zod schemas have proper constraints and descriptive error messages +- [ ] All tools have comprehensive descriptions with explicit input/output types +- [ ] Descriptions include return value examples and complete schema documentation +- [ ] Error messages are clear, actionable, and educational + +### TypeScript Quality +- [ ] TypeScript interfaces are defined for all data structures +- [ ] Strict TypeScript is enabled in tsconfig.json +- [ ] No use of `any` type - use `unknown` or proper types instead +- [ ] All async functions have explicit Promise return types +- [ ] Error handling uses proper type guards (e.g., `axios.isAxiosError`, `z.ZodError`) + +### Advanced Features (where applicable) +- [ ] Resources registered for appropriate data endpoints +- [ ] Appropriate transport configured (stdio or streamable HTTP) +- [ ] Notifications implemented for dynamic server capabilities +- [ ] Type-safe with SDK interfaces + +### Project Configuration +- [ ] Package.json includes all necessary dependencies +- [ ] Build script produces working JavaScript in dist/ directory +- [ ] Main entry point is properly configured as dist/index.js +- [ ] Server name follows format: `{service}-mcp-server` +- [ ] tsconfig.json properly configured with strict mode + +### Code Quality +- [ ] Pagination is properly implemented where applicable +- [ ] Large responses check CHARACTER_LIMIT constant and truncate with clear messages +- [ ] Filtering options are provided for potentially large result sets +- [ ] All network operations handle timeouts and connection errors gracefully +- [ ] Common functionality is extracted into reusable functions +- [ ] Return types are consistent across similar operations + +### Testing and Build +- [ ] `npm run build` completes successfully without errors +- [ ] dist/index.js created and executable +- [ ] Server runs: `node dist/index.js --help` +- [ ] All imports resolve correctly +- [ ] Sample tool calls work as expected diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/python_mcp_server.md b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/python_mcp_server.md new file mode 100644 index 00000000..a8332ff3 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/reference/python_mcp_server.md @@ -0,0 +1,719 @@ +# Python MCP Server Implementation Guide + +## Overview + +This document provides Python-specific best practices and examples for implementing MCP servers using the MCP Python SDK. It covers server setup, tool registration patterns, input validation with Pydantic, error handling, and complete working examples. + +--- + +## Quick Reference + +### Key Imports +```python +from mcp.server.fastmcp import FastMCP +from pydantic import BaseModel, Field, field_validator, ConfigDict +from typing import Optional, List, Dict, Any +from enum import Enum +import httpx +``` + +### Server Initialization +```python +mcp = FastMCP("service_mcp") +``` + +### Tool Registration Pattern +```python +@mcp.tool(name="tool_name", annotations={...}) +async def tool_function(params: InputModel) -> str: + # Implementation + pass +``` + +--- + +## MCP Python SDK and FastMCP + +The official MCP Python SDK provides FastMCP, a high-level framework for building MCP servers. It provides: +- Automatic description and inputSchema generation from function signatures and docstrings +- Pydantic model integration for input validation +- Decorator-based tool registration with `@mcp.tool` + +**For complete SDK documentation, use WebFetch to load:** +`https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` + +## Server Naming Convention + +Python MCP servers must follow this naming pattern: +- **Format**: `{service}_mcp` (lowercase with underscores) +- **Examples**: `github_mcp`, `jira_mcp`, `stripe_mcp` + +The name should be: +- General (not tied to specific features) +- Descriptive of the service/API being integrated +- Easy to infer from the task description +- Without version numbers or dates + +## Tool Implementation + +### Tool Naming + +Use snake_case for tool names (e.g., "search_users", "create_project", "get_channel_info") with clear, action-oriented names. + +**Avoid Naming Conflicts**: Include the service context to prevent overlaps: +- Use "slack_send_message" instead of just "send_message" +- Use "github_create_issue" instead of just "create_issue" +- Use "asana_list_tasks" instead of just "list_tasks" + +### Tool Structure with FastMCP + +Tools are defined using the `@mcp.tool` decorator with Pydantic models for input validation: + +```python +from pydantic import BaseModel, Field, ConfigDict +from mcp.server.fastmcp import FastMCP + +# Initialize the MCP server +mcp = FastMCP("example_mcp") + +# Define Pydantic model for input validation +class ServiceToolInput(BaseModel): + '''Input model for service tool operation.''' + model_config = ConfigDict( + str_strip_whitespace=True, # Auto-strip whitespace from strings + validate_assignment=True, # Validate on assignment + extra='forbid' # Forbid extra fields + ) + + param1: str = Field(..., description="First parameter description (e.g., 'user123', 'project-abc')", min_length=1, max_length=100) + param2: Optional[int] = Field(default=None, description="Optional integer parameter with constraints", ge=0, le=1000) + tags: Optional[List[str]] = Field(default_factory=list, description="List of tags to apply", max_items=10) + +@mcp.tool( + name="service_tool_name", + annotations={ + "title": "Human-Readable Tool Title", + "readOnlyHint": True, # Tool does not modify environment + "destructiveHint": False, # Tool does not perform destructive operations + "idempotentHint": True, # Repeated calls have no additional effect + "openWorldHint": False # Tool does not interact with external entities + } +) +async def service_tool_name(params: ServiceToolInput) -> str: + '''Tool description automatically becomes the 'description' field. + + This tool performs a specific operation on the service. It validates all inputs + using the ServiceToolInput Pydantic model before processing. + + Args: + params (ServiceToolInput): Validated input parameters containing: + - param1 (str): First parameter description + - param2 (Optional[int]): Optional parameter with default + - tags (Optional[List[str]]): List of tags + + Returns: + str: JSON-formatted response containing operation results + ''' + # Implementation here + pass +``` + +## Pydantic v2 Key Features + +- Use `model_config` instead of nested `Config` class +- Use `field_validator` instead of deprecated `validator` +- Use `model_dump()` instead of deprecated `dict()` +- Validators require `@classmethod` decorator +- Type hints are required for validator methods + +```python +from pydantic import BaseModel, Field, field_validator, ConfigDict + +class CreateUserInput(BaseModel): + model_config = ConfigDict( + str_strip_whitespace=True, + validate_assignment=True + ) + + name: str = Field(..., description="User's full name", min_length=1, max_length=100) + email: str = Field(..., description="User's email address", pattern=r'^[\w\.-]+@[\w\.-]+\.\w+$') + age: int = Field(..., description="User's age", ge=0, le=150) + + @field_validator('email') + @classmethod + def validate_email(cls, v: str) -> str: + if not v.strip(): + raise ValueError("Email cannot be empty") + return v.lower() +``` + +## Response Format Options + +Support multiple output formats for flexibility: + +```python +from enum import Enum + +class ResponseFormat(str, Enum): + '''Output format for tool responses.''' + MARKDOWN = "markdown" + JSON = "json" + +class UserSearchInput(BaseModel): + query: str = Field(..., description="Search query") + response_format: ResponseFormat = Field( + default=ResponseFormat.MARKDOWN, + description="Output format: 'markdown' for human-readable or 'json' for machine-readable" + ) +``` + +**Markdown format**: +- Use headers, lists, and formatting for clarity +- Convert timestamps to human-readable format (e.g., "2024-01-15 10:30:00 UTC" instead of epoch) +- Show display names with IDs in parentheses (e.g., "@john.doe (U123456)") +- Omit verbose metadata (e.g., show only one profile image URL, not all sizes) +- Group related information logically + +**JSON format**: +- Return complete, structured data suitable for programmatic processing +- Include all available fields and metadata +- Use consistent field names and types + +## Pagination Implementation + +For tools that list resources: + +```python +class ListInput(BaseModel): + limit: Optional[int] = Field(default=20, description="Maximum results to return", ge=1, le=100) + offset: Optional[int] = Field(default=0, description="Number of results to skip for pagination", ge=0) + +async def list_items(params: ListInput) -> str: + # Make API request with pagination + data = await api_request(limit=params.limit, offset=params.offset) + + # Return pagination info + response = { + "total": data["total"], + "count": len(data["items"]), + "offset": params.offset, + "items": data["items"], + "has_more": data["total"] > params.offset + len(data["items"]), + "next_offset": params.offset + len(data["items"]) if data["total"] > params.offset + len(data["items"]) else None + } + return json.dumps(response, indent=2) +``` + +## Error Handling + +Provide clear, actionable error messages: + +```python +def _handle_api_error(e: Exception) -> str: + '''Consistent error formatting across all tools.''' + if isinstance(e, httpx.HTTPStatusError): + if e.response.status_code == 404: + return "Error: Resource not found. Please check the ID is correct." + elif e.response.status_code == 403: + return "Error: Permission denied. You don't have access to this resource." + elif e.response.status_code == 429: + return "Error: Rate limit exceeded. Please wait before making more requests." + return f"Error: API request failed with status {e.response.status_code}" + elif isinstance(e, httpx.TimeoutException): + return "Error: Request timed out. Please try again." + return f"Error: Unexpected error occurred: {type(e).__name__}" +``` + +## Shared Utilities + +Extract common functionality into reusable functions: + +```python +# Shared API request function +async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict: + '''Reusable function for all API calls.''' + async with httpx.AsyncClient() as client: + response = await client.request( + method, + f"{API_BASE_URL}/{endpoint}", + timeout=30.0, + **kwargs + ) + response.raise_for_status() + return response.json() +``` + +## Async/Await Best Practices + +Always use async/await for network requests and I/O operations: + +```python +# Good: Async network request +async def fetch_data(resource_id: str) -> dict: + async with httpx.AsyncClient() as client: + response = await client.get(f"{API_URL}/resource/{resource_id}") + response.raise_for_status() + return response.json() + +# Bad: Synchronous request +def fetch_data(resource_id: str) -> dict: + response = requests.get(f"{API_URL}/resource/{resource_id}") # Blocks + return response.json() +``` + +## Type Hints + +Use type hints throughout: + +```python +from typing import Optional, List, Dict, Any + +async def get_user(user_id: str) -> Dict[str, Any]: + data = await fetch_user(user_id) + return {"id": data["id"], "name": data["name"]} +``` + +## Tool Docstrings + +Every tool must have comprehensive docstrings with explicit type information: + +```python +async def search_users(params: UserSearchInput) -> str: + ''' + Search for users in the Example system by name, email, or team. + + This tool searches across all user profiles in the Example platform, + supporting partial matches and various search filters. It does NOT + create or modify users, only searches existing ones. + + Args: + params (UserSearchInput): Validated input parameters containing: + - query (str): Search string to match against names/emails (e.g., "john", "@example.com", "team:marketing") + - limit (Optional[int]): Maximum results to return, between 1-100 (default: 20) + - offset (Optional[int]): Number of results to skip for pagination (default: 0) + + Returns: + str: JSON-formatted string containing search results with the following schema: + + Success response: + { + "total": int, # Total number of matches found + "count": int, # Number of results in this response + "offset": int, # Current pagination offset + "users": [ + { + "id": str, # User ID (e.g., "U123456789") + "name": str, # Full name (e.g., "John Doe") + "email": str, # Email address (e.g., "john@example.com") + "team": str # Team name (e.g., "Marketing") - optional + } + ] + } + + Error response: + "Error: " or "No users found matching ''" + + Examples: + - Use when: "Find all marketing team members" -> params with query="team:marketing" + - Use when: "Search for John's account" -> params with query="john" + - Don't use when: You need to create a user (use example_create_user instead) + - Don't use when: You have a user ID and need full details (use example_get_user instead) + + Error Handling: + - Input validation errors are handled by Pydantic model + - Returns "Error: Rate limit exceeded" if too many requests (429 status) + - Returns "Error: Invalid API authentication" if API key is invalid (401 status) + - Returns formatted list of results or "No users found matching 'query'" + ''' +``` + +## Complete Example + +See below for a complete Python MCP server example: + +```python +#!/usr/bin/env python3 +''' +MCP Server for Example Service. + +This server provides tools to interact with Example API, including user search, +project management, and data export capabilities. +''' + +from typing import Optional, List, Dict, Any +from enum import Enum +import httpx +from pydantic import BaseModel, Field, field_validator, ConfigDict +from mcp.server.fastmcp import FastMCP + +# Initialize the MCP server +mcp = FastMCP("example_mcp") + +# Constants +API_BASE_URL = "https://api.example.com/v1" + +# Enums +class ResponseFormat(str, Enum): + '''Output format for tool responses.''' + MARKDOWN = "markdown" + JSON = "json" + +# Pydantic Models for Input Validation +class UserSearchInput(BaseModel): + '''Input model for user search operations.''' + model_config = ConfigDict( + str_strip_whitespace=True, + validate_assignment=True + ) + + query: str = Field(..., description="Search string to match against names/emails", min_length=2, max_length=200) + limit: Optional[int] = Field(default=20, description="Maximum results to return", ge=1, le=100) + offset: Optional[int] = Field(default=0, description="Number of results to skip for pagination", ge=0) + response_format: ResponseFormat = Field(default=ResponseFormat.MARKDOWN, description="Output format") + + @field_validator('query') + @classmethod + def validate_query(cls, v: str) -> str: + if not v.strip(): + raise ValueError("Query cannot be empty or whitespace only") + return v.strip() + +# Shared utility functions +async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict: + '''Reusable function for all API calls.''' + async with httpx.AsyncClient() as client: + response = await client.request( + method, + f"{API_BASE_URL}/{endpoint}", + timeout=30.0, + **kwargs + ) + response.raise_for_status() + return response.json() + +def _handle_api_error(e: Exception) -> str: + '''Consistent error formatting across all tools.''' + if isinstance(e, httpx.HTTPStatusError): + if e.response.status_code == 404: + return "Error: Resource not found. Please check the ID is correct." + elif e.response.status_code == 403: + return "Error: Permission denied. You don't have access to this resource." + elif e.response.status_code == 429: + return "Error: Rate limit exceeded. Please wait before making more requests." + return f"Error: API request failed with status {e.response.status_code}" + elif isinstance(e, httpx.TimeoutException): + return "Error: Request timed out. Please try again." + return f"Error: Unexpected error occurred: {type(e).__name__}" + +# Tool definitions +@mcp.tool( + name="example_search_users", + annotations={ + "title": "Search Example Users", + "readOnlyHint": True, + "destructiveHint": False, + "idempotentHint": True, + "openWorldHint": True + } +) +async def example_search_users(params: UserSearchInput) -> str: + '''Search for users in the Example system by name, email, or team. + + [Full docstring as shown above] + ''' + try: + # Make API request using validated parameters + data = await _make_api_request( + "users/search", + params={ + "q": params.query, + "limit": params.limit, + "offset": params.offset + } + ) + + users = data.get("users", []) + total = data.get("total", 0) + + if not users: + return f"No users found matching '{params.query}'" + + # Format response based on requested format + if params.response_format == ResponseFormat.MARKDOWN: + lines = [f"# User Search Results: '{params.query}'", ""] + lines.append(f"Found {total} users (showing {len(users)})") + lines.append("") + + for user in users: + lines.append(f"## {user['name']} ({user['id']})") + lines.append(f"- **Email**: {user['email']}") + if user.get('team'): + lines.append(f"- **Team**: {user['team']}") + lines.append("") + + return "\n".join(lines) + + else: + # Machine-readable JSON format + import json + response = { + "total": total, + "count": len(users), + "offset": params.offset, + "users": users + } + return json.dumps(response, indent=2) + + except Exception as e: + return _handle_api_error(e) + +if __name__ == "__main__": + mcp.run() +``` + +--- + +## Advanced FastMCP Features + +### Context Parameter Injection + +FastMCP can automatically inject a `Context` parameter into tools for advanced capabilities like logging, progress reporting, resource reading, and user interaction: + +```python +from mcp.server.fastmcp import FastMCP, Context + +mcp = FastMCP("example_mcp") + +@mcp.tool() +async def advanced_search(query: str, ctx: Context) -> str: + '''Advanced tool with context access for logging and progress.''' + + # Report progress for long operations + await ctx.report_progress(0.25, "Starting search...") + + # Log information for debugging + await ctx.log_info("Processing query", {"query": query, "timestamp": datetime.now()}) + + # Perform search + results = await search_api(query) + await ctx.report_progress(0.75, "Formatting results...") + + # Access server configuration + server_name = ctx.fastmcp.name + + return format_results(results) + +@mcp.tool() +async def interactive_tool(resource_id: str, ctx: Context) -> str: + '''Tool that can request additional input from users.''' + + # Request sensitive information when needed + api_key = await ctx.elicit( + prompt="Please provide your API key:", + input_type="password" + ) + + # Use the provided key + return await api_call(resource_id, api_key) +``` + +**Context capabilities:** +- `ctx.report_progress(progress, message)` - Report progress for long operations +- `ctx.log_info(message, data)` / `ctx.log_error()` / `ctx.log_debug()` - Logging +- `ctx.elicit(prompt, input_type)` - Request input from users +- `ctx.fastmcp.name` - Access server configuration +- `ctx.read_resource(uri)` - Read MCP resources + +### Resource Registration + +Expose data as resources for efficient, template-based access: + +```python +@mcp.resource("file://documents/{name}") +async def get_document(name: str) -> str: + '''Expose documents as MCP resources. + + Resources are useful for static or semi-static data that doesn't + require complex parameters. They use URI templates for flexible access. + ''' + document_path = f"./docs/{name}" + with open(document_path, "r") as f: + return f.read() + +@mcp.resource("config://settings/{key}") +async def get_setting(key: str, ctx: Context) -> str: + '''Expose configuration as resources with context.''' + settings = await load_settings() + return json.dumps(settings.get(key, {})) +``` + +**When to use Resources vs Tools:** +- **Resources**: For data access with simple parameters (URI templates) +- **Tools**: For complex operations with validation and business logic + +### Structured Output Types + +FastMCP supports multiple return types beyond strings: + +```python +from typing import TypedDict +from dataclasses import dataclass +from pydantic import BaseModel + +# TypedDict for structured returns +class UserData(TypedDict): + id: str + name: str + email: str + +@mcp.tool() +async def get_user_typed(user_id: str) -> UserData: + '''Returns structured data - FastMCP handles serialization.''' + return {"id": user_id, "name": "John Doe", "email": "john@example.com"} + +# Pydantic models for complex validation +class DetailedUser(BaseModel): + id: str + name: str + email: str + created_at: datetime + metadata: Dict[str, Any] + +@mcp.tool() +async def get_user_detailed(user_id: str) -> DetailedUser: + '''Returns Pydantic model - automatically generates schema.''' + user = await fetch_user(user_id) + return DetailedUser(**user) +``` + +### Lifespan Management + +Initialize resources that persist across requests: + +```python +from contextlib import asynccontextmanager + +@asynccontextmanager +async def app_lifespan(): + '''Manage resources that live for the server's lifetime.''' + # Initialize connections, load config, etc. + db = await connect_to_database() + config = load_configuration() + + # Make available to all tools + yield {"db": db, "config": config} + + # Cleanup on shutdown + await db.close() + +mcp = FastMCP("example_mcp", lifespan=app_lifespan) + +@mcp.tool() +async def query_data(query: str, ctx: Context) -> str: + '''Access lifespan resources through context.''' + db = ctx.request_context.lifespan_state["db"] + results = await db.query(query) + return format_results(results) +``` + +### Transport Options + +FastMCP supports two main transport mechanisms: + +```python +# stdio transport (for local tools) - default +if __name__ == "__main__": + mcp.run() + +# Streamable HTTP transport (for remote servers) +if __name__ == "__main__": + mcp.run(transport="streamable_http", port=8000) +``` + +**Transport selection:** +- **stdio**: Command-line tools, local integrations, subprocess execution +- **Streamable HTTP**: Web services, remote access, multiple clients + +--- + +## Code Best Practices + +### Code Composability and Reusability + +Your implementation MUST prioritize composability and code reuse: + +1. **Extract Common Functionality**: + - Create reusable helper functions for operations used across multiple tools + - Build shared API clients for HTTP requests instead of duplicating code + - Centralize error handling logic in utility functions + - Extract business logic into dedicated functions that can be composed + - Extract shared markdown or JSON field selection & formatting functionality + +2. **Avoid Duplication**: + - NEVER copy-paste similar code between tools + - If you find yourself writing similar logic twice, extract it into a function + - Common operations like pagination, filtering, field selection, and formatting should be shared + - Authentication/authorization logic should be centralized + +### Python-Specific Best Practices + +1. **Use Type Hints**: Always include type annotations for function parameters and return values +2. **Pydantic Models**: Define clear Pydantic models for all input validation +3. **Avoid Manual Validation**: Let Pydantic handle input validation with constraints +4. **Proper Imports**: Group imports (standard library, third-party, local) +5. **Error Handling**: Use specific exception types (httpx.HTTPStatusError, not generic Exception) +6. **Async Context Managers**: Use `async with` for resources that need cleanup +7. **Constants**: Define module-level constants in UPPER_CASE + +## Quality Checklist + +Before finalizing your Python MCP server implementation, ensure: + +### Strategic Design +- [ ] Tools enable complete workflows, not just API endpoint wrappers +- [ ] Tool names reflect natural task subdivisions +- [ ] Response formats optimize for agent context efficiency +- [ ] Human-readable identifiers used where appropriate +- [ ] Error messages guide agents toward correct usage + +### Implementation Quality +- [ ] FOCUSED IMPLEMENTATION: Most important and valuable tools implemented +- [ ] All tools have descriptive names and documentation +- [ ] Return types are consistent across similar operations +- [ ] Error handling is implemented for all external calls +- [ ] Server name follows format: `{service}_mcp` +- [ ] All network operations use async/await +- [ ] Common functionality is extracted into reusable functions +- [ ] Error messages are clear, actionable, and educational +- [ ] Outputs are properly validated and formatted + +### Tool Configuration +- [ ] All tools implement 'name' and 'annotations' in the decorator +- [ ] Annotations correctly set (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) +- [ ] All tools use Pydantic BaseModel for input validation with Field() definitions +- [ ] All Pydantic Fields have explicit types and descriptions with constraints +- [ ] All tools have comprehensive docstrings with explicit input/output types +- [ ] Docstrings include complete schema structure for dict/JSON returns +- [ ] Pydantic models handle input validation (no manual validation needed) + +### Advanced Features (where applicable) +- [ ] Context injection used for logging, progress, or elicitation +- [ ] Resources registered for appropriate data endpoints +- [ ] Lifespan management implemented for persistent connections +- [ ] Structured output types used (TypedDict, Pydantic models) +- [ ] Appropriate transport configured (stdio or streamable HTTP) + +### Code Quality +- [ ] File includes proper imports including Pydantic imports +- [ ] Pagination is properly implemented where applicable +- [ ] Filtering options are provided for potentially large result sets +- [ ] All async functions are properly defined with `async def` +- [ ] HTTP client usage follows async patterns with proper context managers +- [ ] Type hints are used throughout the code +- [ ] Constants are defined at module level in UPPER_CASE + +### Testing +- [ ] Server runs successfully: `python your_server.py --help` +- [ ] All imports resolve correctly +- [ ] Sample tool calls work as expected +- [ ] Error scenarios handled gracefully diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/connections.py b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/connections.py new file mode 100644 index 00000000..ffcd0da3 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/connections.py @@ -0,0 +1,151 @@ +"""Lightweight connection handling for MCP servers.""" + +from abc import ABC, abstractmethod +from contextlib import AsyncExitStack +from typing import Any + +from mcp import ClientSession, StdioServerParameters +from mcp.client.sse import sse_client +from mcp.client.stdio import stdio_client +from mcp.client.streamable_http import streamablehttp_client + + +class MCPConnection(ABC): + """Base class for MCP server connections.""" + + def __init__(self): + self.session = None + self._stack = None + + @abstractmethod + def _create_context(self): + """Create the connection context based on connection type.""" + + async def __aenter__(self): + """Initialize MCP server connection.""" + self._stack = AsyncExitStack() + await self._stack.__aenter__() + + try: + ctx = self._create_context() + result = await self._stack.enter_async_context(ctx) + + if len(result) == 2: + read, write = result + elif len(result) == 3: + read, write, _ = result + else: + raise ValueError(f"Unexpected context result: {result}") + + session_ctx = ClientSession(read, write) + self.session = await self._stack.enter_async_context(session_ctx) + await self.session.initialize() + return self + except BaseException: + await self._stack.__aexit__(None, None, None) + raise + + async def __aexit__(self, exc_type, exc_val, exc_tb): + """Clean up MCP server connection resources.""" + if self._stack: + await self._stack.__aexit__(exc_type, exc_val, exc_tb) + self.session = None + self._stack = None + + async def list_tools(self) -> list[dict[str, Any]]: + """Retrieve available tools from the MCP server.""" + response = await self.session.list_tools() + return [ + { + "name": tool.name, + "description": tool.description, + "input_schema": tool.inputSchema, + } + for tool in response.tools + ] + + async def call_tool(self, tool_name: str, arguments: dict[str, Any]) -> Any: + """Call a tool on the MCP server with provided arguments.""" + result = await self.session.call_tool(tool_name, arguments=arguments) + return result.content + + +class MCPConnectionStdio(MCPConnection): + """MCP connection using standard input/output.""" + + def __init__(self, command: str, args: list[str] = None, env: dict[str, str] = None): + super().__init__() + self.command = command + self.args = args or [] + self.env = env + + def _create_context(self): + return stdio_client( + StdioServerParameters(command=self.command, args=self.args, env=self.env) + ) + + +class MCPConnectionSSE(MCPConnection): + """MCP connection using Server-Sent Events.""" + + def __init__(self, url: str, headers: dict[str, str] = None): + super().__init__() + self.url = url + self.headers = headers or {} + + def _create_context(self): + return sse_client(url=self.url, headers=self.headers) + + +class MCPConnectionHTTP(MCPConnection): + """MCP connection using Streamable HTTP.""" + + def __init__(self, url: str, headers: dict[str, str] = None): + super().__init__() + self.url = url + self.headers = headers or {} + + def _create_context(self): + return streamablehttp_client(url=self.url, headers=self.headers) + + +def create_connection( + transport: str, + command: str = None, + args: list[str] = None, + env: dict[str, str] = None, + url: str = None, + headers: dict[str, str] = None, +) -> MCPConnection: + """Factory function to create the appropriate MCP connection. + + Args: + transport: Connection type ("stdio", "sse", or "http") + command: Command to run (stdio only) + args: Command arguments (stdio only) + env: Environment variables (stdio only) + url: Server URL (sse and http only) + headers: HTTP headers (sse and http only) + + Returns: + MCPConnection instance + """ + transport = transport.lower() + + if transport == "stdio": + if not command: + raise ValueError("Command is required for stdio transport") + return MCPConnectionStdio(command=command, args=args, env=env) + + elif transport == "sse": + if not url: + raise ValueError("URL is required for sse transport") + return MCPConnectionSSE(url=url, headers=headers) + + elif transport in ["http", "streamable_http", "streamable-http"]: + if not url: + raise ValueError("URL is required for http transport") + return MCPConnectionHTTP(url=url, headers=headers) + + else: + raise ValueError(f"Unsupported transport type: {transport}. Use 'stdio', 'sse', or 'http'") diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/evaluation.py b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/evaluation.py new file mode 100644 index 00000000..41778569 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/evaluation.py @@ -0,0 +1,373 @@ +"""MCP Server Evaluation Harness + +This script evaluates MCP servers by running test questions against them using Claude. +""" + +import argparse +import asyncio +import json +import re +import sys +import time +import traceback +import xml.etree.ElementTree as ET +from pathlib import Path +from typing import Any + +from anthropic import Anthropic + +from connections import create_connection + +EVALUATION_PROMPT = """You are an AI assistant with access to tools. + +When given a task, you MUST: +1. Use the available tools to complete the task +2. Provide summary of each step in your approach, wrapped in     tags +3. Provide feedback on the tools provided, wrapped in tags +4. Provide your final response, wrapped in tags + +Summary Requirements: +- In your tags, you must explain: + - The steps you took to complete the task + - Which tools you used, in what order, and why + - The inputs you provided to each tool + - The outputs you received from each tool + - A summary for how you arrived at the response + +Feedback Requirements: +- In your tags, provide constructive feedback on the tools: + - Comment on tool names: Are they clear and descriptive? + - Comment on input parameters: Are they well-documented? Are required vs optional parameters clear? + - Comment on descriptions: Do they accurately describe what the tool does? + - Comment on any errors encountered during tool usage: Did the tool fail to execute? Did the tool return too many tokens? + - Identify specific areas for improvement and explain WHY they would help + - Be specific and actionable in your suggestions + +Response Requirements: +- Your response should be concise and directly address what was asked +- Always wrap your final response in tags +- If you cannot solve the task return NOT_FOUND +- For numeric responses, provide just the number +- For IDs, provide just the ID +- For names or text, provide the exact text requested +- Your response should go last""" + + +def parse_evaluation_file(file_path: Path) -> list[dict[str, Any]]: + """Parse XML evaluation file with qa_pair elements.""" + try: + tree = ET.parse(file_path) + root = tree.getroot() + evaluations = [] + + for qa_pair in root.findall(".//qa_pair"): + question_elem = qa_pair.find("question") + answer_elem = qa_pair.find("answer") + + if question_elem is not None and answer_elem is not None: + evaluations.append({ + "question": (question_elem.text or "").strip(), + "answer": (answer_elem.text or "").strip(), + }) + + return evaluations + except Exception as e: + print(f"Error parsing evaluation file {file_path}: {e}") + return [] + + +def extract_xml_content(text: str, tag: str) -> str | None: + """Extract content from XML tags.""" + pattern = rf"<{tag}>(.*?)" + matches = re.findall(pattern, text, re.DOTALL) + return matches[-1].strip() if matches else None + + +async def agent_loop( + client: Anthropic, + model: str, + question: str, + tools: list[dict[str, Any]], + connection: Any, +) -> tuple[str, dict[str, Any]]: + """Run the agent loop with MCP tools.""" + messages = [{"role": "user", "content": question}] + + response = await asyncio.to_thread( + client.messages.create, + model=model, + max_tokens=4096, + system=EVALUATION_PROMPT, + messages=messages, + tools=tools, + ) + + messages.append({"role": "assistant", "content": response.content}) + + tool_metrics = {} + + while response.stop_reason == "tool_use": + tool_use = next(block for block in response.content if block.type == "tool_use") + tool_name = tool_use.name + tool_input = tool_use.input + + tool_start_ts = time.time() + try: + tool_result = await connection.call_tool(tool_name, tool_input) + tool_response = json.dumps(tool_result) if isinstance(tool_result, (dict, list)) else str(tool_result) + except Exception as e: + tool_response = f"Error executing tool {tool_name}: {str(e)}\n" + tool_response += traceback.format_exc() + tool_duration = time.time() - tool_start_ts + + if tool_name not in tool_metrics: + tool_metrics[tool_name] = {"count": 0, "durations": []} + tool_metrics[tool_name]["count"] += 1 + tool_metrics[tool_name]["durations"].append(tool_duration) + + messages.append({ + "role": "user", + "content": [{ + "type": "tool_result", + "tool_use_id": tool_use.id, + "content": tool_response, + }] + }) + + response = await asyncio.to_thread( + client.messages.create, + model=model, + max_tokens=4096, + system=EVALUATION_PROMPT, + messages=messages, + tools=tools, + ) + messages.append({"role": "assistant", "content": response.content}) + + response_text = next( + (block.text for block in response.content if hasattr(block, "text")), + None, + ) + return response_text, tool_metrics + + +async def evaluate_single_task( + client: Anthropic, + model: str, + qa_pair: dict[str, Any], + tools: list[dict[str, Any]], + connection: Any, + task_index: int, +) -> dict[str, Any]: + """Evaluate a single QA pair with the given tools.""" + start_time = time.time() + + print(f"Task {task_index + 1}: Running task with question: {qa_pair['question']}") + response, tool_metrics = await agent_loop(client, model, qa_pair["question"], tools, connection) + + response_value = extract_xml_content(response, "response") + summary = extract_xml_content(response, "summary") + feedback = extract_xml_content(response, "feedback") + + duration_seconds = time.time() - start_time + + return { + "question": qa_pair["question"], + "expected": qa_pair["answer"], + "actual": response_value, + "score": int(response_value == qa_pair["answer"]) if response_value else 0, + "total_duration": duration_seconds, + "tool_calls": tool_metrics, + "num_tool_calls": sum(len(metrics["durations"]) for metrics in tool_metrics.values()), + "summary": summary, + "feedback": feedback, + } + + +REPORT_HEADER = """ +# Evaluation Report + +## Summary + +- **Accuracy**: {correct}/{total} ({accuracy:.1f}%) +- **Average Task Duration**: {average_duration_s:.2f}s +- **Average Tool Calls per Task**: {average_tool_calls:.2f} +- **Total Tool Calls**: {total_tool_calls} + +--- +""" + +TASK_TEMPLATE = """ +### Task {task_num} + +**Question**: {question} +**Ground Truth Answer**: `{expected_answer}` +**Actual Answer**: `{actual_answer}` +**Correct**: {correct_indicator} +**Duration**: {total_duration:.2f}s +**Tool Calls**: {tool_calls} + +**Summary** +{summary} + +**Feedback** +{feedback} + +--- +""" + + +async def run_evaluation( + eval_path: Path, + connection: Any, + model: str = "claude-3-7-sonnet-20250219", +) -> str: + """Run evaluation with MCP server tools.""" + print("🚀 Starting Evaluation") + + client = Anthropic() + + tools = await connection.list_tools() + print(f"📋 Loaded {len(tools)} tools from MCP server") + + qa_pairs = parse_evaluation_file(eval_path) + print(f"📋 Loaded {len(qa_pairs)} evaluation tasks") + + results = [] + for i, qa_pair in enumerate(qa_pairs): + print(f"Processing task {i + 1}/{len(qa_pairs)}") + result = await evaluate_single_task(client, model, qa_pair, tools, connection, i) + results.append(result) + + correct = sum(r["score"] for r in results) + accuracy = (correct / len(results)) * 100 if results else 0 + average_duration_s = sum(r["total_duration"] for r in results) / len(results) if results else 0 + average_tool_calls = sum(r["num_tool_calls"] for r in results) / len(results) if results else 0 + total_tool_calls = sum(r["num_tool_calls"] for r in results) + + report = REPORT_HEADER.format( + correct=correct, + total=len(results), + accuracy=accuracy, + average_duration_s=average_duration_s, + average_tool_calls=average_tool_calls, + total_tool_calls=total_tool_calls, + ) + + report += "".join([ + TASK_TEMPLATE.format( + task_num=i + 1, + question=qa_pair["question"], + expected_answer=qa_pair["answer"], + actual_answer=result["actual"] or "N/A", + correct_indicator="✅" if result["score"] else "❌", + total_duration=result["total_duration"], + tool_calls=json.dumps(result["tool_calls"], indent=2), + summary=result["summary"] or "N/A", + feedback=result["feedback"] or "N/A", + ) + for i, (qa_pair, result) in enumerate(zip(qa_pairs, results)) + ]) + + return report + + +def parse_headers(header_list: list[str]) -> dict[str, str]: + """Parse header strings in format 'Key: Value' into a dictionary.""" + headers = {} + if not header_list: + return headers + + for header in header_list: + if ":" in header: + key, value = header.split(":", 1) + headers[key.strip()] = value.strip() + else: + print(f"Warning: Ignoring malformed header: {header}") + return headers + + +def parse_env_vars(env_list: list[str]) -> dict[str, str]: + """Parse environment variable strings in format 'KEY=VALUE' into a dictionary.""" + env = {} + if not env_list: + return env + + for env_var in env_list: + if "=" in env_var: + key, value = env_var.split("=", 1) + env[key.strip()] = value.strip() + else: + print(f"Warning: Ignoring malformed environment variable: {env_var}") + return env + + +async def main(): + parser = argparse.ArgumentParser( + description="Evaluate MCP servers using test questions", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + # Evaluate a local stdio MCP server + python evaluation.py -t stdio -c python -a my_server.py eval.xml + + # Evaluate an SSE MCP server + python evaluation.py -t sse -u https://example.com/mcp -H "Authorization: Bearer token" eval.xml + + # Evaluate an HTTP MCP server with custom model + python evaluation.py -t http -u https://example.com/mcp -m claude-3-5-sonnet-20241022 eval.xml + """, + ) + + parser.add_argument("eval_file", type=Path, help="Path to evaluation XML file") + parser.add_argument("-t", "--transport", choices=["stdio", "sse", "http"], default="stdio", help="Transport type (default: stdio)") + parser.add_argument("-m", "--model", default="claude-3-7-sonnet-20250219", help="Claude model to use (default: claude-3-7-sonnet-20250219)") + + stdio_group = parser.add_argument_group("stdio options") + stdio_group.add_argument("-c", "--command", help="Command to run MCP server (stdio only)") + stdio_group.add_argument("-a", "--args", nargs="+", help="Arguments for the command (stdio only)") + stdio_group.add_argument("-e", "--env", nargs="+", help="Environment variables in KEY=VALUE format (stdio only)") + + remote_group = parser.add_argument_group("sse/http options") + remote_group.add_argument("-u", "--url", help="MCP server URL (sse/http only)") + remote_group.add_argument("-H", "--header", nargs="+", dest="headers", help="HTTP headers in 'Key: Value' format (sse/http only)") + + parser.add_argument("-o", "--output", type=Path, help="Output file for evaluation report (default: stdout)") + + args = parser.parse_args() + + if not args.eval_file.exists(): + print(f"Error: Evaluation file not found: {args.eval_file}") + sys.exit(1) + + headers = parse_headers(args.headers) if args.headers else None + env_vars = parse_env_vars(args.env) if args.env else None + + try: + connection = create_connection( + transport=args.transport, + command=args.command, + args=args.args, + env=env_vars, + url=args.url, + headers=headers, + ) + except ValueError as e: + print(f"Error: {e}") + sys.exit(1) + + print(f"🔗 Connecting to MCP server via {args.transport}...") + + async with connection: + print("✅ Connected successfully") + report = await run_evaluation(args.eval_file, connection, args.model) + + if args.output: + args.output.write_text(report) + print(f"\n✅ Report saved to {args.output}") + else: + print("\n" + report) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/example_evaluation.xml b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/example_evaluation.xml new file mode 100644 index 00000000..41e4459b --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/example_evaluation.xml @@ -0,0 +1,22 @@ + + + Calculate the compound interest on $10,000 invested at 5% annual interest rate, compounded monthly for 3 years. What is the final amount in dollars (rounded to 2 decimal places)? + 11614.72 + + + A projectile is launched at a 45-degree angle with an initial velocity of 50 m/s. Calculate the total distance (in meters) it has traveled from the launch point after 2 seconds, assuming g=9.8 m/s². Round to 2 decimal places. + 87.25 + + + A sphere has a volume of 500 cubic meters. Calculate its surface area in square meters. Round to 2 decimal places. + 304.65 + + + Calculate the population standard deviation of this dataset: [12, 15, 18, 22, 25, 30, 35]. Round to 2 decimal places. + 7.61 + + + Calculate the pH of a solution with a hydrogen ion concentration of 3.5 × 10^-5 M. Round to 2 decimal places. + 4.46 + + diff --git a/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/requirements.txt b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/requirements.txt new file mode 100644 index 00000000..e73e5d1e --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/mcp-builder/scripts/requirements.txt @@ -0,0 +1,2 @@ +anthropic>=0.39.0 +mcp>=1.1.0 diff --git a/libs/hexagent_demo/backend/skills/public/pdf/LICENSE.txt b/libs/hexagent_demo/backend/skills/public/pdf/LICENSE.txt new file mode 100644 index 00000000..13e25df8 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/pdf/LICENSE.txt @@ -0,0 +1,201 @@ +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. 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Prefer visual review: render PDF pages to PNGs and inspect them. + - Use `pdftoppm` if available. + - If unavailable, install Poppler or ask the user to review the output locally. +2. Use `reportlab` to generate PDFs when creating new documents. +3. Use `pdfplumber` (or `pypdf`) for text extraction and quick checks; do not rely on it for layout fidelity. +4. After each meaningful update, re-render pages and verify alignment, spacing, and legibility. + +## Temp and output conventions +- Use `tmp/pdfs/` for intermediate files; delete when done. +- Write final artifacts under `output/pdf/` when working in this repo. +- Keep filenames stable and descriptive. + +## Dependencies (install if missing) +Prefer `uv` for dependency management. + +Python packages: +``` +uv pip install reportlab pdfplumber pypdf +``` +If `uv` is unavailable: +``` +python3 -m pip install reportlab pdfplumber pypdf +``` +System tools (for rendering): +``` +# macOS (Homebrew) +brew install poppler + +# Ubuntu/Debian +sudo apt-get install -y poppler-utils +``` + +If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally. + +## Environment +No required environment variables. + +## Rendering command +``` +pdftoppm -png $INPUT_PDF $OUTPUT_PREFIX +``` + +## Quality expectations +- Maintain polished visual design: consistent typography, spacing, margins, and section hierarchy. +- Avoid rendering issues: clipped text, overlapping elements, broken tables, black squares, or unreadable glyphs. +- Charts, tables, and images must be sharp, aligned, and clearly labeled. +- Use ASCII hyphens only. Avoid U+2011 (non-breaking hyphen) and other Unicode dashes. +- Citations and references must be human-readable; never leave tool tokens or placeholder strings. + +## Final checks +- Do not deliver until the latest PNG inspection shows zero visual or formatting defects. +- Confirm headers/footers, page numbering, and section transitions look polished. +- Keep intermediate files organized or remove them after final approval. diff --git a/libs/hexagent_demo/backend/skills/public/pdf/agents/openai.yaml b/libs/hexagent_demo/backend/skills/public/pdf/agents/openai.yaml new file mode 100644 index 00000000..fe2876a6 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/pdf/agents/openai.yaml @@ -0,0 +1,5 @@ +interface: + display_name: "PDF Skill" + short_description: "Create, edit, and review PDFs" + icon_large: "./assets/pdf.png" + default_prompt: "Create, edit, or review this PDF and summarize the key output or changes." diff --git a/libs/hexagent_demo/backend/skills/public/pdf/assets/pdf.png b/libs/hexagent_demo/backend/skills/public/pdf/assets/pdf.png new file mode 100644 index 0000000000000000000000000000000000000000..dd16ba283f6056cfe99cc3d36612d3b8cd79e00d GIT binary patch literal 1312 zcmeAS@N?(olHy`uVBq!ia0vp^DIm``W z$lZxy-8q?;Kn_c~qpu?a!^VE@KZ&eB?p9A1$B+ufw{!RVi#UoLzyD5d!2}6Ysoskj zJ-oMOtXOL%=8(u-&tf7H5Pb1+fP*iushC+nhKLvQ#R(jWQ6COpkYTy8xA^{y#-}%$ zt!K>q`|gw7Nj3I2j%D^|sz0ZtKiiYV!)fqC#X-^OfPi8`hk$_#hlCOfk04VU2cvUK z12*BsE|P(F?<_fWNhtK%wT`m#lPdq-&K9||-~G!M$%}{Gr>NUp_vcx>)3WQ?^Qk=1 zQ{-#|*n{_$&fden*Tp<9K(0Wog;mDSZ`HKK*-HdmqoptYUiV*@O-9}6&`e3L<;zcs zE^o<*@OsYebgU|QA>qiZ zb+l{3sYgnoVd0!|4w_*tErn|*N*`Di2Jvb+>kA za(S;^a^dd1jO1>#~z9$Eu1Q{k8fqp`wIuZ&)+yF_j8h&`3aMmXJbk@yDegV zE{&^}efuOfTUDRq#ik$Utu!k<-F6B&O$yoR9b*=}ydw4U*FK)PSYre^qKxEYzF1jx ztc&;m8(EsY`r+rx=WIXjvo3!T^X;3_e6HC$1^!>v&XSZ^@w+(g`nhb;uSKsmpL@Ra zdX;RAZtmm9C35Y;!YkjGa@L&Sy0>@nwTBPe&V8M4AHFH-*Kf`B4z~Q360)}UA{OkO z+hm@<;>vCBdykL5O1u8<-vpccyQ`-+ZO@1McnsXq2_YL1iiyYc@rXHBB;`Qfy z@xGJN0lF>Dli%@fAdo679+mSlu*RLztcVC~9-Z^jj(b#C&X*>Kr&a(+TImdIg z<0pr8tt=ZSM3p#pTu9!|#;HrSs--^YT3FR4_c3CS={JXn*>}t3`_z&AS-Eb^4lC>AD%YM{ca~>|?ue z;ME1s(-#633faVazdpfn^T;ZJT1M9ik6uO1dGmLjdFZ(+x8tsyj~=ZzF(@$cOA}r$ zA0BAElwG#2Z++3i!%5eFK5sXu`ZuL2f@NE#n!VGv$H({F(b^300 lines), include a table of contents + +**Domain organization**: When a skill supports multiple domains/frameworks, organize by variant: +``` +cloud-deploy/ +├── SKILL.md (workflow + selection) +└── references/ + ├── aws.md + ├── gcp.md + └── azure.md +``` +Claude reads only the relevant reference file. + +#### Principle of Lack of Surprise + +This goes without saying, but skills must not contain malware, exploit code, or any content that could compromise system security. A skill's contents should not surprise the user in their intent if described. Don't go along with requests to create misleading skills or skills designed to facilitate unauthorized access, data exfiltration, or other malicious activities. Things like a "roleplay as an XYZ" are OK though. + +#### Writing Patterns + +Prefer using the imperative form in instructions. + +**Defining output formats** - You can do it like this: +```markdown +## Report structure +ALWAYS use this exact template: +# [Title] +## Executive summary +## Key findings +## Recommendations +``` + +**Examples pattern** - It's useful to include examples. You can format them like this (but if "Input" and "Output" are in the examples you might want to deviate a little): +```markdown +## Commit message format +**Example 1:** +Input: Added user authentication with JWT tokens +Output: feat(auth): implement JWT-based authentication +``` + +### Writing Style + +Try to explain to the model why things are important in lieu of heavy-handed musty MUSTs. Use theory of mind and try to make the skill general and not super-narrow to specific examples. Start by writing a draft and then look at it with fresh eyes and improve it. + +### Test Cases + +After writing the skill draft, come up with 2-3 realistic test prompts — the kind of thing a real user would actually say. Share them with the user: [you don't have to use this exact language] "Here are a few test cases I'd like to try. Do these look right, or do you want to add more?" Then run them. + +Save test cases to `evals/evals.json`. Don't write assertions yet — just the prompts. You'll draft assertions in the next step while the runs are in progress. + +```json +{ + "skill_name": "example-skill", + "evals": [ + { + "id": 1, + "prompt": "User's task prompt", + "expected_output": "Description of expected result", + "files": [] + } + ] +} +``` + +See `references/schemas.md` for the full schema (including the `assertions` field, which you'll add later). + +## Running and evaluating test cases + +This section is one continuous sequence — don't stop partway through. Do NOT use `/skill-test` or any other testing skill. + +Put results in `-workspace/` as a sibling to the skill directory. Within the workspace, organize results by iteration (`iteration-1/`, `iteration-2/`, etc.) and within that, each test case gets a directory (`eval-0/`, `eval-1/`, etc.). Don't create all of this upfront — just create directories as you go. + +### Step 1: Spawn all runs (with-skill AND baseline) in the same turn + +For each test case, spawn two subagents in the same turn — one with the skill, one without. This is important: don't spawn the with-skill runs first and then come back for baselines later. Launch everything at once so it all finishes around the same time. + +**With-skill run:** + +``` +Execute this task: +- Skill path: +- Task: +- Input files: +- Save outputs to: /iteration-/eval-/with_skill/outputs/ +- Outputs to save: +``` + +**Baseline run** (same prompt, but the baseline depends on context): +- **Creating a new skill**: no skill at all. Same prompt, no skill path, save to `without_skill/outputs/`. +- **Improving an existing skill**: the old version. Before editing, snapshot the skill (`cp -r /skill-snapshot/`), then point the baseline subagent at the snapshot. Save to `old_skill/outputs/`. + +Write an `eval_metadata.json` for each test case (assertions can be empty for now). Give each eval a descriptive name based on what it's testing — not just "eval-0". Use this name for the directory too. If this iteration uses new or modified eval prompts, create these files for each new eval directory — don't assume they carry over from previous iterations. + +```json +{ + "eval_id": 0, + "eval_name": "descriptive-name-here", + "prompt": "The user's task prompt", + "assertions": [] +} +``` + +### Step 2: While runs are in progress, draft assertions + +Don't just wait for the runs to finish — you can use this time productively. Draft quantitative assertions for each test case and explain them to the user. If assertions already exist in `evals/evals.json`, review them and explain what they check. + +Good assertions are objectively verifiable and have descriptive names — they should read clearly in the benchmark viewer so someone glancing at the results immediately understands what each one checks. Subjective skills (writing style, design quality) are better evaluated qualitatively — don't force assertions onto things that need human judgment. + +Update the `eval_metadata.json` files and `evals/evals.json` with the assertions once drafted. Also explain to the user what they'll see in the viewer — both the qualitative outputs and the quantitative benchmark. + +### Step 3: As runs complete, capture timing data + +When each subagent task completes, you receive a notification containing `total_tokens` and `duration_ms`. Save this data immediately to `timing.json` in the run directory: + +```json +{ + "total_tokens": 84852, + "duration_ms": 23332, + "total_duration_seconds": 23.3 +} +``` + +This is the only opportunity to capture this data — it comes through the task notification and isn't persisted elsewhere. Process each notification as it arrives rather than trying to batch them. + +### Step 4: Grade, aggregate, and launch the viewer + +Once all runs are done: + +1. **Grade each run** — spawn a grader subagent (or grade inline) that reads `agents/grader.md` and evaluates each assertion against the outputs. Save results to `grading.json` in each run directory. The grading.json expectations array must use the fields `text`, `passed`, and `evidence` (not `name`/`met`/`details` or other variants) — the viewer depends on these exact field names. For assertions that can be checked programmatically, write and run a script rather than eyeballing it — scripts are faster, more reliable, and can be reused across iterations. + +2. **Aggregate into benchmark** — run the aggregation script from the skill-creator directory: + ```bash + python -m scripts.aggregate_benchmark /iteration-N --skill-name + ``` + This produces `benchmark.json` and `benchmark.md` with pass_rate, time, and tokens for each configuration, with mean ± stddev and the delta. If generating benchmark.json manually, see `references/schemas.md` for the exact schema the viewer expects. +Put each with_skill version before its baseline counterpart. + +3. **Do an analyst pass** — read the benchmark data and surface patterns the aggregate stats might hide. See `agents/analyzer.md` (the "Analyzing Benchmark Results" section) for what to look for — things like assertions that always pass regardless of skill (non-discriminating), high-variance evals (possibly flaky), and time/token tradeoffs. + +4. **Launch the viewer** with both qualitative outputs and quantitative data: + ```bash + nohup python /eval-viewer/generate_review.py \ + /iteration-N \ + --skill-name "my-skill" \ + --benchmark /iteration-N/benchmark.json \ + > /dev/null 2>&1 & + VIEWER_PID=$! + ``` + For iteration 2+, also pass `--previous-workspace /iteration-`. + + **Cowork / headless environments:** If `webbrowser.open()` is not available or the environment has no display, use `--static ` to write a standalone HTML file instead of starting a server. Feedback will be downloaded as a `feedback.json` file when the user clicks "Submit All Reviews". After download, copy `feedback.json` into the workspace directory for the next iteration to pick up. + +Note: please use generate_review.py to create the viewer; there's no need to write custom HTML. + +5. **Tell the user** something like: "I've opened the results in your browser. There are two tabs — 'Outputs' lets you click through each test case and leave feedback, 'Benchmark' shows the quantitative comparison. When you're done, come back here and let me know." + +### What the user sees in the viewer + +The "Outputs" tab shows one test case at a time: +- **Prompt**: the task that was given +- **Output**: the files the skill produced, rendered inline where possible +- **Previous Output** (iteration 2+): collapsed section showing last iteration's output +- **Formal Grades** (if grading was run): collapsed section showing assertion pass/fail +- **Feedback**: a textbox that auto-saves as they type +- **Previous Feedback** (iteration 2+): their comments from last time, shown below the textbox + +The "Benchmark" tab shows the stats summary: pass rates, timing, and token usage for each configuration, with per-eval breakdowns and analyst observations. + +Navigation is via prev/next buttons or arrow keys. When done, they click "Submit All Reviews" which saves all feedback to `feedback.json`. + +### Step 5: Read the feedback + +When the user tells you they're done, read `feedback.json`: + +```json +{ + "reviews": [ + {"run_id": "eval-0-with_skill", "feedback": "the chart is missing axis labels", "timestamp": "..."}, + {"run_id": "eval-1-with_skill", "feedback": "", "timestamp": "..."}, + {"run_id": "eval-2-with_skill", "feedback": "perfect, love this", "timestamp": "..."} + ], + "status": "complete" +} +``` + +Empty feedback means the user thought it was fine. Focus your improvements on the test cases where the user had specific complaints. + +Kill the viewer server when you're done with it: + +```bash +kill $VIEWER_PID 2>/dev/null +``` + +--- + +## Improving the skill + +This is the heart of the loop. You've run the test cases, the user has reviewed the results, and now you need to make the skill better based on their feedback. + +### How to think about improvements + +1. **Generalize from the feedback.** The big picture thing that's happening here is that we're trying to create skills that can be used a million times (maybe literally, maybe even more who knows) across many different prompts. Here you and the user are iterating on only a few examples over and over again because it helps move faster. The user knows these examples in and out and it's quick for them to assess new outputs. But if the skill you and the user are codeveloping works only for those examples, it's useless. Rather than put in fiddly overfitty changes, or oppressively constrictive MUSTs, if there's some stubborn issue, you might try branching out and using different metaphors, or recommending different patterns of working. It's relatively cheap to try and maybe you'll land on something great. + +2. **Keep the prompt lean.** Remove things that aren't pulling their weight. Make sure to read the transcripts, not just the final outputs — if it looks like the skill is making the model waste a bunch of time doing things that are unproductive, you can try getting rid of the parts of the skill that are making it do that and seeing what happens. + +3. **Explain the why.** Try hard to explain the **why** behind everything you're asking the model to do. Today's LLMs are *smart*. They have good theory of mind and when given a good harness can go beyond rote instructions and really make things happen. Even if the feedback from the user is terse or frustrated, try to actually understand the task and why the user is writing what they wrote, and what they actually wrote, and then transmit this understanding into the instructions. If you find yourself writing ALWAYS or NEVER in all caps, or using super rigid structures, that's a yellow flag — if possible, reframe and explain the reasoning so that the model understands why the thing you're asking for is important. That's a more humane, powerful, and effective approach. + +4. **Look for repeated work across test cases.** Read the transcripts from the test runs and notice if the subagents all independently wrote similar helper scripts or took the same multi-step approach to something. If all 3 test cases resulted in the subagent writing a `create_docx.py` or a `build_chart.py`, that's a strong signal the skill should bundle that script. Write it once, put it in `scripts/`, and tell the skill to use it. This saves every future invocation from reinventing the wheel. + +This task is pretty important (we are trying to create billions a year in economic value here!) and your thinking time is not the blocker; take your time and really mull things over. I'd suggest writing a draft revision and then looking at it anew and making improvements. Really do your best to get into the head of the user and understand what they want and need. + +### The iteration loop + +After improving the skill: + +1. Apply your improvements to the skill +2. Rerun all test cases into a new `iteration-/` directory, including baseline runs. If you're creating a new skill, the baseline is always `without_skill` (no skill) — that stays the same across iterations. If you're improving an existing skill, use your judgment on what makes sense as the baseline: the original version the user came in with, or the previous iteration. +3. Launch the reviewer with `--previous-workspace` pointing at the previous iteration +4. Wait for the user to review and tell you they're done +5. Read the new feedback, improve again, repeat + +Keep going until: +- The user says they're happy +- The feedback is all empty (everything looks good) +- You're not making meaningful progress + +--- + +## Advanced: Blind comparison + +For situations where you want a more rigorous comparison between two versions of a skill (e.g., the user asks "is the new version actually better?"), there's a blind comparison system. Read `agents/comparator.md` and `agents/analyzer.md` for the details. The basic idea is: give two outputs to an independent agent without telling it which is which, and let it judge quality. Then analyze why the winner won. + +This is optional, requires subagents, and most users won't need it. The human review loop is usually sufficient. + +--- + +## Description Optimization + +The description field in SKILL.md frontmatter is the primary mechanism that determines whether Claude invokes a skill. After creating or improving a skill, offer to optimize the description for better triggering accuracy. + +### Step 1: Generate trigger eval queries + +Create 20 eval queries — a mix of should-trigger and should-not-trigger. Save as JSON: + +```json +[ + {"query": "the user prompt", "should_trigger": true}, + {"query": "another prompt", "should_trigger": false} +] +``` + +The queries must be realistic and something a Claude Code or Claude.ai user would actually type. Not abstract requests, but requests that are concrete and specific and have a good amount of detail. For instance, file paths, personal context about the user's job or situation, column names and values, company names, URLs. A little bit of backstory. Some might be in lowercase or contain abbreviations or typos or casual speech. Use a mix of different lengths, and focus on edge cases rather than making them clear-cut (the user will get a chance to sign off on them). + +Bad: `"Format this data"`, `"Extract text from PDF"`, `"Create a chart"` + +Good: `"ok so my boss just sent me this xlsx file (its in my downloads, called something like 'Q4 sales final FINAL v2.xlsx') and she wants me to add a column that shows the profit margin as a percentage. The revenue is in column C and costs are in column D i think"` + +For the **should-trigger** queries (8-10), think about coverage. You want different phrasings of the same intent — some formal, some casual. Include cases where the user doesn't explicitly name the skill or file type but clearly needs it. Throw in some uncommon use cases and cases where this skill competes with another but should win. + +For the **should-not-trigger** queries (8-10), the most valuable ones are the near-misses — queries that share keywords or concepts with the skill but actually need something different. Think adjacent domains, ambiguous phrasing where a naive keyword match would trigger but shouldn't, and cases where the query touches on something the skill does but in a context where another tool is more appropriate. + +The key thing to avoid: don't make should-not-trigger queries obviously irrelevant. "Write a fibonacci function" as a negative test for a PDF skill is too easy — it doesn't test anything. The negative cases should be genuinely tricky. + +### Step 2: Review with user + +Present the eval set to the user for review using the HTML template: + +1. Read the template from `assets/eval_review.html` +2. Replace the placeholders: + - `__EVAL_DATA_PLACEHOLDER__` → the JSON array of eval items (no quotes around it — it's a JS variable assignment) + - `__SKILL_NAME_PLACEHOLDER__` → the skill's name + - `__SKILL_DESCRIPTION_PLACEHOLDER__` → the skill's current description +3. Write to a temp file (e.g., `/tmp/eval_review_.html`) and open it: `open /tmp/eval_review_.html` +4. The user can edit queries, toggle should-trigger, add/remove entries, then click "Export Eval Set" +5. The file downloads to `~/Downloads/eval_set.json` — check the Downloads folder for the most recent version in case there are multiple (e.g., `eval_set (1).json`) + +This step matters — bad eval queries lead to bad descriptions. + +### Step 3: Run the optimization loop + +Tell the user: "This will take some time — I'll run the optimization loop in the background and check on it periodically." + +Save the eval set to the workspace, then run in the background: + +```bash +python -m scripts.run_loop \ + --eval-set \ + --skill-path \ + --model \ + --max-iterations 5 \ + --verbose +``` + +Use the model ID from your system prompt (the one powering the current session) so the triggering test matches what the user actually experiences. + +While it runs, periodically tail the output to give the user updates on which iteration it's on and what the scores look like. + +This handles the full optimization loop automatically. It splits the eval set into 60% train and 40% held-out test, evaluates the current description (running each query 3 times to get a reliable trigger rate), then calls Claude to propose improvements based on what failed. It re-evaluates each new description on both train and test, iterating up to 5 times. When it's done, it opens an HTML report in the browser showing the results per iteration and returns JSON with `best_description` — selected by test score rather than train score to avoid overfitting. + +### How skill triggering works + +Understanding the triggering mechanism helps design better eval queries. Skills appear in Claude's `available_skills` list with their name + description, and Claude decides whether to consult a skill based on that description. The important thing to know is that Claude only consults skills for tasks it can't easily handle on its own — simple, one-step queries like "read this PDF" may not trigger a skill even if the description matches perfectly, because Claude can handle them directly with basic tools. Complex, multi-step, or specialized queries reliably trigger skills when the description matches. + +This means your eval queries should be substantive enough that Claude would actually benefit from consulting a skill. Simple queries like "read file X" are poor test cases — they won't trigger skills regardless of description quality. + +### Step 4: Apply the result + +Take `best_description` from the JSON output and update the skill's SKILL.md frontmatter. Show the user before/after and report the scores. + +--- + +### Package and Present (only if `present_files` tool is available) + +Check whether you have access to the `present_files` tool. If you don't, skip this step. If you do, package the skill and present the .skill file to the user: + +```bash +python -m scripts.package_skill +``` + +After packaging, direct the user to the resulting `.skill` file path so they can install it. + +--- + +## Claude.ai-specific instructions + +In Claude.ai, the core workflow is the same (draft → test → review → improve → repeat), but because Claude.ai doesn't have subagents, some mechanics change. Here's what to adapt: + +**Running test cases**: No subagents means no parallel execution. For each test case, read the skill's SKILL.md, then follow its instructions to accomplish the test prompt yourself. Do them one at a time. This is less rigorous than independent subagents (you wrote the skill and you're also running it, so you have full context), but it's a useful sanity check — and the human review step compensates. Skip the baseline runs — just use the skill to complete the task as requested. + +**Reviewing results**: If you can't open a browser (e.g., Claude.ai's VM has no display, or you're on a remote server), skip the browser reviewer entirely. Instead, present results directly in the conversation. For each test case, show the prompt and the output. If the output is a file the user needs to see (like a .docx or .xlsx), save it to the filesystem and tell them where it is so they can download and inspect it. Ask for feedback inline: "How does this look? Anything you'd change?" + +**Benchmarking**: Skip the quantitative benchmarking — it relies on baseline comparisons which aren't meaningful without subagents. Focus on qualitative feedback from the user. + +**The iteration loop**: Same as before — improve the skill, rerun the test cases, ask for feedback — just without the browser reviewer in the middle. You can still organize results into iteration directories on the filesystem if you have one. + +**Description optimization**: This section requires the `claude` CLI tool (specifically `claude -p`) which is only available in Claude Code. Skip it if you're on Claude.ai. + +**Blind comparison**: Requires subagents. Skip it. + +**Packaging**: The `package_skill.py` script works anywhere with Python and a filesystem. On Claude.ai, you can run it and the user can download the resulting `.skill` file. + +**Updating an existing skill**: The user might be asking you to update an existing skill, not create a new one. In this case: +- **Preserve the original name.** Note the skill's directory name and `name` frontmatter field -- use them unchanged. E.g., if the installed skill is `research-helper`, output `research-helper.skill` (not `research-helper-v2`). +- **Copy to a writeable location before editing.** The installed skill path may be read-only. Copy to `/tmp/skill-name/`, edit there, and package from the copy. +- **If packaging manually, stage in `/tmp/` first**, then copy to the output directory -- direct writes may fail due to permissions. + +--- + +## Cowork-Specific Instructions + +If you're in Cowork, the main things to know are: + +- You have subagents, so the main workflow (spawn test cases in parallel, run baselines, grade, etc.) all works. (However, if you run into severe problems with timeouts, it's OK to run the test prompts in series rather than parallel.) +- You don't have a browser or display, so when generating the eval viewer, use `--static ` to write a standalone HTML file instead of starting a server. Then proffer a link that the user can click to open the HTML in their browser. +- For whatever reason, the Cowork setup seems to disincline Claude from generating the eval viewer after running the tests, so just to reiterate: whether you're in Cowork or in Claude Code, after running tests, you should always generate the eval viewer for the human to look at examples before revising the skill yourself and trying to make corrections, using `generate_review.py` (not writing your own boutique html code). Sorry in advance but I'm gonna go all caps here: GENERATE THE EVAL VIEWER *BEFORE* evaluating inputs yourself. You want to get them in front of the human ASAP! +- Feedback works differently: since there's no running server, the viewer's "Submit All Reviews" button will download `feedback.json` as a file. You can then read it from there (you may have to request access first). +- Packaging works — `package_skill.py` just needs Python and a filesystem. +- Description optimization (`run_loop.py` / `run_eval.py`) should work in Cowork just fine since it uses `claude -p` via subprocess, not a browser, but please save it until you've fully finished making the skill and the user agrees it's in good shape. +- **Updating an existing skill**: The user might be asking you to update an existing skill, not create a new one. Follow the update guidance in the claude.ai section above. + +--- + +## Reference files + +The agents/ directory contains instructions for specialized subagents. Read them when you need to spawn the relevant subagent. + +- `agents/grader.md` — How to evaluate assertions against outputs +- `agents/comparator.md` — How to do blind A/B comparison between two outputs +- `agents/analyzer.md` — How to analyze why one version beat another + +The references/ directory has additional documentation: +- `references/schemas.md` — JSON structures for evals.json, grading.json, etc. + +--- + +Repeating one more time the core loop here for emphasis: + +- Figure out what the skill is about +- Draft or edit the skill +- Run claude-with-access-to-the-skill on test prompts +- With the user, evaluate the outputs: + - Create benchmark.json and run `eval-viewer/generate_review.py` to help the user review them + - Run quantitative evals +- Repeat until you and the user are satisfied +- Package the final skill and return it to the user. + +Please add steps to your TodoList, if you have such a thing, to make sure you don't forget. If you're in Cowork, please specifically put "Create evals JSON and run `eval-viewer/generate_review.py` so human can review test cases" in your TodoList to make sure it happens. + +Good luck! diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/agents/analyzer.md b/libs/hexagent_demo/backend/skills/public/skill-creator/agents/analyzer.md new file mode 100644 index 00000000..14e41d60 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/agents/analyzer.md @@ -0,0 +1,274 @@ +# Post-hoc Analyzer Agent + +Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions. + +## Role + +After the blind comparator determines a winner, the Post-hoc Analyzer "unblids" the results by examining the skills and transcripts. The goal is to extract actionable insights: what made the winner better, and how can the loser be improved? + +## Inputs + +You receive these parameters in your prompt: + +- **winner**: "A" or "B" (from blind comparison) +- **winner_skill_path**: Path to the skill that produced the winning output +- **winner_transcript_path**: Path to the execution transcript for the winner +- **loser_skill_path**: Path to the skill that produced the losing output +- **loser_transcript_path**: Path to the execution transcript for the loser +- **comparison_result_path**: Path to the blind comparator's output JSON +- **output_path**: Where to save the analysis results + +## Process + +### Step 1: Read Comparison Result + +1. Read the blind comparator's output at comparison_result_path +2. Note the winning side (A or B), the reasoning, and any scores +3. Understand what the comparator valued in the winning output + +### Step 2: Read Both Skills + +1. Read the winner skill's SKILL.md and key referenced files +2. Read the loser skill's SKILL.md and key referenced files +3. Identify structural differences: + - Instructions clarity and specificity + - Script/tool usage patterns + - Example coverage + - Edge case handling + +### Step 3: Read Both Transcripts + +1. Read the winner's transcript +2. Read the loser's transcript +3. Compare execution patterns: + - How closely did each follow their skill's instructions? + - What tools were used differently? + - Where did the loser diverge from optimal behavior? + - Did either encounter errors or make recovery attempts? + +### Step 4: Analyze Instruction Following + +For each transcript, evaluate: +- Did the agent follow the skill's explicit instructions? +- Did the agent use the skill's provided tools/scripts? +- Were there missed opportunities to leverage skill content? +- Did the agent add unnecessary steps not in the skill? + +Score instruction following 1-10 and note specific issues. + +### Step 5: Identify Winner Strengths + +Determine what made the winner better: +- Clearer instructions that led to better behavior? +- Better scripts/tools that produced better output? +- More comprehensive examples that guided edge cases? +- Better error handling guidance? + +Be specific. Quote from skills/transcripts where relevant. + +### Step 6: Identify Loser Weaknesses + +Determine what held the loser back: +- Ambiguous instructions that led to suboptimal choices? +- Missing tools/scripts that forced workarounds? +- Gaps in edge case coverage? +- Poor error handling that caused failures? + +### Step 7: Generate Improvement Suggestions + +Based on the analysis, produce actionable suggestions for improving the loser skill: +- Specific instruction changes to make +- Tools/scripts to add or modify +- Examples to include +- Edge cases to address + +Prioritize by impact. Focus on changes that would have changed the outcome. + +### Step 8: Write Analysis Results + +Save structured analysis to `{output_path}`. + +## Output Format + +Write a JSON file with this structure: + +```json +{ + "comparison_summary": { + "winner": "A", + "winner_skill": "path/to/winner/skill", + "loser_skill": "path/to/loser/skill", + "comparator_reasoning": "Brief summary of why comparator chose winner" + }, + "winner_strengths": [ + "Clear step-by-step instructions for handling multi-page documents", + "Included validation script that caught formatting errors", + "Explicit guidance on fallback behavior when OCR fails" + ], + "loser_weaknesses": [ + "Vague instruction 'process the document appropriately' led to inconsistent behavior", + "No script for validation, agent had to improvise and made errors", + "No guidance on OCR failure, agent gave up instead of trying alternatives" + ], + "instruction_following": { + "winner": { + "score": 9, + "issues": [ + "Minor: skipped optional logging step" + ] + }, + "loser": { + "score": 6, + "issues": [ + "Did not use the skill's formatting template", + "Invented own approach instead of following step 3", + "Missed the 'always validate output' instruction" + ] + } + }, + "improvement_suggestions": [ + { + "priority": "high", + "category": "instructions", + "suggestion": "Replace 'process the document appropriately' with explicit steps: 1) Extract text, 2) Identify sections, 3) Format per template", + "expected_impact": "Would eliminate ambiguity that caused inconsistent behavior" + }, + { + "priority": "high", + "category": "tools", + "suggestion": "Add validate_output.py script similar to winner skill's validation approach", + "expected_impact": "Would catch formatting errors before final output" + }, + { + "priority": "medium", + "category": "error_handling", + "suggestion": "Add fallback instructions: 'If OCR fails, try: 1) different resolution, 2) image preprocessing, 3) manual extraction'", + "expected_impact": "Would prevent early failure on difficult documents" + } + ], + "transcript_insights": { + "winner_execution_pattern": "Read skill -> Followed 5-step process -> Used validation script -> Fixed 2 issues -> Produced output", + "loser_execution_pattern": "Read skill -> Unclear on approach -> Tried 3 different methods -> No validation -> Output had errors" + } +} +``` + +## Guidelines + +- **Be specific**: Quote from skills and transcripts, don't just say "instructions were unclear" +- **Be actionable**: Suggestions should be concrete changes, not vague advice +- **Focus on skill improvements**: The goal is to improve the losing skill, not critique the agent +- **Prioritize by impact**: Which changes would most likely have changed the outcome? +- **Consider causation**: Did the skill weakness actually cause the worse output, or is it incidental? +- **Stay objective**: Analyze what happened, don't editorialize +- **Think about generalization**: Would this improvement help on other evals too? + +## Categories for Suggestions + +Use these categories to organize improvement suggestions: + +| Category | Description | +|----------|-------------| +| `instructions` | Changes to the skill's prose instructions | +| `tools` | Scripts, templates, or utilities to add/modify | +| `examples` | Example inputs/outputs to include | +| `error_handling` | Guidance for handling failures | +| `structure` | Reorganization of skill content | +| `references` | External docs or resources to add | + +## Priority Levels + +- **high**: Would likely change the outcome of this comparison +- **medium**: Would improve quality but may not change win/loss +- **low**: Nice to have, marginal improvement + +--- + +# Analyzing Benchmark Results + +When analyzing benchmark results, the analyzer's purpose is to **surface patterns and anomalies** across multiple runs, not suggest skill improvements. + +## Role + +Review all benchmark run results and generate freeform notes that help the user understand skill performance. Focus on patterns that wouldn't be visible from aggregate metrics alone. + +## Inputs + +You receive these parameters in your prompt: + +- **benchmark_data_path**: Path to the in-progress benchmark.json with all run results +- **skill_path**: Path to the skill being benchmarked +- **output_path**: Where to save the notes (as JSON array of strings) + +## Process + +### Step 1: Read Benchmark Data + +1. Read the benchmark.json containing all run results +2. Note the configurations tested (with_skill, without_skill) +3. Understand the run_summary aggregates already calculated + +### Step 2: Analyze Per-Assertion Patterns + +For each expectation across all runs: +- Does it **always pass** in both configurations? (may not differentiate skill value) +- Does it **always fail** in both configurations? (may be broken or beyond capability) +- Does it **always pass with skill but fail without**? (skill clearly adds value here) +- Does it **always fail with skill but pass without**? (skill may be hurting) +- Is it **highly variable**? (flaky expectation or non-deterministic behavior) + +### Step 3: Analyze Cross-Eval Patterns + +Look for patterns across evals: +- Are certain eval types consistently harder/easier? +- Do some evals show high variance while others are stable? +- Are there surprising results that contradict expectations? + +### Step 4: Analyze Metrics Patterns + +Look at time_seconds, tokens, tool_calls: +- Does the skill significantly increase execution time? +- Is there high variance in resource usage? +- Are there outlier runs that skew the aggregates? + +### Step 5: Generate Notes + +Write freeform observations as a list of strings. Each note should: +- State a specific observation +- Be grounded in the data (not speculation) +- Help the user understand something the aggregate metrics don't show + +Examples: +- "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value" +- "Eval 3 shows high variance (50% ± 40%) - run 2 had an unusual failure that may be flaky" +- "Without-skill runs consistently fail on table extraction expectations (0% pass rate)" +- "Skill adds 13s average execution time but improves pass rate by 50%" +- "Token usage is 80% higher with skill, primarily due to script output parsing" +- "All 3 without-skill runs for eval 1 produced empty output" + +### Step 6: Write Notes + +Save notes to `{output_path}` as a JSON array of strings: + +```json +[ + "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value", + "Eval 3 shows high variance (50% ± 40%) - run 2 had an unusual failure", + "Without-skill runs consistently fail on table extraction expectations", + "Skill adds 13s average execution time but improves pass rate by 50%" +] +``` + +## Guidelines + +**DO:** +- Report what you observe in the data +- Be specific about which evals, expectations, or runs you're referring to +- Note patterns that aggregate metrics would hide +- Provide context that helps interpret the numbers + +**DO NOT:** +- Suggest improvements to the skill (that's for the improvement step, not benchmarking) +- Make subjective quality judgments ("the output was good/bad") +- Speculate about causes without evidence +- Repeat information already in the run_summary aggregates diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/agents/comparator.md b/libs/hexagent_demo/backend/skills/public/skill-creator/agents/comparator.md new file mode 100644 index 00000000..80e00eb4 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/agents/comparator.md @@ -0,0 +1,202 @@ +# Blind Comparator Agent + +Compare two outputs WITHOUT knowing which skill produced them. + +## Role + +The Blind Comparator judges which output better accomplishes the eval task. You receive two outputs labeled A and B, but you do NOT know which skill produced which. This prevents bias toward a particular skill or approach. + +Your judgment is based purely on output quality and task completion. + +## Inputs + +You receive these parameters in your prompt: + +- **output_a_path**: Path to the first output file or directory +- **output_b_path**: Path to the second output file or directory +- **eval_prompt**: The original task/prompt that was executed +- **expectations**: List of expectations to check (optional - may be empty) + +## Process + +### Step 1: Read Both Outputs + +1. Examine output A (file or directory) +2. Examine output B (file or directory) +3. Note the type, structure, and content of each +4. If outputs are directories, examine all relevant files inside + +### Step 2: Understand the Task + +1. Read the eval_prompt carefully +2. Identify what the task requires: + - What should be produced? + - What qualities matter (accuracy, completeness, format)? + - What would distinguish a good output from a poor one? + +### Step 3: Generate Evaluation Rubric + +Based on the task, generate a rubric with two dimensions: + +**Content Rubric** (what the output contains): +| Criterion | 1 (Poor) | 3 (Acceptable) | 5 (Excellent) | +|-----------|----------|----------------|---------------| +| Correctness | Major errors | Minor errors | Fully correct | +| Completeness | Missing key elements | Mostly complete | All elements present | +| Accuracy | Significant inaccuracies | Minor inaccuracies | Accurate throughout | + +**Structure Rubric** (how the output is organized): +| Criterion | 1 (Poor) | 3 (Acceptable) | 5 (Excellent) | +|-----------|----------|----------------|---------------| +| Organization | Disorganized | Reasonably organized | Clear, logical structure | +| Formatting | Inconsistent/broken | Mostly consistent | Professional, polished | +| Usability | Difficult to use | Usable with effort | Easy to use | + +Adapt criteria to the specific task. For example: +- PDF form → "Field alignment", "Text readability", "Data placement" +- Document → "Section structure", "Heading hierarchy", "Paragraph flow" +- Data output → "Schema correctness", "Data types", "Completeness" + +### Step 4: Evaluate Each Output Against the Rubric + +For each output (A and B): + +1. **Score each criterion** on the rubric (1-5 scale) +2. **Calculate dimension totals**: Content score, Structure score +3. **Calculate overall score**: Average of dimension scores, scaled to 1-10 + +### Step 5: Check Assertions (if provided) + +If expectations are provided: + +1. Check each expectation against output A +2. Check each expectation against output B +3. Count pass rates for each output +4. Use expectation scores as secondary evidence (not the primary decision factor) + +### Step 6: Determine the Winner + +Compare A and B based on (in priority order): + +1. **Primary**: Overall rubric score (content + structure) +2. **Secondary**: Assertion pass rates (if applicable) +3. **Tiebreaker**: If truly equal, declare a TIE + +Be decisive - ties should be rare. One output is usually better, even if marginally. + +### Step 7: Write Comparison Results + +Save results to a JSON file at the path specified (or `comparison.json` if not specified). + +## Output Format + +Write a JSON file with this structure: + +```json +{ + "winner": "A", + "reasoning": "Output A provides a complete solution with proper formatting and all required fields. Output B is missing the date field and has formatting inconsistencies.", + "rubric": { + "A": { + "content": { + "correctness": 5, + "completeness": 5, + "accuracy": 4 + }, + "structure": { + "organization": 4, + "formatting": 5, + "usability": 4 + }, + "content_score": 4.7, + "structure_score": 4.3, + "overall_score": 9.0 + }, + "B": { + "content": { + "correctness": 3, + "completeness": 2, + "accuracy": 3 + }, + "structure": { + "organization": 3, + "formatting": 2, + "usability": 3 + }, + "content_score": 2.7, + "structure_score": 2.7, + "overall_score": 5.4 + } + }, + "output_quality": { + "A": { + "score": 9, + "strengths": ["Complete solution", "Well-formatted", "All fields present"], + "weaknesses": ["Minor style inconsistency in header"] + }, + "B": { + "score": 5, + "strengths": ["Readable output", "Correct basic structure"], + "weaknesses": ["Missing date field", "Formatting inconsistencies", "Partial data extraction"] + } + }, + "expectation_results": { + "A": { + "passed": 4, + "total": 5, + "pass_rate": 0.80, + "details": [ + {"text": "Output includes name", "passed": true}, + {"text": "Output includes date", "passed": true}, + {"text": "Format is PDF", "passed": true}, + {"text": "Contains signature", "passed": false}, + {"text": "Readable text", "passed": true} + ] + }, + "B": { + "passed": 3, + "total": 5, + "pass_rate": 0.60, + "details": [ + {"text": "Output includes name", "passed": true}, + {"text": "Output includes date", "passed": false}, + {"text": "Format is PDF", "passed": true}, + {"text": "Contains signature", "passed": false}, + {"text": "Readable text", "passed": true} + ] + } + } +} +``` + +If no expectations were provided, omit the `expectation_results` field entirely. + +## Field Descriptions + +- **winner**: "A", "B", or "TIE" +- **reasoning**: Clear explanation of why the winner was chosen (or why it's a tie) +- **rubric**: Structured rubric evaluation for each output + - **content**: Scores for content criteria (correctness, completeness, accuracy) + - **structure**: Scores for structure criteria (organization, formatting, usability) + - **content_score**: Average of content criteria (1-5) + - **structure_score**: Average of structure criteria (1-5) + - **overall_score**: Combined score scaled to 1-10 +- **output_quality**: Summary quality assessment + - **score**: 1-10 rating (should match rubric overall_score) + - **strengths**: List of positive aspects + - **weaknesses**: List of issues or shortcomings +- **expectation_results**: (Only if expectations provided) + - **passed**: Number of expectations that passed + - **total**: Total number of expectations + - **pass_rate**: Fraction passed (0.0 to 1.0) + - **details**: Individual expectation results + +## Guidelines + +- **Stay blind**: DO NOT try to infer which skill produced which output. Judge purely on output quality. +- **Be specific**: Cite specific examples when explaining strengths and weaknesses. +- **Be decisive**: Choose a winner unless outputs are genuinely equivalent. +- **Output quality first**: Assertion scores are secondary to overall task completion. +- **Be objective**: Don't favor outputs based on style preferences; focus on correctness and completeness. +- **Explain your reasoning**: The reasoning field should make it clear why you chose the winner. +- **Handle edge cases**: If both outputs fail, pick the one that fails less badly. If both are excellent, pick the one that's marginally better. diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/agents/grader.md b/libs/hexagent_demo/backend/skills/public/skill-creator/agents/grader.md new file mode 100644 index 00000000..558ab05c --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/agents/grader.md @@ -0,0 +1,223 @@ +# Grader Agent + +Evaluate expectations against an execution transcript and outputs. + +## Role + +The Grader reviews a transcript and output files, then determines whether each expectation passes or fails. Provide clear evidence for each judgment. + +You have two jobs: grade the outputs, and critique the evals themselves. A passing grade on a weak assertion is worse than useless — it creates false confidence. When you notice an assertion that's trivially satisfied, or an important outcome that no assertion checks, say so. + +## Inputs + +You receive these parameters in your prompt: + +- **expectations**: List of expectations to evaluate (strings) +- **transcript_path**: Path to the execution transcript (markdown file) +- **outputs_dir**: Directory containing output files from execution + +## Process + +### Step 1: Read the Transcript + +1. Read the transcript file completely +2. Note the eval prompt, execution steps, and final result +3. Identify any issues or errors documented + +### Step 2: Examine Output Files + +1. List files in outputs_dir +2. Read/examine each file relevant to the expectations. If outputs aren't plain text, use the inspection tools provided in your prompt — don't rely solely on what the transcript says the executor produced. +3. Note contents, structure, and quality + +### Step 3: Evaluate Each Assertion + +For each expectation: + +1. **Search for evidence** in the transcript and outputs +2. **Determine verdict**: + - **PASS**: Clear evidence the expectation is true AND the evidence reflects genuine task completion, not just surface-level compliance + - **FAIL**: No evidence, or evidence contradicts the expectation, or the evidence is superficial (e.g., correct filename but empty/wrong content) +3. **Cite the evidence**: Quote the specific text or describe what you found + +### Step 4: Extract and Verify Claims + +Beyond the predefined expectations, extract implicit claims from the outputs and verify them: + +1. **Extract claims** from the transcript and outputs: + - Factual statements ("The form has 12 fields") + - Process claims ("Used pypdf to fill the form") + - Quality claims ("All fields were filled correctly") + +2. **Verify each claim**: + - **Factual claims**: Can be checked against the outputs or external sources + - **Process claims**: Can be verified from the transcript + - **Quality claims**: Evaluate whether the claim is justified + +3. **Flag unverifiable claims**: Note claims that cannot be verified with available information + +This catches issues that predefined expectations might miss. + +### Step 5: Read User Notes + +If `{outputs_dir}/user_notes.md` exists: +1. Read it and note any uncertainties or issues flagged by the executor +2. Include relevant concerns in the grading output +3. These may reveal problems even when expectations pass + +### Step 6: Critique the Evals + +After grading, consider whether the evals themselves could be improved. Only surface suggestions when there's a clear gap. + +Good suggestions test meaningful outcomes — assertions that are hard to satisfy without actually doing the work correctly. Think about what makes an assertion *discriminating*: it passes when the skill genuinely succeeds and fails when it doesn't. + +Suggestions worth raising: +- An assertion that passed but would also pass for a clearly wrong output (e.g., checking filename existence but not file content) +- An important outcome you observed — good or bad — that no assertion covers at all +- An assertion that can't actually be verified from the available outputs + +Keep the bar high. The goal is to flag things the eval author would say "good catch" about, not to nitpick every assertion. + +### Step 7: Write Grading Results + +Save results to `{outputs_dir}/../grading.json` (sibling to outputs_dir). + +## Grading Criteria + +**PASS when**: +- The transcript or outputs clearly demonstrate the expectation is true +- Specific evidence can be cited +- The evidence reflects genuine substance, not just surface compliance (e.g., a file exists AND contains correct content, not just the right filename) + +**FAIL when**: +- No evidence found for the expectation +- Evidence contradicts the expectation +- The expectation cannot be verified from available information +- The evidence is superficial — the assertion is technically satisfied but the underlying task outcome is wrong or incomplete +- The output appears to meet the assertion by coincidence rather than by actually doing the work + +**When uncertain**: The burden of proof to pass is on the expectation. + +### Step 8: Read Executor Metrics and Timing + +1. If `{outputs_dir}/metrics.json` exists, read it and include in grading output +2. If `{outputs_dir}/../timing.json` exists, read it and include timing data + +## Output Format + +Write a JSON file with this structure: + +```json +{ + "expectations": [ + { + "text": "The output includes the name 'John Smith'", + "passed": true, + "evidence": "Found in transcript Step 3: 'Extracted names: John Smith, Sarah Johnson'" + }, + { + "text": "The spreadsheet has a SUM formula in cell B10", + "passed": false, + "evidence": "No spreadsheet was created. The output was a text file." + }, + { + "text": "The assistant used the skill's OCR script", + "passed": true, + "evidence": "Transcript Step 2 shows: 'Tool: Bash - python ocr_script.py image.png'" + } + ], + "summary": { + "passed": 2, + "failed": 1, + "total": 3, + "pass_rate": 0.67 + }, + "execution_metrics": { + "tool_calls": { + "Read": 5, + "Write": 2, + "Bash": 8 + }, + "total_tool_calls": 15, + "total_steps": 6, + "errors_encountered": 0, + "output_chars": 12450, + "transcript_chars": 3200 + }, + "timing": { + "executor_duration_seconds": 165.0, + "grader_duration_seconds": 26.0, + "total_duration_seconds": 191.0 + }, + "claims": [ + { + "claim": "The form has 12 fillable fields", + "type": "factual", + "verified": true, + "evidence": "Counted 12 fields in field_info.json" + }, + { + "claim": "All required fields were populated", + "type": "quality", + "verified": false, + "evidence": "Reference section was left blank despite data being available" + } + ], + "user_notes_summary": { + "uncertainties": ["Used 2023 data, may be stale"], + "needs_review": [], + "workarounds": ["Fell back to text overlay for non-fillable fields"] + }, + "eval_feedback": { + "suggestions": [ + { + "assertion": "The output includes the name 'John Smith'", + "reason": "A hallucinated document that mentions the name would also pass — consider checking it appears as the primary contact with matching phone and email from the input" + }, + { + "reason": "No assertion checks whether the extracted phone numbers match the input — I observed incorrect numbers in the output that went uncaught" + } + ], + "overall": "Assertions check presence but not correctness. Consider adding content verification." + } +} +``` + +## Field Descriptions + +- **expectations**: Array of graded expectations + - **text**: The original expectation text + - **passed**: Boolean - true if expectation passes + - **evidence**: Specific quote or description supporting the verdict +- **summary**: Aggregate statistics + - **passed**: Count of passed expectations + - **failed**: Count of failed expectations + - **total**: Total expectations evaluated + - **pass_rate**: Fraction passed (0.0 to 1.0) +- **execution_metrics**: Copied from executor's metrics.json (if available) + - **output_chars**: Total character count of output files (proxy for tokens) + - **transcript_chars**: Character count of transcript +- **timing**: Wall clock timing from timing.json (if available) + - **executor_duration_seconds**: Time spent in executor subagent + - **total_duration_seconds**: Total elapsed time for the run +- **claims**: Extracted and verified claims from the output + - **claim**: The statement being verified + - **type**: "factual", "process", or "quality" + - **verified**: Boolean - whether the claim holds + - **evidence**: Supporting or contradicting evidence +- **user_notes_summary**: Issues flagged by the executor + - **uncertainties**: Things the executor wasn't sure about + - **needs_review**: Items requiring human attention + - **workarounds**: Places where the skill didn't work as expected +- **eval_feedback**: Improvement suggestions for the evals (only when warranted) + - **suggestions**: List of concrete suggestions, each with a `reason` and optionally an `assertion` it relates to + - **overall**: Brief assessment — can be "No suggestions, evals look solid" if nothing to flag + +## Guidelines + +- **Be objective**: Base verdicts on evidence, not assumptions +- **Be specific**: Quote the exact text that supports your verdict +- **Be thorough**: Check both transcript and output files +- **Be consistent**: Apply the same standard to each expectation +- **Explain failures**: Make it clear why evidence was insufficient +- **No partial credit**: Each expectation is pass or fail, not partial diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/assets/eval_review.html b/libs/hexagent_demo/backend/skills/public/skill-creator/assets/eval_review.html new file mode 100644 index 00000000..938ff32a --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/assets/eval_review.html @@ -0,0 +1,146 @@ + + + + + + Eval Set Review - __SKILL_NAME_PLACEHOLDER__ + + + + + + +

    Eval Set Review: __SKILL_NAME_PLACEHOLDER__

    +

    Current description: __SKILL_DESCRIPTION_PLACEHOLDER__

    + +
    + + +
    + + + + + + + + + + +
    QueryShould TriggerActions
    + +

    + + + + diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/eval-viewer/generate_review.py b/libs/hexagent_demo/backend/skills/public/skill-creator/eval-viewer/generate_review.py new file mode 100644 index 00000000..7fa59786 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/eval-viewer/generate_review.py @@ -0,0 +1,471 @@ +#!/usr/bin/env python3 +"""Generate and serve a review page for eval results. + +Reads the workspace directory, discovers runs (directories with outputs/), +embeds all output data into a self-contained HTML page, and serves it via +a tiny HTTP server. Feedback auto-saves to feedback.json in the workspace. + +Usage: + python generate_review.py [--port PORT] [--skill-name NAME] + python generate_review.py --previous-feedback /path/to/old/feedback.json + +No dependencies beyond the Python stdlib are required. +""" + +import argparse +import base64 +import json +import mimetypes +import os +import re +import signal +import subprocess +import sys +import time +import webbrowser +from functools import partial +from http.server import HTTPServer, BaseHTTPRequestHandler +from pathlib import Path + +# Files to exclude from output listings +METADATA_FILES = {"transcript.md", "user_notes.md", "metrics.json"} + +# Extensions we render as inline text +TEXT_EXTENSIONS = { + ".txt", ".md", ".json", ".csv", ".py", ".js", ".ts", ".tsx", ".jsx", + ".yaml", ".yml", ".xml", ".html", ".css", ".sh", ".rb", ".go", ".rs", + ".java", ".c", ".cpp", ".h", ".hpp", ".sql", ".r", ".toml", +} + +# Extensions we render as inline images +IMAGE_EXTENSIONS = {".png", ".jpg", ".jpeg", ".gif", ".svg", ".webp"} + +# MIME type overrides for common types +MIME_OVERRIDES = { + ".svg": "image/svg+xml", + ".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", + ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", + ".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation", +} + + +def get_mime_type(path: Path) -> str: + ext = path.suffix.lower() + if ext in MIME_OVERRIDES: + return MIME_OVERRIDES[ext] + mime, _ = mimetypes.guess_type(str(path)) + return mime or "application/octet-stream" + + +def find_runs(workspace: Path) -> list[dict]: + """Recursively find directories that contain an outputs/ subdirectory.""" + runs: list[dict] = [] + _find_runs_recursive(workspace, workspace, runs) + runs.sort(key=lambda r: (r.get("eval_id", float("inf")), r["id"])) + return runs + + +def _find_runs_recursive(root: Path, current: Path, runs: list[dict]) -> None: + if not current.is_dir(): + return + + outputs_dir = current / "outputs" + if outputs_dir.is_dir(): + run = build_run(root, current) + if run: + runs.append(run) + return + + skip = {"node_modules", ".git", "__pycache__", "skill", "inputs"} + for child in sorted(current.iterdir()): + if child.is_dir() and child.name not in skip: + _find_runs_recursive(root, child, runs) + + +def build_run(root: Path, run_dir: Path) -> dict | None: + """Build a run dict with prompt, outputs, and grading data.""" + prompt = "" + eval_id = None + + # Try eval_metadata.json + for candidate in [run_dir / "eval_metadata.json", run_dir.parent / "eval_metadata.json"]: + if candidate.exists(): + try: + metadata = json.loads(candidate.read_text()) + prompt = metadata.get("prompt", "") + eval_id = metadata.get("eval_id") + except (json.JSONDecodeError, OSError): + pass + if prompt: + break + + # Fall back to transcript.md + if not prompt: + for candidate in [run_dir / "transcript.md", run_dir / "outputs" / "transcript.md"]: + if candidate.exists(): + try: + text = candidate.read_text() + match = re.search(r"## Eval Prompt\n\n([\s\S]*?)(?=\n##|$)", text) + if match: + prompt = match.group(1).strip() + except OSError: + pass + if prompt: + break + + if not prompt: + prompt = "(No prompt found)" + + run_id = str(run_dir.relative_to(root)).replace("/", "-").replace("\\", "-") + + # Collect output files + outputs_dir = run_dir / "outputs" + output_files: list[dict] = [] + if outputs_dir.is_dir(): + for f in sorted(outputs_dir.iterdir()): + if f.is_file() and f.name not in METADATA_FILES: + output_files.append(embed_file(f)) + + # Load grading if present + grading = None + for candidate in [run_dir / "grading.json", run_dir.parent / "grading.json"]: + if candidate.exists(): + try: + grading = json.loads(candidate.read_text()) + except (json.JSONDecodeError, OSError): + pass + if grading: + break + + return { + "id": run_id, + "prompt": prompt, + "eval_id": eval_id, + "outputs": output_files, + "grading": grading, + } + + +def embed_file(path: Path) -> dict: + """Read a file and return an embedded representation.""" + ext = path.suffix.lower() + mime = get_mime_type(path) + + if ext in TEXT_EXTENSIONS: + try: + content = path.read_text(errors="replace") + except OSError: + content = "(Error reading file)" + return { + "name": path.name, + "type": "text", + "content": content, + } + elif ext in IMAGE_EXTENSIONS: + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "image", + "mime": mime, + "data_uri": f"data:{mime};base64,{b64}", + } + elif ext == ".pdf": + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "pdf", + "data_uri": f"data:{mime};base64,{b64}", + } + elif ext == ".xlsx": + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "xlsx", + "data_b64": b64, + } + else: + # Binary / unknown — base64 download link + try: + raw = path.read_bytes() + b64 = base64.b64encode(raw).decode("ascii") + except OSError: + return {"name": path.name, "type": "error", "content": "(Error reading file)"} + return { + "name": path.name, + "type": "binary", + "mime": mime, + "data_uri": f"data:{mime};base64,{b64}", + } + + +def load_previous_iteration(workspace: Path) -> dict[str, dict]: + """Load previous iteration's feedback and outputs. + + Returns a map of run_id -> {"feedback": str, "outputs": list[dict]}. + """ + result: dict[str, dict] = {} + + # Load feedback + feedback_map: dict[str, str] = {} + feedback_path = workspace / "feedback.json" + if feedback_path.exists(): + try: + data = json.loads(feedback_path.read_text()) + feedback_map = { + r["run_id"]: r["feedback"] + for r in data.get("reviews", []) + if r.get("feedback", "").strip() + } + except (json.JSONDecodeError, OSError, KeyError): + pass + + # Load runs (to get outputs) + prev_runs = find_runs(workspace) + for run in prev_runs: + result[run["id"]] = { + "feedback": feedback_map.get(run["id"], ""), + "outputs": run.get("outputs", []), + } + + # Also add feedback for run_ids that had feedback but no matching run + for run_id, fb in feedback_map.items(): + if run_id not in result: + result[run_id] = {"feedback": fb, "outputs": []} + + return result + + +def generate_html( + runs: list[dict], + skill_name: str, + previous: dict[str, dict] | None = None, + benchmark: dict | None = None, +) -> str: + """Generate the complete standalone HTML page with embedded data.""" + template_path = Path(__file__).parent / "viewer.html" + template = template_path.read_text() + + # Build previous_feedback and previous_outputs maps for the template + previous_feedback: dict[str, str] = {} + previous_outputs: dict[str, list[dict]] = {} + if previous: + for run_id, data in previous.items(): + if data.get("feedback"): + previous_feedback[run_id] = data["feedback"] + if data.get("outputs"): + previous_outputs[run_id] = data["outputs"] + + embedded = { + "skill_name": skill_name, + "runs": runs, + "previous_feedback": previous_feedback, + "previous_outputs": previous_outputs, + } + if benchmark: + embedded["benchmark"] = benchmark + + data_json = json.dumps(embedded) + + return template.replace("/*__EMBEDDED_DATA__*/", f"const EMBEDDED_DATA = {data_json};") + + +# --------------------------------------------------------------------------- +# HTTP server (stdlib only, zero dependencies) +# --------------------------------------------------------------------------- + +def _kill_port(port: int) -> None: + """Kill any process listening on the given port.""" + try: + result = subprocess.run( + ["lsof", "-ti", f":{port}"], + capture_output=True, text=True, timeout=5, + ) + for pid_str in result.stdout.strip().split("\n"): + if pid_str.strip(): + try: + os.kill(int(pid_str.strip()), signal.SIGTERM) + except (ProcessLookupError, ValueError): + pass + if result.stdout.strip(): + time.sleep(0.5) + except subprocess.TimeoutExpired: + pass + except FileNotFoundError: + print("Note: lsof not found, cannot check if port is in use", file=sys.stderr) + +class ReviewHandler(BaseHTTPRequestHandler): + """Serves the review HTML and handles feedback saves. + + Regenerates the HTML on each page load so that refreshing the browser + picks up new eval outputs without restarting the server. + """ + + def __init__( + self, + workspace: Path, + skill_name: str, + feedback_path: Path, + previous: dict[str, dict], + benchmark_path: Path | None, + *args, + **kwargs, + ): + self.workspace = workspace + self.skill_name = skill_name + self.feedback_path = feedback_path + self.previous = previous + self.benchmark_path = benchmark_path + super().__init__(*args, **kwargs) + + def do_GET(self) -> None: + if self.path == "/" or self.path == "/index.html": + # Regenerate HTML on each request (re-scans workspace for new outputs) + runs = find_runs(self.workspace) + benchmark = None + if self.benchmark_path and self.benchmark_path.exists(): + try: + benchmark = json.loads(self.benchmark_path.read_text()) + except (json.JSONDecodeError, OSError): + pass + html = generate_html(runs, self.skill_name, self.previous, benchmark) + content = html.encode("utf-8") + self.send_response(200) + self.send_header("Content-Type", "text/html; charset=utf-8") + self.send_header("Content-Length", str(len(content))) + self.end_headers() + self.wfile.write(content) + elif self.path == "/api/feedback": + data = b"{}" + if self.feedback_path.exists(): + data = self.feedback_path.read_bytes() + self.send_response(200) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(data))) + self.end_headers() + self.wfile.write(data) + else: + self.send_error(404) + + def do_POST(self) -> None: + if self.path == "/api/feedback": + length = int(self.headers.get("Content-Length", 0)) + body = self.rfile.read(length) + try: + data = json.loads(body) + if not isinstance(data, dict) or "reviews" not in data: + raise ValueError("Expected JSON object with 'reviews' key") + self.feedback_path.write_text(json.dumps(data, indent=2) + "\n") + resp = b'{"ok":true}' + self.send_response(200) + except (json.JSONDecodeError, OSError, ValueError) as e: + resp = json.dumps({"error": str(e)}).encode() + self.send_response(500) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(resp))) + self.end_headers() + self.wfile.write(resp) + else: + self.send_error(404) + + def log_message(self, format: str, *args: object) -> None: + # Suppress request logging to keep terminal clean + pass + + +def main() -> None: + parser = argparse.ArgumentParser(description="Generate and serve eval review") + parser.add_argument("workspace", type=Path, help="Path to workspace directory") + parser.add_argument("--port", "-p", type=int, default=3117, help="Server port (default: 3117)") + parser.add_argument("--skill-name", "-n", type=str, default=None, help="Skill name for header") + parser.add_argument( + "--previous-workspace", type=Path, default=None, + help="Path to previous iteration's workspace (shows old outputs and feedback as context)", + ) + parser.add_argument( + "--benchmark", type=Path, default=None, + help="Path to benchmark.json to show in the Benchmark tab", + ) + parser.add_argument( + "--static", "-s", type=Path, default=None, + help="Write standalone HTML to this path instead of starting a server", + ) + args = parser.parse_args() + + workspace = args.workspace.resolve() + if not workspace.is_dir(): + print(f"Error: {workspace} is not a directory", file=sys.stderr) + sys.exit(1) + + runs = find_runs(workspace) + if not runs: + print(f"No runs found in {workspace}", file=sys.stderr) + sys.exit(1) + + skill_name = args.skill_name or workspace.name.replace("-workspace", "") + feedback_path = workspace / "feedback.json" + + previous: dict[str, dict] = {} + if args.previous_workspace: + previous = load_previous_iteration(args.previous_workspace.resolve()) + + benchmark_path = args.benchmark.resolve() if args.benchmark else None + benchmark = None + if benchmark_path and benchmark_path.exists(): + try: + benchmark = json.loads(benchmark_path.read_text()) + except (json.JSONDecodeError, OSError): + pass + + if args.static: + html = generate_html(runs, skill_name, previous, benchmark) + args.static.parent.mkdir(parents=True, exist_ok=True) + args.static.write_text(html) + print(f"\n Static viewer written to: {args.static}\n") + sys.exit(0) + + # Kill any existing process on the target port + port = args.port + _kill_port(port) + handler = partial(ReviewHandler, workspace, skill_name, feedback_path, previous, benchmark_path) + try: + server = HTTPServer(("127.0.0.1", port), handler) + except OSError: + # Port still in use after kill attempt — find a free one + server = HTTPServer(("127.0.0.1", 0), handler) + port = server.server_address[1] + + url = f"http://localhost:{port}" + print(f"\n Eval Viewer") + print(f" ─────────────────────────────────") + print(f" URL: {url}") + print(f" Workspace: {workspace}") + print(f" Feedback: {feedback_path}") + if previous: + print(f" Previous: {args.previous_workspace} ({len(previous)} runs)") + if benchmark_path: + print(f" Benchmark: {benchmark_path}") + print(f"\n Press Ctrl+C to stop.\n") + + webbrowser.open(url) + + try: + server.serve_forever() + except KeyboardInterrupt: + print("\nStopped.") + server.server_close() + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/eval-viewer/viewer.html b/libs/hexagent_demo/backend/skills/public/skill-creator/eval-viewer/viewer.html new file mode 100644 index 00000000..6d8e9634 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/eval-viewer/viewer.html @@ -0,0 +1,1325 @@ + + + + + + Eval Review + + + + + + + +
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    + + + + diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/references/output-patterns.md b/libs/hexagent_demo/backend/skills/public/skill-creator/references/output-patterns.md new file mode 100644 index 00000000..073ddda5 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/references/output-patterns.md @@ -0,0 +1,82 @@ +# Output Patterns + +Use these patterns when skills need to produce consistent, high-quality output. + +## Template Pattern + +Provide templates for output format. Match the level of strictness to your needs. + +**For strict requirements (like API responses or data formats):** + +```markdown +## Report structure + +ALWAYS use this exact template structure: + +# [Analysis Title] + +## Executive summary +[One-paragraph overview of key findings] + +## Key findings +- Finding 1 with supporting data +- Finding 2 with supporting data +- Finding 3 with supporting data + +## Recommendations +1. Specific actionable recommendation +2. Specific actionable recommendation +``` + +**For flexible guidance (when adaptation is useful):** + +```markdown +## Report structure + +Here is a sensible default format, but use your best judgment: + +# [Analysis Title] + +## Executive summary +[Overview] + +## Key findings +[Adapt sections based on what you discover] + +## Recommendations +[Tailor to the specific context] + +Adjust sections as needed for the specific analysis type. +``` + +## Examples Pattern + +For skills where output quality depends on seeing examples, provide input/output pairs: + +```markdown +## Commit message format + +Generate commit messages following these examples: + +**Example 1:** +Input: Added user authentication with JWT tokens +Output: +``` +feat(auth): implement JWT-based authentication + +Add login endpoint and token validation middleware +``` + +**Example 2:** +Input: Fixed bug where dates displayed incorrectly in reports +Output: +``` +fix(reports): correct date formatting in timezone conversion + +Use UTC timestamps consistently across report generation +``` + +Follow this style: type(scope): brief description, then detailed explanation. +``` + +Examples help Claude understand the desired style and level of detail more clearly than descriptions alone. diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/references/schemas.md b/libs/hexagent_demo/backend/skills/public/skill-creator/references/schemas.md new file mode 100644 index 00000000..b6eeaa2d --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/references/schemas.md @@ -0,0 +1,430 @@ +# JSON Schemas + +This document defines the JSON schemas used by skill-creator. + +--- + +## evals.json + +Defines the evals for a skill. Located at `evals/evals.json` within the skill directory. + +```json +{ + "skill_name": "example-skill", + "evals": [ + { + "id": 1, + "prompt": "User's example prompt", + "expected_output": "Description of expected result", + "files": ["evals/files/sample1.pdf"], + "expectations": [ + "The output includes X", + "The skill used script Y" + ] + } + ] +} +``` + +**Fields:** +- `skill_name`: Name matching the skill's frontmatter +- `evals[].id`: Unique integer identifier +- `evals[].prompt`: The task to execute +- `evals[].expected_output`: Human-readable description of success +- `evals[].files`: Optional list of input file paths (relative to skill root) +- `evals[].expectations`: List of verifiable statements + +--- + +## history.json + +Tracks version progression in Improve mode. Located at workspace root. + +```json +{ + "started_at": "2026-01-15T10:30:00Z", + "skill_name": "pdf", + "current_best": "v2", + "iterations": [ + { + "version": "v0", + "parent": null, + "expectation_pass_rate": 0.65, + "grading_result": "baseline", + "is_current_best": false + }, + { + "version": "v1", + "parent": "v0", + "expectation_pass_rate": 0.75, + "grading_result": "won", + "is_current_best": false + }, + { + "version": "v2", + "parent": "v1", + "expectation_pass_rate": 0.85, + "grading_result": "won", + "is_current_best": true + } + ] +} +``` + +**Fields:** +- `started_at`: ISO timestamp of when improvement started +- `skill_name`: Name of the skill being improved +- `current_best`: Version identifier of the best performer +- `iterations[].version`: Version identifier (v0, v1, ...) +- `iterations[].parent`: Parent version this was derived from +- `iterations[].expectation_pass_rate`: Pass rate from grading +- `iterations[].grading_result`: "baseline", "won", "lost", or "tie" +- `iterations[].is_current_best`: Whether this is the current best version + +--- + +## grading.json + +Output from the grader agent. Located at `/grading.json`. + +```json +{ + "expectations": [ + { + "text": "The output includes the name 'John Smith'", + "passed": true, + "evidence": "Found in transcript Step 3: 'Extracted names: John Smith, Sarah Johnson'" + }, + { + "text": "The spreadsheet has a SUM formula in cell B10", + "passed": false, + "evidence": "No spreadsheet was created. The output was a text file." + } + ], + "summary": { + "passed": 2, + "failed": 1, + "total": 3, + "pass_rate": 0.67 + }, + "execution_metrics": { + "tool_calls": { + "Read": 5, + "Write": 2, + "Bash": 8 + }, + "total_tool_calls": 15, + "total_steps": 6, + "errors_encountered": 0, + "output_chars": 12450, + "transcript_chars": 3200 + }, + "timing": { + "executor_duration_seconds": 165.0, + "grader_duration_seconds": 26.0, + "total_duration_seconds": 191.0 + }, + "claims": [ + { + "claim": "The form has 12 fillable fields", + "type": "factual", + "verified": true, + "evidence": "Counted 12 fields in field_info.json" + } + ], + "user_notes_summary": { + "uncertainties": ["Used 2023 data, may be stale"], + "needs_review": [], + "workarounds": ["Fell back to text overlay for non-fillable fields"] + }, + "eval_feedback": { + "suggestions": [ + { + "assertion": "The output includes the name 'John Smith'", + "reason": "A hallucinated document that mentions the name would also pass" + } + ], + "overall": "Assertions check presence but not correctness." + } +} +``` + +**Fields:** +- `expectations[]`: Graded expectations with evidence +- `summary`: Aggregate pass/fail counts +- `execution_metrics`: Tool usage and output size (from executor's metrics.json) +- `timing`: Wall clock timing (from timing.json) +- `claims`: Extracted and verified claims from the output +- `user_notes_summary`: Issues flagged by the executor +- `eval_feedback`: (optional) Improvement suggestions for the evals, only present when the grader identifies issues worth raising + +--- + +## metrics.json + +Output from the executor agent. Located at `/outputs/metrics.json`. + +```json +{ + "tool_calls": { + "Read": 5, + "Write": 2, + "Bash": 8, + "Edit": 1, + "Glob": 2, + "Grep": 0 + }, + "total_tool_calls": 18, + "total_steps": 6, + "files_created": ["filled_form.pdf", "field_values.json"], + "errors_encountered": 0, + "output_chars": 12450, + "transcript_chars": 3200 +} +``` + +**Fields:** +- `tool_calls`: Count per tool type +- `total_tool_calls`: Sum of all tool calls +- `total_steps`: Number of major execution steps +- `files_created`: List of output files created +- `errors_encountered`: Number of errors during execution +- `output_chars`: Total character count of output files +- `transcript_chars`: Character count of transcript + +--- + +## timing.json + +Wall clock timing for a run. Located at `/timing.json`. + +**How to capture:** When a subagent task completes, the task notification includes `total_tokens` and `duration_ms`. Save these immediately — they are not persisted anywhere else and cannot be recovered after the fact. + +```json +{ + "total_tokens": 84852, + "duration_ms": 23332, + "total_duration_seconds": 23.3, + "executor_start": "2026-01-15T10:30:00Z", + "executor_end": "2026-01-15T10:32:45Z", + "executor_duration_seconds": 165.0, + "grader_start": "2026-01-15T10:32:46Z", + "grader_end": "2026-01-15T10:33:12Z", + "grader_duration_seconds": 26.0 +} +``` + +--- + +## benchmark.json + +Output from Benchmark mode. Located at `benchmarks//benchmark.json`. + +```json +{ + "metadata": { + "skill_name": "pdf", + "skill_path": "/path/to/pdf", + "executor_model": "claude-sonnet-4-20250514", + "analyzer_model": "most-capable-model", + "timestamp": "2026-01-15T10:30:00Z", + "evals_run": [1, 2, 3], + "runs_per_configuration": 3 + }, + + "runs": [ + { + "eval_id": 1, + "eval_name": "Ocean", + "configuration": "with_skill", + "run_number": 1, + "result": { + "pass_rate": 0.85, + "passed": 6, + "failed": 1, + "total": 7, + "time_seconds": 42.5, + "tokens": 3800, + "tool_calls": 18, + "errors": 0 + }, + "expectations": [ + {"text": "...", "passed": true, "evidence": "..."} + ], + "notes": [ + "Used 2023 data, may be stale", + "Fell back to text overlay for non-fillable fields" + ] + } + ], + + "run_summary": { + "with_skill": { + "pass_rate": {"mean": 0.85, "stddev": 0.05, "min": 0.80, "max": 0.90}, + "time_seconds": {"mean": 45.0, "stddev": 12.0, "min": 32.0, "max": 58.0}, + "tokens": {"mean": 3800, "stddev": 400, "min": 3200, "max": 4100} + }, + "without_skill": { + "pass_rate": {"mean": 0.35, "stddev": 0.08, "min": 0.28, "max": 0.45}, + "time_seconds": {"mean": 32.0, "stddev": 8.0, "min": 24.0, "max": 42.0}, + "tokens": {"mean": 2100, "stddev": 300, "min": 1800, "max": 2500} + }, + "delta": { + "pass_rate": "+0.50", + "time_seconds": "+13.0", + "tokens": "+1700" + } + }, + + "notes": [ + "Assertion 'Output is a PDF file' passes 100% in both configurations - may not differentiate skill value", + "Eval 3 shows high variance (50% ± 40%) - may be flaky or model-dependent", + "Without-skill runs consistently fail on table extraction expectations", + "Skill adds 13s average execution time but improves pass rate by 50%" + ] +} +``` + +**Fields:** +- `metadata`: Information about the benchmark run + - `skill_name`: Name of the skill + - `timestamp`: When the benchmark was run + - `evals_run`: List of eval names or IDs + - `runs_per_configuration`: Number of runs per config (e.g. 3) +- `runs[]`: Individual run results + - `eval_id`: Numeric eval identifier + - `eval_name`: Human-readable eval name (used as section header in the viewer) + - `configuration`: Must be `"with_skill"` or `"without_skill"` (the viewer uses this exact string for grouping and color coding) + - `run_number`: Integer run number (1, 2, 3...) + - `result`: Nested object with `pass_rate`, `passed`, `total`, `time_seconds`, `tokens`, `errors` +- `run_summary`: Statistical aggregates per configuration + - `with_skill` / `without_skill`: Each contains `pass_rate`, `time_seconds`, `tokens` objects with `mean` and `stddev` fields + - `delta`: Difference strings like `"+0.50"`, `"+13.0"`, `"+1700"` +- `notes`: Freeform observations from the analyzer + +**Important:** The viewer reads these field names exactly. Using `config` instead of `configuration`, or putting `pass_rate` at the top level of a run instead of nested under `result`, will cause the viewer to show empty/zero values. Always reference this schema when generating benchmark.json manually. + +--- + +## comparison.json + +Output from blind comparator. Located at `/comparison-N.json`. + +```json +{ + "winner": "A", + "reasoning": "Output A provides a complete solution with proper formatting and all required fields. Output B is missing the date field and has formatting inconsistencies.", + "rubric": { + "A": { + "content": { + "correctness": 5, + "completeness": 5, + "accuracy": 4 + }, + "structure": { + "organization": 4, + "formatting": 5, + "usability": 4 + }, + "content_score": 4.7, + "structure_score": 4.3, + "overall_score": 9.0 + }, + "B": { + "content": { + "correctness": 3, + "completeness": 2, + "accuracy": 3 + }, + "structure": { + "organization": 3, + "formatting": 2, + "usability": 3 + }, + "content_score": 2.7, + "structure_score": 2.7, + "overall_score": 5.4 + } + }, + "output_quality": { + "A": { + "score": 9, + "strengths": ["Complete solution", "Well-formatted", "All fields present"], + "weaknesses": ["Minor style inconsistency in header"] + }, + "B": { + "score": 5, + "strengths": ["Readable output", "Correct basic structure"], + "weaknesses": ["Missing date field", "Formatting inconsistencies", "Partial data extraction"] + } + }, + "expectation_results": { + "A": { + "passed": 4, + "total": 5, + "pass_rate": 0.80, + "details": [ + {"text": "Output includes name", "passed": true} + ] + }, + "B": { + "passed": 3, + "total": 5, + "pass_rate": 0.60, + "details": [ + {"text": "Output includes name", "passed": true} + ] + } + } +} +``` + +--- + +## analysis.json + +Output from post-hoc analyzer. Located at `/analysis.json`. + +```json +{ + "comparison_summary": { + "winner": "A", + "winner_skill": "path/to/winner/skill", + "loser_skill": "path/to/loser/skill", + "comparator_reasoning": "Brief summary of why comparator chose winner" + }, + "winner_strengths": [ + "Clear step-by-step instructions for handling multi-page documents", + "Included validation script that caught formatting errors" + ], + "loser_weaknesses": [ + "Vague instruction 'process the document appropriately' led to inconsistent behavior", + "No script for validation, agent had to improvise" + ], + "instruction_following": { + "winner": { + "score": 9, + "issues": ["Minor: skipped optional logging step"] + }, + "loser": { + "score": 6, + "issues": [ + "Did not use the skill's formatting template", + "Invented own approach instead of following step 3" + ] + } + }, + "improvement_suggestions": [ + { + "priority": "high", + "category": "instructions", + "suggestion": "Replace 'process the document appropriately' with explicit steps", + "expected_impact": "Would eliminate ambiguity that caused inconsistent behavior" + } + ], + "transcript_insights": { + "winner_execution_pattern": "Read skill -> Followed 5-step process -> Used validation script", + "loser_execution_pattern": "Read skill -> Unclear on approach -> Tried 3 different methods" + } +} +``` diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/references/workflows.md b/libs/hexagent_demo/backend/skills/public/skill-creator/references/workflows.md new file mode 100644 index 00000000..54b01740 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/references/workflows.md @@ -0,0 +1,28 @@ +# Workflow Patterns + +## Sequential Workflows + +For complex tasks, break operations into clear, sequential steps. It is often helpful to give Claude an overview of the process towards the beginning of SKILL.md: + +```markdown +Filling a PDF form involves these steps: + +1. Analyze the form (run analyze_form.py) +2. Create field mapping (edit fields.json) +3. Validate mapping (run validate_fields.py) +4. Fill the form (run fill_form.py) +5. Verify output (run verify_output.py) +``` + +## Conditional Workflows + +For tasks with branching logic, guide Claude through decision points: + +```markdown +1. Determine the modification type: + **Creating new content?** → Follow "Creation workflow" below + **Editing existing content?** → Follow "Editing workflow" below + +2. Creation workflow: [steps] +3. Editing workflow: [steps] +``` diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/aggregate_benchmark.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/aggregate_benchmark.py new file mode 100644 index 00000000..fa44b384 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/aggregate_benchmark.py @@ -0,0 +1,401 @@ +#!/usr/bin/env python3 +""" +Aggregate individual run results into benchmark summary statistics. + +Reads grading.json files from run directories and produces: +- run_summary with mean, stddev, min, max for each metric +- delta between with_skill and without_skill configurations + +Usage: + python aggregate_benchmark.py + +Example: + python aggregate_benchmark.py benchmarks/2026-01-15T10-30-00/ + +The script supports two directory layouts: + + Workspace layout (from skill-creator iterations): + / + └── eval-N/ + ├── with_skill/ + │ ├── run-1/grading.json + │ └── run-2/grading.json + └── without_skill/ + ├── run-1/grading.json + └── run-2/grading.json + + Legacy layout (with runs/ subdirectory): + / + └── runs/ + └── eval-N/ + ├── with_skill/ + │ └── run-1/grading.json + └── without_skill/ + └── run-1/grading.json +""" + +import argparse +import json +import math +import sys +from datetime import datetime, timezone +from pathlib import Path + + +def calculate_stats(values: list[float]) -> dict: + """Calculate mean, stddev, min, max for a list of values.""" + if not values: + return {"mean": 0.0, "stddev": 0.0, "min": 0.0, "max": 0.0} + + n = len(values) + mean = sum(values) / n + + if n > 1: + variance = sum((x - mean) ** 2 for x in values) / (n - 1) + stddev = math.sqrt(variance) + else: + stddev = 0.0 + + return { + "mean": round(mean, 4), + "stddev": round(stddev, 4), + "min": round(min(values), 4), + "max": round(max(values), 4) + } + + +def load_run_results(benchmark_dir: Path) -> dict: + """ + Load all run results from a benchmark directory. + + Returns dict keyed by config name (e.g. "with_skill"/"without_skill", + or "new_skill"/"old_skill"), each containing a list of run results. + """ + # Support both layouts: eval dirs directly under benchmark_dir, or under runs/ + runs_dir = benchmark_dir / "runs" + if runs_dir.exists(): + search_dir = runs_dir + elif list(benchmark_dir.glob("eval-*")): + search_dir = benchmark_dir + else: + print(f"No eval directories found in {benchmark_dir} or {benchmark_dir / 'runs'}") + return {} + + results: dict[str, list] = {} + + for eval_idx, eval_dir in enumerate(sorted(search_dir.glob("eval-*"))): + metadata_path = eval_dir / "eval_metadata.json" + if metadata_path.exists(): + try: + with open(metadata_path, encoding="utf-8") as mf: + eval_id = json.load(mf).get("eval_id", eval_idx) + except (json.JSONDecodeError, OSError): + eval_id = eval_idx + else: + try: + eval_id = int(eval_dir.name.split("-")[1]) + except ValueError: + eval_id = eval_idx + + # Discover config directories dynamically rather than hardcoding names + for config_dir in sorted(eval_dir.iterdir()): + if not config_dir.is_dir(): + continue + # Skip non-config directories (inputs, outputs, etc.) + if not list(config_dir.glob("run-*")): + continue + config = config_dir.name + if config not in results: + results[config] = [] + + for run_dir in sorted(config_dir.glob("run-*")): + run_number = int(run_dir.name.split("-")[1]) + grading_file = run_dir / "grading.json" + + if not grading_file.exists(): + print(f"Warning: grading.json not found in {run_dir}") + continue + + try: + with open(grading_file, encoding="utf-8") as f: + grading = json.load(f) + except json.JSONDecodeError as e: + print(f"Warning: Invalid JSON in {grading_file}: {e}") + continue + + # Extract metrics + result = { + "eval_id": eval_id, + "run_number": run_number, + "pass_rate": grading.get("summary", {}).get("pass_rate", 0.0), + "passed": grading.get("summary", {}).get("passed", 0), + "failed": grading.get("summary", {}).get("failed", 0), + "total": grading.get("summary", {}).get("total", 0), + } + + # Extract timing — check grading.json first, then sibling timing.json + timing = grading.get("timing", {}) + result["time_seconds"] = timing.get("total_duration_seconds", 0.0) + timing_file = run_dir / "timing.json" + if result["time_seconds"] == 0.0 and timing_file.exists(): + try: + with open(timing_file, encoding="utf-8") as tf: + timing_data = json.load(tf) + result["time_seconds"] = timing_data.get("total_duration_seconds", 0.0) + result["tokens"] = timing_data.get("total_tokens", 0) + except json.JSONDecodeError: + pass + + # Extract metrics if available + metrics = grading.get("execution_metrics", {}) + result["tool_calls"] = metrics.get("total_tool_calls", 0) + if not result.get("tokens"): + result["tokens"] = metrics.get("output_chars", 0) + result["errors"] = metrics.get("errors_encountered", 0) + + # Extract expectations — viewer requires fields: text, passed, evidence + raw_expectations = grading.get("expectations", []) + for exp in raw_expectations: + if "text" not in exp or "passed" not in exp: + print(f"Warning: expectation in {grading_file} missing required fields (text, passed, evidence): {exp}") + result["expectations"] = raw_expectations + + # Extract notes from user_notes_summary + notes_summary = grading.get("user_notes_summary", {}) + notes = [] + notes.extend(notes_summary.get("uncertainties", [])) + notes.extend(notes_summary.get("needs_review", [])) + notes.extend(notes_summary.get("workarounds", [])) + result["notes"] = notes + + results[config].append(result) + + return results + + +def aggregate_results(results: dict) -> dict: + """ + Aggregate run results into summary statistics. + + Returns run_summary with stats for each configuration and delta. + """ + run_summary = {} + configs = list(results.keys()) + + for config in configs: + runs = results.get(config, []) + + if not runs: + run_summary[config] = { + "pass_rate": {"mean": 0.0, "stddev": 0.0, "min": 0.0, "max": 0.0}, + "time_seconds": {"mean": 0.0, "stddev": 0.0, "min": 0.0, "max": 0.0}, + "tokens": {"mean": 0, "stddev": 0, "min": 0, "max": 0} + } + continue + + pass_rates = [r["pass_rate"] for r in runs] + times = [r["time_seconds"] for r in runs] + tokens = [r.get("tokens", 0) for r in runs] + + run_summary[config] = { + "pass_rate": calculate_stats(pass_rates), + "time_seconds": calculate_stats(times), + "tokens": calculate_stats(tokens) + } + + # Calculate delta between the first two configs (if two exist) + if len(configs) >= 2: + primary = run_summary.get(configs[0], {}) + baseline = run_summary.get(configs[1], {}) + else: + primary = run_summary.get(configs[0], {}) if configs else {} + baseline = {} + + delta_pass_rate = primary.get("pass_rate", {}).get("mean", 0) - baseline.get("pass_rate", {}).get("mean", 0) + delta_time = primary.get("time_seconds", {}).get("mean", 0) - baseline.get("time_seconds", {}).get("mean", 0) + delta_tokens = primary.get("tokens", {}).get("mean", 0) - baseline.get("tokens", {}).get("mean", 0) + + run_summary["delta"] = { + "pass_rate": f"{delta_pass_rate:+.2f}", + "time_seconds": f"{delta_time:+.1f}", + "tokens": f"{delta_tokens:+.0f}" + } + + return run_summary + + +def generate_benchmark(benchmark_dir: Path, skill_name: str = "", skill_path: str = "") -> dict: + """ + Generate complete benchmark.json from run results. + """ + results = load_run_results(benchmark_dir) + run_summary = aggregate_results(results) + + # Build runs array for benchmark.json + runs = [] + for config in results: + for result in results[config]: + runs.append({ + "eval_id": result["eval_id"], + "configuration": config, + "run_number": result["run_number"], + "result": { + "pass_rate": result["pass_rate"], + "passed": result["passed"], + "failed": result["failed"], + "total": result["total"], + "time_seconds": result["time_seconds"], + "tokens": result.get("tokens", 0), + "tool_calls": result.get("tool_calls", 0), + "errors": result.get("errors", 0) + }, + "expectations": result["expectations"], + "notes": result["notes"] + }) + + # Determine eval IDs from results + eval_ids = sorted(set( + r["eval_id"] + for config in results.values() + for r in config + )) + + benchmark = { + "metadata": { + "skill_name": skill_name or "", + "skill_path": skill_path or "", + "executor_model": "", + "analyzer_model": "", + "timestamp": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"), + "evals_run": eval_ids, + "runs_per_configuration": 3 + }, + "runs": runs, + "run_summary": run_summary, + "notes": [] # To be filled by analyzer + } + + return benchmark + + +def generate_markdown(benchmark: dict) -> str: + """Generate human-readable benchmark.md from benchmark data.""" + metadata = benchmark["metadata"] + run_summary = benchmark["run_summary"] + + # Determine config names (excluding "delta") + configs = [k for k in run_summary if k != "delta"] + config_a = configs[0] if len(configs) >= 1 else "config_a" + config_b = configs[1] if len(configs) >= 2 else "config_b" + label_a = config_a.replace("_", " ").title() + label_b = config_b.replace("_", " ").title() + + lines = [ + f"# Skill Benchmark: {metadata['skill_name']}", + "", + f"**Model**: {metadata['executor_model']}", + f"**Date**: {metadata['timestamp']}", + f"**Evals**: {', '.join(map(str, metadata['evals_run']))} ({metadata['runs_per_configuration']} runs each per configuration)", + "", + "## Summary", + "", + f"| Metric | {label_a} | {label_b} | Delta |", + "|--------|------------|---------------|-------|", + ] + + a_summary = run_summary.get(config_a, {}) + b_summary = run_summary.get(config_b, {}) + delta = run_summary.get("delta", {}) + + # Format pass rate + a_pr = a_summary.get("pass_rate", {}) + b_pr = b_summary.get("pass_rate", {}) + lines.append(f"| Pass Rate | {a_pr.get('mean', 0)*100:.0f}% ± {a_pr.get('stddev', 0)*100:.0f}% | {b_pr.get('mean', 0)*100:.0f}% ± {b_pr.get('stddev', 0)*100:.0f}% | {delta.get('pass_rate', '—')} |") + + # Format time + a_time = a_summary.get("time_seconds", {}) + b_time = b_summary.get("time_seconds", {}) + lines.append(f"| Time | {a_time.get('mean', 0):.1f}s ± {a_time.get('stddev', 0):.1f}s | {b_time.get('mean', 0):.1f}s ± {b_time.get('stddev', 0):.1f}s | {delta.get('time_seconds', '—')}s |") + + # Format tokens + a_tokens = a_summary.get("tokens", {}) + b_tokens = b_summary.get("tokens", {}) + lines.append(f"| Tokens | {a_tokens.get('mean', 0):.0f} ± {a_tokens.get('stddev', 0):.0f} | {b_tokens.get('mean', 0):.0f} ± {b_tokens.get('stddev', 0):.0f} | {delta.get('tokens', '—')} |") + + # Notes section + if benchmark.get("notes"): + lines.extend([ + "", + "## Notes", + "" + ]) + for note in benchmark["notes"]: + lines.append(f"- {note}") + + return "\n".join(lines) + + +def main(): + parser = argparse.ArgumentParser( + description="Aggregate benchmark run results into summary statistics" + ) + parser.add_argument( + "benchmark_dir", + type=Path, + help="Path to the benchmark directory" + ) + parser.add_argument( + "--skill-name", + default="", + help="Name of the skill being benchmarked" + ) + parser.add_argument( + "--skill-path", + default="", + help="Path to the skill being benchmarked" + ) + parser.add_argument( + "--output", "-o", + type=Path, + help="Output path for benchmark.json (default: /benchmark.json)" + ) + + args = parser.parse_args() + + if not args.benchmark_dir.exists(): + print(f"Directory not found: {args.benchmark_dir}") + sys.exit(1) + + # Generate benchmark + benchmark = generate_benchmark(args.benchmark_dir, args.skill_name, args.skill_path) + + # Determine output paths + output_json = args.output or (args.benchmark_dir / "benchmark.json") + output_md = output_json.with_suffix(".md") + + # Write benchmark.json + with open(output_json, "w", encoding="utf-8") as f: + json.dump(benchmark, f, indent=2) + print(f"Generated: {output_json}") + + # Write benchmark.md + markdown = generate_markdown(benchmark) + with open(output_md, "w", encoding="utf-8") as f: + f.write(markdown) + print(f"Generated: {output_md}") + + # Print summary + run_summary = benchmark["run_summary"] + configs = [k for k in run_summary if k != "delta"] + delta = run_summary.get("delta", {}) + + print(f"\nSummary:") + for config in configs: + pr = run_summary[config]["pass_rate"]["mean"] + label = config.replace("_", " ").title() + print(f" {label}: {pr*100:.1f}% pass rate") + print(f" Delta: {delta.get('pass_rate', '—')}") + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/generate_report.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/generate_report.py new file mode 100644 index 00000000..959e30a0 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/generate_report.py @@ -0,0 +1,326 @@ +#!/usr/bin/env python3 +"""Generate an HTML report from run_loop.py output. + +Takes the JSON output from run_loop.py and generates a visual HTML report +showing each description attempt with check/x for each test case. +Distinguishes between train and test queries. +""" + +import argparse +import html +import json +import sys +from pathlib import Path + + +def generate_html(data: dict, auto_refresh: bool = False, skill_name: str = "") -> str: + """Generate HTML report from loop output data. If auto_refresh is True, adds a meta refresh tag.""" + history = data.get("history", []) + holdout = data.get("holdout", 0) + title_prefix = html.escape(skill_name + " \u2014 ") if skill_name else "" + + # Get all unique queries from train and test sets, with should_trigger info + train_queries: list[dict] = [] + test_queries: list[dict] = [] + if history: + for r in history[0].get("train_results", history[0].get("results", [])): + train_queries.append({"query": r["query"], "should_trigger": r.get("should_trigger", True)}) + if history[0].get("test_results"): + for r in history[0].get("test_results", []): + test_queries.append({"query": r["query"], "should_trigger": r.get("should_trigger", True)}) + + refresh_tag = ' \n' if auto_refresh else "" + + html_parts = [""" + + + +""" + refresh_tag + """ """ + title_prefix + """Skill Description Optimization + + + + + + +

    """ + title_prefix + """Skill Description Optimization

    +
    + Optimizing your skill's description. This page updates automatically as Claude tests different versions of your skill's description. Each row is an iteration — a new description attempt. The columns show test queries: green checkmarks mean the skill triggered correctly (or correctly didn't trigger), red crosses mean it got it wrong. The "Train" score shows performance on queries used to improve the description; the "Test" score shows performance on held-out queries the optimizer hasn't seen. When it's done, Claude will apply the best-performing description to your skill. +
    +"""] + + # Summary section + best_test_score = data.get('best_test_score') + best_train_score = data.get('best_train_score') + html_parts.append(f""" +
    +

    Original: {html.escape(data.get('original_description', 'N/A'))}

    +

    Best: {html.escape(data.get('best_description', 'N/A'))}

    +

    Best Score: {data.get('best_score', 'N/A')} {'(test)' if best_test_score else '(train)'}

    +

    Iterations: {data.get('iterations_run', 0)} | Train: {data.get('train_size', '?')} | Test: {data.get('test_size', '?')}

    +
    +""") + + # Legend + html_parts.append(""" +
    + Query columns: + Should trigger + Should NOT trigger + Train + Test +
    +""") + + # Table header + html_parts.append(""" +
    + + + + + + + +""") + + # Add column headers for train queries + for qinfo in train_queries: + polarity = "positive-col" if qinfo["should_trigger"] else "negative-col" + html_parts.append(f' \n') + + # Add column headers for test queries (different color) + for qinfo in test_queries: + polarity = "positive-col" if qinfo["should_trigger"] else "negative-col" + html_parts.append(f' \n') + + html_parts.append(""" + + +""") + + # Find best iteration for highlighting + if test_queries: + best_iter = max(history, key=lambda h: h.get("test_passed") or 0).get("iteration") + else: + best_iter = max(history, key=lambda h: h.get("train_passed", h.get("passed", 0))).get("iteration") + + # Add rows for each iteration + for h in history: + iteration = h.get("iteration", "?") + train_passed = h.get("train_passed", h.get("passed", 0)) + train_total = h.get("train_total", h.get("total", 0)) + test_passed = h.get("test_passed") + test_total = h.get("test_total") + description = h.get("description", "") + train_results = h.get("train_results", h.get("results", [])) + test_results = h.get("test_results", []) + + # Create lookups for results by query + train_by_query = {r["query"]: r for r in train_results} + test_by_query = {r["query"]: r for r in test_results} if test_results else {} + + # Compute aggregate correct/total runs across all retries + def aggregate_runs(results: list[dict]) -> tuple[int, int]: + correct = 0 + total = 0 + for r in results: + runs = r.get("runs", 0) + triggers = r.get("triggers", 0) + total += runs + if r.get("should_trigger", True): + correct += triggers + else: + correct += runs - triggers + return correct, total + + train_correct, train_runs = aggregate_runs(train_results) + test_correct, test_runs = aggregate_runs(test_results) + + # Determine score classes + def score_class(correct: int, total: int) -> str: + if total > 0: + ratio = correct / total + if ratio >= 0.8: + return "score-good" + elif ratio >= 0.5: + return "score-ok" + return "score-bad" + + train_class = score_class(train_correct, train_runs) + test_class = score_class(test_correct, test_runs) + + row_class = "best-row" if iteration == best_iter else "" + + html_parts.append(f""" + + + + +""") + + # Add result for each train query + for qinfo in train_queries: + r = train_by_query.get(qinfo["query"], {}) + did_pass = r.get("pass", False) + triggers = r.get("triggers", 0) + runs = r.get("runs", 0) + + icon = "✓" if did_pass else "✗" + css_class = "pass" if did_pass else "fail" + + html_parts.append(f' \n') + + # Add result for each test query (with different background) + for qinfo in test_queries: + r = test_by_query.get(qinfo["query"], {}) + did_pass = r.get("pass", False) + triggers = r.get("triggers", 0) + runs = r.get("runs", 0) + + icon = "✓" if did_pass else "✗" + css_class = "pass" if did_pass else "fail" + + html_parts.append(f' \n') + + html_parts.append(" \n") + + html_parts.append(""" +
    IterTrainTestDescription{html.escape(qinfo["query"])}{html.escape(qinfo["query"])}
    {iteration}{train_correct}/{train_runs}{test_correct}/{test_runs}{html.escape(description)}{icon}{triggers}/{runs}{icon}{triggers}/{runs}
    +
    +""") + + html_parts.append(""" + + +""") + + return "".join(html_parts) + + +def main(): + parser = argparse.ArgumentParser(description="Generate HTML report from run_loop output") + parser.add_argument("input", help="Path to JSON output from run_loop.py (or - for stdin)") + parser.add_argument("-o", "--output", default=None, help="Output HTML file (default: stdout)") + parser.add_argument("--skill-name", default="", help="Skill name to include in the report title") + args = parser.parse_args() + + if args.input == "-": + data = json.load(sys.stdin) + else: + data = json.loads(Path(args.input).read_text()) + + html_output = generate_html(data, skill_name=args.skill_name) + + if args.output: + Path(args.output).write_text(html_output) + print(f"Report written to {args.output}", file=sys.stderr) + else: + print(html_output) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/improve_description.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/improve_description.py new file mode 100644 index 00000000..9a3ad7e7 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/improve_description.py @@ -0,0 +1,247 @@ +#!/usr/bin/env python3 +"""Improve a skill description based on eval results. + +Takes eval results (from run_eval.py) and generates an improved description +by calling `claude -p` as a subprocess (same auth pattern as run_eval.py — +uses the session's Claude Code auth, no separate ANTHROPIC_API_KEY needed). +""" + +import argparse +import json +import os +import re +import subprocess +import sys +from pathlib import Path + +from scripts.utils import parse_skill_md + + +def _call_claude(prompt: str, model: str | None, timeout: int = 300) -> str: + """Run `claude -p` with the prompt on stdin and return the text response. + + Prompt goes over stdin (not argv) because it embeds the full SKILL.md + body and can easily exceed comfortable argv length. + """ + cmd = ["claude", "-p", "--output-format", "text"] + if model: + cmd.extend(["--model", model]) + + # Remove CLAUDECODE env var to allow nesting claude -p inside a + # Claude Code session. The guard is for interactive terminal conflicts; + # programmatic subprocess usage is safe. Same pattern as run_eval.py. + env = {k: v for k, v in os.environ.items() if k != "CLAUDECODE"} + + result = subprocess.run( + cmd, + input=prompt, + capture_output=True, + text=True, + env=env, + timeout=timeout, + ) + if result.returncode != 0: + raise RuntimeError( + f"claude -p exited {result.returncode}\nstderr: {result.stderr}" + ) + return result.stdout + + +def improve_description( + skill_name: str, + skill_content: str, + current_description: str, + eval_results: dict, + history: list[dict], + model: str, + test_results: dict | None = None, + log_dir: Path | None = None, + iteration: int | None = None, +) -> str: + """Call Claude to improve the description based on eval results.""" + failed_triggers = [ + r for r in eval_results["results"] + if r["should_trigger"] and not r["pass"] + ] + false_triggers = [ + r for r in eval_results["results"] + if not r["should_trigger"] and not r["pass"] + ] + + # Build scores summary + train_score = f"{eval_results['summary']['passed']}/{eval_results['summary']['total']}" + if test_results: + test_score = f"{test_results['summary']['passed']}/{test_results['summary']['total']}" + scores_summary = f"Train: {train_score}, Test: {test_score}" + else: + scores_summary = f"Train: {train_score}" + + prompt = f"""You are optimizing a skill description for a Claude Code skill called "{skill_name}". A "skill" is sort of like a prompt, but with progressive disclosure -- there's a title and description that Claude sees when deciding whether to use the skill, and then if it does use the skill, it reads the .md file which has lots more details and potentially links to other resources in the skill folder like helper files and scripts and additional documentation or examples. + +The description appears in Claude's "available_skills" list. When a user sends a query, Claude decides whether to invoke the skill based solely on the title and on this description. Your goal is to write a description that triggers for relevant queries, and doesn't trigger for irrelevant ones. + +Here's the current description: + +"{current_description}" + + +Current scores ({scores_summary}): + +""" + if failed_triggers: + prompt += "FAILED TO TRIGGER (should have triggered but didn't):\n" + for r in failed_triggers: + prompt += f' - "{r["query"]}" (triggered {r["triggers"]}/{r["runs"]} times)\n' + prompt += "\n" + + if false_triggers: + prompt += "FALSE TRIGGERS (triggered but shouldn't have):\n" + for r in false_triggers: + prompt += f' - "{r["query"]}" (triggered {r["triggers"]}/{r["runs"]} times)\n' + prompt += "\n" + + if history: + prompt += "PREVIOUS ATTEMPTS (do NOT repeat these — try something structurally different):\n\n" + for h in history: + train_s = f"{h.get('train_passed', h.get('passed', 0))}/{h.get('train_total', h.get('total', 0))}" + test_s = f"{h.get('test_passed', '?')}/{h.get('test_total', '?')}" if h.get('test_passed') is not None else None + score_str = f"train={train_s}" + (f", test={test_s}" if test_s else "") + prompt += f'\n' + prompt += f'Description: "{h["description"]}"\n' + if "results" in h: + prompt += "Train results:\n" + for r in h["results"]: + status = "PASS" if r["pass"] else "FAIL" + prompt += f' [{status}] "{r["query"][:80]}" (triggered {r["triggers"]}/{r["runs"]})\n' + if h.get("note"): + prompt += f'Note: {h["note"]}\n' + prompt += "\n\n" + + prompt += f""" + +Skill content (for context on what the skill does): + +{skill_content} + + +Based on the failures, write a new and improved description that is more likely to trigger correctly. When I say "based on the failures", it's a bit of a tricky line to walk because we don't want to overfit to the specific cases you're seeing. So what I DON'T want you to do is produce an ever-expanding list of specific queries that this skill should or shouldn't trigger for. Instead, try to generalize from the failures to broader categories of user intent and situations where this skill would be useful or not useful. The reason for this is twofold: + +1. Avoid overfitting +2. The list might get loooong and it's injected into ALL queries and there might be a lot of skills, so we don't want to blow too much space on any given description. + +Concretely, your description should not be more than about 100-200 words, even if that comes at the cost of accuracy. There is a hard limit of 1024 characters — descriptions over that will be truncated, so stay comfortably under it. + +Here are some tips that we've found to work well in writing these descriptions: +- The skill should be phrased in the imperative -- "Use this skill for" rather than "this skill does" +- The skill description should focus on the user's intent, what they are trying to achieve, vs. the implementation details of how the skill works. +- The description competes with other skills for Claude's attention — make it distinctive and immediately recognizable. +- If you're getting lots of failures after repeated attempts, change things up. Try different sentence structures or wordings. + +I'd encourage you to be creative and mix up the style in different iterations since you'll have multiple opportunities to try different approaches and we'll just grab the highest-scoring one at the end. + +Please respond with only the new description text in tags, nothing else.""" + + text = _call_claude(prompt, model) + + match = re.search(r"(.*?)", text, re.DOTALL) + description = match.group(1).strip().strip('"') if match else text.strip().strip('"') + + transcript: dict = { + "iteration": iteration, + "prompt": prompt, + "response": text, + "parsed_description": description, + "char_count": len(description), + "over_limit": len(description) > 1024, + } + + # Safety net: the prompt already states the 1024-char hard limit, but if + # the model blew past it anyway, make one fresh single-turn call that + # quotes the too-long version and asks for a shorter rewrite. (The old + # SDK path did this as a true multi-turn; `claude -p` is one-shot, so we + # inline the prior output into the new prompt instead.) + if len(description) > 1024: + shorten_prompt = ( + f"{prompt}\n\n" + f"---\n\n" + f"A previous attempt produced this description, which at " + f"{len(description)} characters is over the 1024-character hard limit:\n\n" + f'"{description}"\n\n' + f"Rewrite it to be under 1024 characters while keeping the most " + f"important trigger words and intent coverage. Respond with only " + f"the new description in tags." + ) + shorten_text = _call_claude(shorten_prompt, model) + match = re.search(r"(.*?)", shorten_text, re.DOTALL) + shortened = match.group(1).strip().strip('"') if match else shorten_text.strip().strip('"') + + transcript["rewrite_prompt"] = shorten_prompt + transcript["rewrite_response"] = shorten_text + transcript["rewrite_description"] = shortened + transcript["rewrite_char_count"] = len(shortened) + description = shortened + + transcript["final_description"] = description + + if log_dir: + log_dir.mkdir(parents=True, exist_ok=True) + log_file = log_dir / f"improve_iter_{iteration or 'unknown'}.json" + log_file.write_text(json.dumps(transcript, indent=2)) + + return description + + +def main(): + parser = argparse.ArgumentParser(description="Improve a skill description based on eval results") + parser.add_argument("--eval-results", required=True, help="Path to eval results JSON (from run_eval.py)") + parser.add_argument("--skill-path", required=True, help="Path to skill directory") + parser.add_argument("--history", default=None, help="Path to history JSON (previous attempts)") + parser.add_argument("--model", required=True, help="Model for improvement") + parser.add_argument("--verbose", action="store_true", help="Print thinking to stderr") + args = parser.parse_args() + + skill_path = Path(args.skill_path) + if not (skill_path / "SKILL.md").exists(): + print(f"Error: No SKILL.md found at {skill_path}", file=sys.stderr) + sys.exit(1) + + eval_results = json.loads(Path(args.eval_results).read_text()) + history = [] + if args.history: + history = json.loads(Path(args.history).read_text()) + + name, _, content = parse_skill_md(skill_path) + current_description = eval_results["description"] + + if args.verbose: + print(f"Current: {current_description}", file=sys.stderr) + print(f"Score: {eval_results['summary']['passed']}/{eval_results['summary']['total']}", file=sys.stderr) + + new_description = improve_description( + skill_name=name, + skill_content=content, + current_description=current_description, + eval_results=eval_results, + history=history, + model=args.model, + ) + + if args.verbose: + print(f"Improved: {new_description}", file=sys.stderr) + + # Output as JSON with both the new description and updated history + output = { + "description": new_description, + "history": history + [{ + "description": current_description, + "passed": eval_results["summary"]["passed"], + "failed": eval_results["summary"]["failed"], + "total": eval_results["summary"]["total"], + "results": eval_results["results"], + }], + } + print(json.dumps(output, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/init_skill.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/init_skill.py new file mode 100644 index 00000000..329ad4e5 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/init_skill.py @@ -0,0 +1,303 @@ +#!/usr/bin/env python3 +""" +Skill Initializer - Creates a new skill from template + +Usage: + init_skill.py --path + +Examples: + init_skill.py my-new-skill --path skills/public + init_skill.py my-api-helper --path skills/private + init_skill.py custom-skill --path /custom/location +""" + +import sys +from pathlib import Path + + +SKILL_TEMPLATE = """--- +name: {skill_name} +description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.] +--- + +# {skill_title} + +## Overview + +[TODO: 1-2 sentences explaining what this skill enables] + +## Structuring This Skill + +[TODO: Choose the structure that best fits this skill's purpose. Common patterns: + +**1. Workflow-Based** (best for sequential processes) +- Works well when there are clear step-by-step procedures +- Example: DOCX skill with "Workflow Decision Tree" → "Reading" → "Creating" → "Editing" +- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2... + +**2. Task-Based** (best for tool collections) +- Works well when the skill offers different operations/capabilities +- Example: PDF skill with "Quick Start" → "Merge PDFs" → "Split PDFs" → "Extract Text" +- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2... + +**3. Reference/Guidelines** (best for standards or specifications) +- Works well for brand guidelines, coding standards, or requirements +- Example: Brand styling with "Brand Guidelines" → "Colors" → "Typography" → "Features" +- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage... + +**4. Capabilities-Based** (best for integrated systems) +- Works well when the skill provides multiple interrelated features +- Example: Product Management with "Core Capabilities" → numbered capability list +- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature... + +Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations). + +Delete this entire "Structuring This Skill" section when done - it's just guidance.] + +## [TODO: Replace with the first main section based on chosen structure] + +[TODO: Add content here. See examples in existing skills: +- Code samples for technical skills +- Decision trees for complex workflows +- Concrete examples with realistic user requests +- References to scripts/templates/references as needed] + +## Resources + +This skill includes example resource directories that demonstrate how to organize different types of bundled resources: + +### scripts/ +Executable code (Python/Bash/etc.) that can be run directly to perform specific operations. + +**Examples from other skills:** +- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation +- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing + +**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations. + +**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments. + +### references/ +Documentation and reference material intended to be loaded into context to inform Claude's process and thinking. + +**Examples from other skills:** +- Product management: `communication.md`, `context_building.md` - detailed workflow guides +- BigQuery: API reference documentation and query examples +- Finance: Schema documentation, company policies + +**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working. + +### assets/ +Files not intended to be loaded into context, but rather used within the output Claude produces. + +**Examples from other skills:** +- Brand styling: PowerPoint template files (.pptx), logo files +- Frontend builder: HTML/React boilerplate project directories +- Typography: Font files (.ttf, .woff2) + +**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output. + +--- + +**Any unneeded directories can be deleted.** Not every skill requires all three types of resources. +""" + +EXAMPLE_SCRIPT = '''#!/usr/bin/env python3 +""" +Example helper script for {skill_name} + +This is a placeholder script that can be executed directly. +Replace with actual implementation or delete if not needed. + +Example real scripts from other skills: +- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields +- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images +""" + +def main(): + print("This is an example script for {skill_name}") + # TODO: Add actual script logic here + # This could be data processing, file conversion, API calls, etc. + +if __name__ == "__main__": + main() +''' + +EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title} + +This is a placeholder for detailed reference documentation. +Replace with actual reference content or delete if not needed. + +Example real reference docs from other skills: +- product-management/references/communication.md - Comprehensive guide for status updates +- product-management/references/context_building.md - Deep-dive on gathering context +- bigquery/references/ - API references and query examples + +## When Reference Docs Are Useful + +Reference docs are ideal for: +- Comprehensive API documentation +- Detailed workflow guides +- Complex multi-step processes +- Information too lengthy for main SKILL.md +- Content that's only needed for specific use cases + +## Structure Suggestions + +### API Reference Example +- Overview +- Authentication +- Endpoints with examples +- Error codes +- Rate limits + +### Workflow Guide Example +- Prerequisites +- Step-by-step instructions +- Common patterns +- Troubleshooting +- Best practices +""" + +EXAMPLE_ASSET = """# Example Asset File + +This placeholder represents where asset files would be stored. +Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed. + +Asset files are NOT intended to be loaded into context, but rather used within +the output Claude produces. + +Example asset files from other skills: +- Brand guidelines: logo.png, slides_template.pptx +- Frontend builder: hello-world/ directory with HTML/React boilerplate +- Typography: custom-font.ttf, font-family.woff2 +- Data: sample_data.csv, test_dataset.json + +## Common Asset Types + +- Templates: .pptx, .docx, boilerplate directories +- Images: .png, .jpg, .svg, .gif +- Fonts: .ttf, .otf, .woff, .woff2 +- Boilerplate code: Project directories, starter files +- Icons: .ico, .svg +- Data files: .csv, .json, .xml, .yaml + +Note: This is a text placeholder. Actual assets can be any file type. +""" + + +def title_case_skill_name(skill_name): + """Convert hyphenated skill name to Title Case for display.""" + return ' '.join(word.capitalize() for word in skill_name.split('-')) + + +def init_skill(skill_name, path): + """ + Initialize a new skill directory with template SKILL.md. + + Args: + skill_name: Name of the skill + path: Path where the skill directory should be created + + Returns: + Path to created skill directory, or None if error + """ + # Determine skill directory path + skill_dir = Path(path).resolve() / skill_name + + # Check if directory already exists + if skill_dir.exists(): + print(f"❌ Error: Skill directory already exists: {skill_dir}") + return None + + # Create skill directory + try: + skill_dir.mkdir(parents=True, exist_ok=False) + print(f"✅ Created skill directory: {skill_dir}") + except Exception as e: + print(f"❌ Error creating directory: {e}") + return None + + # Create SKILL.md from template + skill_title = title_case_skill_name(skill_name) + skill_content = SKILL_TEMPLATE.format( + skill_name=skill_name, + skill_title=skill_title + ) + + skill_md_path = skill_dir / 'SKILL.md' + try: + skill_md_path.write_text(skill_content) + print("✅ Created SKILL.md") + except Exception as e: + print(f"❌ Error creating SKILL.md: {e}") + return None + + # Create resource directories with example files + try: + # Create scripts/ directory with example script + scripts_dir = skill_dir / 'scripts' + scripts_dir.mkdir(exist_ok=True) + example_script = scripts_dir / 'example.py' + example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name)) + example_script.chmod(0o755) + print("✅ Created scripts/example.py") + + # Create references/ directory with example reference doc + references_dir = skill_dir / 'references' + references_dir.mkdir(exist_ok=True) + example_reference = references_dir / 'api_reference.md' + example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title)) + print("✅ Created references/api_reference.md") + + # Create assets/ directory with example asset placeholder + assets_dir = skill_dir / 'assets' + assets_dir.mkdir(exist_ok=True) + example_asset = assets_dir / 'example_asset.txt' + example_asset.write_text(EXAMPLE_ASSET) + print("✅ Created assets/example_asset.txt") + except Exception as e: + print(f"❌ Error creating resource directories: {e}") + return None + + # Print next steps + print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}") + print("\nNext steps:") + print("1. Edit SKILL.md to complete the TODO items and update the description") + print("2. Customize or delete the example files in scripts/, references/, and assets/") + print("3. Run the validator when ready to check the skill structure") + + return skill_dir + + +def main(): + if len(sys.argv) < 4 or sys.argv[2] != '--path': + print("Usage: init_skill.py --path ") + print("\nSkill name requirements:") + print(" - Hyphen-case identifier (e.g., 'data-analyzer')") + print(" - Lowercase letters, digits, and hyphens only") + print(" - Max 40 characters") + print(" - Must match directory name exactly") + print("\nExamples:") + print(" init_skill.py my-new-skill --path skills/public") + print(" init_skill.py my-api-helper --path skills/private") + print(" init_skill.py custom-skill --path /custom/location") + sys.exit(1) + + skill_name = sys.argv[1] + path = sys.argv[3] + + print(f"🚀 Initializing skill: {skill_name}") + print(f" Location: {path}") + print() + + result = init_skill(skill_name, path) + + if result: + sys.exit(0) + else: + sys.exit(1) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/package_skill.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/package_skill.py new file mode 100644 index 00000000..f48eac44 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/package_skill.py @@ -0,0 +1,136 @@ +#!/usr/bin/env python3 +""" +Skill Packager - Creates a distributable .skill file of a skill folder + +Usage: + python utils/package_skill.py [output-directory] + +Example: + python utils/package_skill.py skills/public/my-skill + python utils/package_skill.py skills/public/my-skill ./dist +""" + +import fnmatch +import sys +import zipfile +from pathlib import Path +from scripts.quick_validate import validate_skill + +# Patterns to exclude when packaging skills. +EXCLUDE_DIRS = {"__pycache__", "node_modules"} +EXCLUDE_GLOBS = {"*.pyc"} +EXCLUDE_FILES = {".DS_Store"} +# Directories excluded only at the skill root (not when nested deeper). +ROOT_EXCLUDE_DIRS = {"evals"} + + +def should_exclude(rel_path: Path) -> bool: + """Check if a path should be excluded from packaging.""" + parts = rel_path.parts + if any(part in EXCLUDE_DIRS for part in parts): + return True + # rel_path is relative to skill_path.parent, so parts[0] is the skill + # folder name and parts[1] (if present) is the first subdir. + if len(parts) > 1 and parts[1] in ROOT_EXCLUDE_DIRS: + return True + name = rel_path.name + if name in EXCLUDE_FILES: + return True + return any(fnmatch.fnmatch(name, pat) for pat in EXCLUDE_GLOBS) + + +def package_skill(skill_path, output_dir=None): + """ + Package a skill folder into a .skill file. + + Args: + skill_path: Path to the skill folder + output_dir: Optional output directory for the .skill file (defaults to current directory) + + Returns: + Path to the created .skill file, or None if error + """ + skill_path = Path(skill_path).resolve() + + # Validate skill folder exists + if not skill_path.exists(): + print(f"❌ Error: Skill folder not found: {skill_path}") + return None + + if not skill_path.is_dir(): + print(f"❌ Error: Path is not a directory: {skill_path}") + return None + + # Validate SKILL.md exists + skill_md = skill_path / "SKILL.md" + if not skill_md.exists(): + print(f"❌ Error: SKILL.md not found in {skill_path}") + return None + + # Run validation before packaging + print("🔍 Validating skill...") + valid, message = validate_skill(skill_path) + if not valid: + print(f"❌ Validation failed: {message}") + print(" Please fix the validation errors before packaging.") + return None + print(f"✅ {message}\n") + + # Determine output location + skill_name = skill_path.name + if output_dir: + output_path = Path(output_dir).resolve() + output_path.mkdir(parents=True, exist_ok=True) + else: + output_path = Path.cwd() + + skill_filename = output_path / f"{skill_name}.skill" + + # Create the .skill file (zip format) + try: + with zipfile.ZipFile(skill_filename, 'w', zipfile.ZIP_DEFLATED) as zipf: + # Walk through the skill directory, excluding build artifacts + for file_path in skill_path.rglob('*'): + if not file_path.is_file(): + continue + arcname = file_path.relative_to(skill_path.parent) + if should_exclude(arcname): + print(f" Skipped: {arcname}") + continue + zipf.write(file_path, arcname) + print(f" Added: {arcname}") + + print(f"\n✅ Successfully packaged skill to: {skill_filename}") + return skill_filename + + except Exception as e: + print(f"❌ Error creating .skill file: {e}") + return None + + +def main(): + if len(sys.argv) < 2: + print("Usage: python utils/package_skill.py [output-directory]") + print("\nExample:") + print(" python utils/package_skill.py skills/public/my-skill") + print(" python utils/package_skill.py skills/public/my-skill ./dist") + sys.exit(1) + + skill_path = sys.argv[1] + output_dir = sys.argv[2] if len(sys.argv) > 2 else None + + print(f"📦 Packaging skill: {skill_path}") + if output_dir: + print(f" Output directory: {output_dir}") + print() + + result = package_skill(skill_path, output_dir) + + if result: + sys.exit(0) + else: + sys.exit(1) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/quick_validate.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/quick_validate.py new file mode 100644 index 00000000..54f682ce --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/quick_validate.py @@ -0,0 +1,103 @@ +#!/usr/bin/env python3 +""" +Quick validation script for skills - minimal version +""" + +import sys +import os +import re +import yaml +from pathlib import Path + +def validate_skill(skill_path): + """Basic validation of a skill""" + skill_path = Path(skill_path) + + # Check SKILL.md exists + skill_md = skill_path / 'SKILL.md' + if not skill_md.exists(): + return False, "SKILL.md not found" + + # Read and validate frontmatter + content = skill_md.read_text() + if not content.startswith('---'): + return False, "No YAML frontmatter found" + + # Extract frontmatter + match = re.match(r'^---\n(.*?)\n---', content, re.DOTALL) + if not match: + return False, "Invalid frontmatter format" + + frontmatter_text = match.group(1) + + # Parse YAML frontmatter + try: + frontmatter = yaml.safe_load(frontmatter_text) + if not isinstance(frontmatter, dict): + return False, "Frontmatter must be a YAML dictionary" + except yaml.YAMLError as e: + return False, f"Invalid YAML in frontmatter: {e}" + + # Define allowed properties + ALLOWED_PROPERTIES = {'name', 'description', 'license', 'allowed-tools', 'metadata', 'compatibility'} + + # Check for unexpected properties (excluding nested keys under metadata) + unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES + if unexpected_keys: + return False, ( + f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. " + f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}" + ) + + # Check required fields + if 'name' not in frontmatter: + return False, "Missing 'name' in frontmatter" + if 'description' not in frontmatter: + return False, "Missing 'description' in frontmatter" + + # Extract name for validation + name = frontmatter.get('name', '') + if not isinstance(name, str): + return False, f"Name must be a string, got {type(name).__name__}" + name = name.strip() + if name: + # Check naming convention (kebab-case: lowercase with hyphens) + if not re.match(r'^[a-z0-9-]+$', name): + return False, f"Name '{name}' should be kebab-case (lowercase letters, digits, and hyphens only)" + if name.startswith('-') or name.endswith('-') or '--' in name: + return False, f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens" + # Check name length (max 64 characters per spec) + if len(name) > 64: + return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters." + + # Extract and validate description + description = frontmatter.get('description', '') + if not isinstance(description, str): + return False, f"Description must be a string, got {type(description).__name__}" + description = description.strip() + if description: + # Check for angle brackets + if '<' in description or '>' in description: + return False, "Description cannot contain angle brackets (< or >)" + # Check description length (max 1024 characters per spec) + if len(description) > 1024: + return False, f"Description is too long ({len(description)} characters). Maximum is 1024 characters." + + # Validate compatibility field if present (optional) + compatibility = frontmatter.get('compatibility', '') + if compatibility: + if not isinstance(compatibility, str): + return False, f"Compatibility must be a string, got {type(compatibility).__name__}" + if len(compatibility) > 500: + return False, f"Compatibility is too long ({len(compatibility)} characters). Maximum is 500 characters." + + return True, "Skill is valid!" + +if __name__ == "__main__": + if len(sys.argv) != 2: + print("Usage: python quick_validate.py ") + sys.exit(1) + + valid, message = validate_skill(sys.argv[1]) + print(message) + sys.exit(0 if valid else 1) diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/run_eval.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/run_eval.py new file mode 100644 index 00000000..e58c70be --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/run_eval.py @@ -0,0 +1,310 @@ +#!/usr/bin/env python3 +"""Run trigger evaluation for a skill description. + +Tests whether a skill's description causes Claude to trigger (read the skill) +for a set of queries. Outputs results as JSON. +""" + +import argparse +import json +import os +import select +import subprocess +import sys +import time +import uuid +from concurrent.futures import ProcessPoolExecutor, as_completed +from pathlib import Path + +from scripts.utils import parse_skill_md + + +def find_project_root() -> Path: + """Find the project root by walking up from cwd looking for .claude/. + + Mimics how Claude Code discovers its project root, so the command file + we create ends up where claude -p will look for it. + """ + current = Path.cwd() + for parent in [current, *current.parents]: + if (parent / ".claude").is_dir(): + return parent + return current + + +def run_single_query( + query: str, + skill_name: str, + skill_description: str, + timeout: int, + project_root: str, + model: str | None = None, +) -> bool: + """Run a single query and return whether the skill was triggered. + + Creates a command file in .claude/commands/ so it appears in Claude's + available_skills list, then runs `claude -p` with the raw query. + Uses --include-partial-messages to detect triggering early from + stream events (content_block_start) rather than waiting for the + full assistant message, which only arrives after tool execution. + """ + unique_id = uuid.uuid4().hex[:8] + clean_name = f"{skill_name}-skill-{unique_id}" + project_commands_dir = Path(project_root) / ".claude" / "commands" + command_file = project_commands_dir / f"{clean_name}.md" + + try: + project_commands_dir.mkdir(parents=True, exist_ok=True) + # Use YAML block scalar to avoid breaking on quotes in description + indented_desc = "\n ".join(skill_description.split("\n")) + command_content = ( + f"---\n" + f"description: |\n" + f" {indented_desc}\n" + f"---\n\n" + f"# {skill_name}\n\n" + f"This skill handles: {skill_description}\n" + ) + command_file.write_text(command_content) + + cmd = [ + "claude", + "-p", query, + "--output-format", "stream-json", + "--verbose", + "--include-partial-messages", + ] + if model: + cmd.extend(["--model", model]) + + # Remove CLAUDECODE env var to allow nesting claude -p inside a + # Claude Code session. The guard is for interactive terminal conflicts; + # programmatic subprocess usage is safe. + env = {k: v for k, v in os.environ.items() if k != "CLAUDECODE"} + + process = subprocess.Popen( + cmd, + stdout=subprocess.PIPE, + stderr=subprocess.DEVNULL, + cwd=project_root, + env=env, + ) + + triggered = False + start_time = time.time() + buffer = "" + # Track state for stream event detection + pending_tool_name = None + accumulated_json = "" + + try: + while time.time() - start_time < timeout: + if process.poll() is not None: + remaining = process.stdout.read() + if remaining: + buffer += remaining.decode("utf-8", errors="replace") + break + + ready, _, _ = select.select([process.stdout], [], [], 1.0) + if not ready: + continue + + chunk = os.read(process.stdout.fileno(), 8192) + if not chunk: + break + buffer += chunk.decode("utf-8", errors="replace") + + while "\n" in buffer: + line, buffer = buffer.split("\n", 1) + line = line.strip() + if not line: + continue + + try: + event = json.loads(line) + except json.JSONDecodeError: + continue + + # Early detection via stream events + if event.get("type") == "stream_event": + se = event.get("event", {}) + se_type = se.get("type", "") + + if se_type == "content_block_start": + cb = se.get("content_block", {}) + if cb.get("type") == "tool_use": + tool_name = cb.get("name", "") + if tool_name in ("Skill", "Read"): + pending_tool_name = tool_name + accumulated_json = "" + else: + return False + + elif se_type == "content_block_delta" and pending_tool_name: + delta = se.get("delta", {}) + if delta.get("type") == "input_json_delta": + accumulated_json += delta.get("partial_json", "") + if clean_name in accumulated_json: + return True + + elif se_type in ("content_block_stop", "message_stop"): + if pending_tool_name: + return clean_name in accumulated_json + if se_type == "message_stop": + return False + + # Fallback: full assistant message + elif event.get("type") == "assistant": + message = event.get("message", {}) + for content_item in message.get("content", []): + if content_item.get("type") != "tool_use": + continue + tool_name = content_item.get("name", "") + tool_input = content_item.get("input", {}) + if tool_name == "Skill" and clean_name in tool_input.get("skill", ""): + triggered = True + elif tool_name == "Read" and clean_name in tool_input.get("file_path", ""): + triggered = True + return triggered + + elif event.get("type") == "result": + return triggered + finally: + # Clean up process on any exit path (return, exception, timeout) + if process.poll() is None: + process.kill() + process.wait() + + return triggered + finally: + if command_file.exists(): + command_file.unlink() + + +def run_eval( + eval_set: list[dict], + skill_name: str, + description: str, + num_workers: int, + timeout: int, + project_root: Path, + runs_per_query: int = 1, + trigger_threshold: float = 0.5, + model: str | None = None, +) -> dict: + """Run the full eval set and return results.""" + results = [] + + with ProcessPoolExecutor(max_workers=num_workers) as executor: + future_to_info = {} + for item in eval_set: + for run_idx in range(runs_per_query): + future = executor.submit( + run_single_query, + item["query"], + skill_name, + description, + timeout, + str(project_root), + model, + ) + future_to_info[future] = (item, run_idx) + + query_triggers: dict[str, list[bool]] = {} + query_items: dict[str, dict] = {} + for future in as_completed(future_to_info): + item, _ = future_to_info[future] + query = item["query"] + query_items[query] = item + if query not in query_triggers: + query_triggers[query] = [] + try: + query_triggers[query].append(future.result()) + except Exception as e: + print(f"Warning: query failed: {e}", file=sys.stderr) + query_triggers[query].append(False) + + for query, triggers in query_triggers.items(): + item = query_items[query] + trigger_rate = sum(triggers) / len(triggers) + should_trigger = item["should_trigger"] + if should_trigger: + did_pass = trigger_rate >= trigger_threshold + else: + did_pass = trigger_rate < trigger_threshold + results.append({ + "query": query, + "should_trigger": should_trigger, + "trigger_rate": trigger_rate, + "triggers": sum(triggers), + "runs": len(triggers), + "pass": did_pass, + }) + + passed = sum(1 for r in results if r["pass"]) + total = len(results) + + return { + "skill_name": skill_name, + "description": description, + "results": results, + "summary": { + "total": total, + "passed": passed, + "failed": total - passed, + }, + } + + +def main(): + parser = argparse.ArgumentParser(description="Run trigger evaluation for a skill description") + parser.add_argument("--eval-set", required=True, help="Path to eval set JSON file") + parser.add_argument("--skill-path", required=True, help="Path to skill directory") + parser.add_argument("--description", default=None, help="Override description to test") + parser.add_argument("--num-workers", type=int, default=10, help="Number of parallel workers") + parser.add_argument("--timeout", type=int, default=30, help="Timeout per query in seconds") + parser.add_argument("--runs-per-query", type=int, default=3, help="Number of runs per query") + parser.add_argument("--trigger-threshold", type=float, default=0.5, help="Trigger rate threshold") + parser.add_argument("--model", default=None, help="Model to use for claude -p (default: user's configured model)") + parser.add_argument("--verbose", action="store_true", help="Print progress to stderr") + args = parser.parse_args() + + eval_set = json.loads(Path(args.eval_set).read_text()) + skill_path = Path(args.skill_path) + + if not (skill_path / "SKILL.md").exists(): + print(f"Error: No SKILL.md found at {skill_path}", file=sys.stderr) + sys.exit(1) + + name, original_description, content = parse_skill_md(skill_path) + description = args.description or original_description + project_root = find_project_root() + + if args.verbose: + print(f"Evaluating: {description}", file=sys.stderr) + + output = run_eval( + eval_set=eval_set, + skill_name=name, + description=description, + num_workers=args.num_workers, + timeout=args.timeout, + project_root=project_root, + runs_per_query=args.runs_per_query, + trigger_threshold=args.trigger_threshold, + model=args.model, + ) + + if args.verbose: + summary = output["summary"] + print(f"Results: {summary['passed']}/{summary['total']} passed", file=sys.stderr) + for r in output["results"]: + status = "PASS" if r["pass"] else "FAIL" + rate_str = f"{r['triggers']}/{r['runs']}" + print(f" [{status}] rate={rate_str} expected={r['should_trigger']}: {r['query'][:70]}", file=sys.stderr) + + print(json.dumps(output, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/run_loop.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/run_loop.py new file mode 100644 index 00000000..30a263d6 --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/run_loop.py @@ -0,0 +1,328 @@ +#!/usr/bin/env python3 +"""Run the eval + improve loop until all pass or max iterations reached. + +Combines run_eval.py and improve_description.py in a loop, tracking history +and returning the best description found. Supports train/test split to prevent +overfitting. +""" + +import argparse +import json +import random +import sys +import tempfile +import time +import webbrowser +from pathlib import Path + +from scripts.generate_report import generate_html +from scripts.improve_description import improve_description +from scripts.run_eval import find_project_root, run_eval +from scripts.utils import parse_skill_md + + +def split_eval_set(eval_set: list[dict], holdout: float, seed: int = 42) -> tuple[list[dict], list[dict]]: + """Split eval set into train and test sets, stratified by should_trigger.""" + random.seed(seed) + + # Separate by should_trigger + trigger = [e for e in eval_set if e["should_trigger"]] + no_trigger = [e for e in eval_set if not e["should_trigger"]] + + # Shuffle each group + random.shuffle(trigger) + random.shuffle(no_trigger) + + # Calculate split points + n_trigger_test = max(1, int(len(trigger) * holdout)) + n_no_trigger_test = max(1, int(len(no_trigger) * holdout)) + + # Split + test_set = trigger[:n_trigger_test] + no_trigger[:n_no_trigger_test] + train_set = trigger[n_trigger_test:] + no_trigger[n_no_trigger_test:] + + return train_set, test_set + + +def run_loop( + eval_set: list[dict], + skill_path: Path, + description_override: str | None, + num_workers: int, + timeout: int, + max_iterations: int, + runs_per_query: int, + trigger_threshold: float, + holdout: float, + model: str, + verbose: bool, + live_report_path: Path | None = None, + log_dir: Path | None = None, +) -> dict: + """Run the eval + improvement loop.""" + project_root = find_project_root() + name, original_description, content = parse_skill_md(skill_path) + current_description = description_override or original_description + + # Split into train/test if holdout > 0 + if holdout > 0: + train_set, test_set = split_eval_set(eval_set, holdout) + if verbose: + print(f"Split: {len(train_set)} train, {len(test_set)} test (holdout={holdout})", file=sys.stderr) + else: + train_set = eval_set + test_set = [] + + history = [] + exit_reason = "unknown" + + for iteration in range(1, max_iterations + 1): + if verbose: + print(f"\n{'='*60}", file=sys.stderr) + print(f"Iteration {iteration}/{max_iterations}", file=sys.stderr) + print(f"Description: {current_description}", file=sys.stderr) + print(f"{'='*60}", file=sys.stderr) + + # Evaluate train + test together in one batch for parallelism + all_queries = train_set + test_set + t0 = time.time() + all_results = run_eval( + eval_set=all_queries, + skill_name=name, + description=current_description, + num_workers=num_workers, + timeout=timeout, + project_root=project_root, + runs_per_query=runs_per_query, + trigger_threshold=trigger_threshold, + model=model, + ) + eval_elapsed = time.time() - t0 + + # Split results back into train/test by matching queries + train_queries_set = {q["query"] for q in train_set} + train_result_list = [r for r in all_results["results"] if r["query"] in train_queries_set] + test_result_list = [r for r in all_results["results"] if r["query"] not in train_queries_set] + + train_passed = sum(1 for r in train_result_list if r["pass"]) + train_total = len(train_result_list) + train_summary = {"passed": train_passed, "failed": train_total - train_passed, "total": train_total} + train_results = {"results": train_result_list, "summary": train_summary} + + if test_set: + test_passed = sum(1 for r in test_result_list if r["pass"]) + test_total = len(test_result_list) + test_summary = {"passed": test_passed, "failed": test_total - test_passed, "total": test_total} + test_results = {"results": test_result_list, "summary": test_summary} + else: + test_results = None + test_summary = None + + history.append({ + "iteration": iteration, + "description": current_description, + "train_passed": train_summary["passed"], + "train_failed": train_summary["failed"], + "train_total": train_summary["total"], + "train_results": train_results["results"], + "test_passed": test_summary["passed"] if test_summary else None, + "test_failed": test_summary["failed"] if test_summary else None, + "test_total": test_summary["total"] if test_summary else None, + "test_results": test_results["results"] if test_results else None, + # For backward compat with report generator + "passed": train_summary["passed"], + "failed": train_summary["failed"], + "total": train_summary["total"], + "results": train_results["results"], + }) + + # Write live report if path provided + if live_report_path: + partial_output = { + "original_description": original_description, + "best_description": current_description, + "best_score": "in progress", + "iterations_run": len(history), + "holdout": holdout, + "train_size": len(train_set), + "test_size": len(test_set), + "history": history, + } + live_report_path.write_text(generate_html(partial_output, auto_refresh=True, skill_name=name)) + + if verbose: + def print_eval_stats(label, results, elapsed): + pos = [r for r in results if r["should_trigger"]] + neg = [r for r in results if not r["should_trigger"]] + tp = sum(r["triggers"] for r in pos) + pos_runs = sum(r["runs"] for r in pos) + fn = pos_runs - tp + fp = sum(r["triggers"] for r in neg) + neg_runs = sum(r["runs"] for r in neg) + tn = neg_runs - fp + total = tp + tn + fp + fn + precision = tp / (tp + fp) if (tp + fp) > 0 else 1.0 + recall = tp / (tp + fn) if (tp + fn) > 0 else 1.0 + accuracy = (tp + tn) / total if total > 0 else 0.0 + print(f"{label}: {tp+tn}/{total} correct, precision={precision:.0%} recall={recall:.0%} accuracy={accuracy:.0%} ({elapsed:.1f}s)", file=sys.stderr) + for r in results: + status = "PASS" if r["pass"] else "FAIL" + rate_str = f"{r['triggers']}/{r['runs']}" + print(f" [{status}] rate={rate_str} expected={r['should_trigger']}: {r['query'][:60]}", file=sys.stderr) + + print_eval_stats("Train", train_results["results"], eval_elapsed) + if test_summary: + print_eval_stats("Test ", test_results["results"], 0) + + if train_summary["failed"] == 0: + exit_reason = f"all_passed (iteration {iteration})" + if verbose: + print(f"\nAll train queries passed on iteration {iteration}!", file=sys.stderr) + break + + if iteration == max_iterations: + exit_reason = f"max_iterations ({max_iterations})" + if verbose: + print(f"\nMax iterations reached ({max_iterations}).", file=sys.stderr) + break + + # Improve the description based on train results + if verbose: + print(f"\nImproving description...", file=sys.stderr) + + t0 = time.time() + # Strip test scores from history so improvement model can't see them + blinded_history = [ + {k: v for k, v in h.items() if not k.startswith("test_")} + for h in history + ] + new_description = improve_description( + skill_name=name, + skill_content=content, + current_description=current_description, + eval_results=train_results, + history=blinded_history, + model=model, + log_dir=log_dir, + iteration=iteration, + ) + improve_elapsed = time.time() - t0 + + if verbose: + print(f"Proposed ({improve_elapsed:.1f}s): {new_description}", file=sys.stderr) + + current_description = new_description + + # Find the best iteration by TEST score (or train if no test set) + if test_set: + best = max(history, key=lambda h: h["test_passed"] or 0) + best_score = f"{best['test_passed']}/{best['test_total']}" + else: + best = max(history, key=lambda h: h["train_passed"]) + best_score = f"{best['train_passed']}/{best['train_total']}" + + if verbose: + print(f"\nExit reason: {exit_reason}", file=sys.stderr) + print(f"Best score: {best_score} (iteration {best['iteration']})", file=sys.stderr) + + return { + "exit_reason": exit_reason, + "original_description": original_description, + "best_description": best["description"], + "best_score": best_score, + "best_train_score": f"{best['train_passed']}/{best['train_total']}", + "best_test_score": f"{best['test_passed']}/{best['test_total']}" if test_set else None, + "final_description": current_description, + "iterations_run": len(history), + "holdout": holdout, + "train_size": len(train_set), + "test_size": len(test_set), + "history": history, + } + + +def main(): + parser = argparse.ArgumentParser(description="Run eval + improve loop") + parser.add_argument("--eval-set", required=True, help="Path to eval set JSON file") + parser.add_argument("--skill-path", required=True, help="Path to skill directory") + parser.add_argument("--description", default=None, help="Override starting description") + parser.add_argument("--num-workers", type=int, default=10, help="Number of parallel workers") + parser.add_argument("--timeout", type=int, default=30, help="Timeout per query in seconds") + parser.add_argument("--max-iterations", type=int, default=5, help="Max improvement iterations") + parser.add_argument("--runs-per-query", type=int, default=3, help="Number of runs per query") + parser.add_argument("--trigger-threshold", type=float, default=0.5, help="Trigger rate threshold") + parser.add_argument("--holdout", type=float, default=0.4, help="Fraction of eval set to hold out for testing (0 to disable)") + parser.add_argument("--model", required=True, help="Model for improvement") + parser.add_argument("--verbose", action="store_true", help="Print progress to stderr") + parser.add_argument("--report", default="auto", help="Generate HTML report at this path (default: 'auto' for temp file, 'none' to disable)") + parser.add_argument("--results-dir", default=None, help="Save all outputs (results.json, report.html, log.txt) to a timestamped subdirectory here") + args = parser.parse_args() + + eval_set = json.loads(Path(args.eval_set).read_text()) + skill_path = Path(args.skill_path) + + if not (skill_path / "SKILL.md").exists(): + print(f"Error: No SKILL.md found at {skill_path}", file=sys.stderr) + sys.exit(1) + + name, _, _ = parse_skill_md(skill_path) + + # Set up live report path + if args.report != "none": + if args.report == "auto": + timestamp = time.strftime("%Y%m%d_%H%M%S") + live_report_path = Path(tempfile.gettempdir()) / f"skill_description_report_{skill_path.name}_{timestamp}.html" + else: + live_report_path = Path(args.report) + # Open the report immediately so the user can watch + live_report_path.write_text("

    Starting optimization loop...

    ") + webbrowser.open(str(live_report_path)) + else: + live_report_path = None + + # Determine output directory (create before run_loop so logs can be written) + if args.results_dir: + timestamp = time.strftime("%Y-%m-%d_%H%M%S") + results_dir = Path(args.results_dir) / timestamp + results_dir.mkdir(parents=True, exist_ok=True) + else: + results_dir = None + + log_dir = results_dir / "logs" if results_dir else None + + output = run_loop( + eval_set=eval_set, + skill_path=skill_path, + description_override=args.description, + num_workers=args.num_workers, + timeout=args.timeout, + max_iterations=args.max_iterations, + runs_per_query=args.runs_per_query, + trigger_threshold=args.trigger_threshold, + holdout=args.holdout, + model=args.model, + verbose=args.verbose, + live_report_path=live_report_path, + log_dir=log_dir, + ) + + # Save JSON output + json_output = json.dumps(output, indent=2) + print(json_output) + if results_dir: + (results_dir / "results.json").write_text(json_output) + + # Write final HTML report (without auto-refresh) + if live_report_path: + live_report_path.write_text(generate_html(output, auto_refresh=False, skill_name=name)) + print(f"\nReport: {live_report_path}", file=sys.stderr) + + if results_dir and live_report_path: + (results_dir / "report.html").write_text(generate_html(output, auto_refresh=False, skill_name=name)) + + if results_dir: + print(f"Results saved to: {results_dir}", file=sys.stderr) + + +if __name__ == "__main__": + main() diff --git a/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/utils.py b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/utils.py new file mode 100644 index 00000000..51b6a07d --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/skill-creator/scripts/utils.py @@ -0,0 +1,47 @@ +"""Shared utilities for skill-creator scripts.""" + +from pathlib import Path + + + +def parse_skill_md(skill_path: Path) -> tuple[str, str, str]: + """Parse a SKILL.md file, returning (name, description, full_content).""" + content = (skill_path / "SKILL.md").read_text() + lines = content.split("\n") + + if lines[0].strip() != "---": + raise ValueError("SKILL.md missing frontmatter (no opening ---)") + + end_idx = None + for i, line in enumerate(lines[1:], start=1): + if line.strip() == "---": + end_idx = i + break + + if end_idx is None: + raise ValueError("SKILL.md missing frontmatter (no closing ---)") + + name = "" + description = "" + frontmatter_lines = lines[1:end_idx] + i = 0 + while i < len(frontmatter_lines): + line = frontmatter_lines[i] + if line.startswith("name:"): + name = line[len("name:"):].strip().strip('"').strip("'") + elif line.startswith("description:"): + value = line[len("description:"):].strip() + # Handle YAML multiline indicators (>, |, >-, |-) + if value in (">", "|", ">-", "|-"): + continuation_lines: list[str] = [] + i += 1 + while i < len(frontmatter_lines) and (frontmatter_lines[i].startswith(" ") or frontmatter_lines[i].startswith("\t")): + continuation_lines.append(frontmatter_lines[i].strip()) + i += 1 + description = " ".join(continuation_lines) + continue + else: + description = value.strip('"').strip("'") + i += 1 + + return name, description, content diff --git a/libs/hexagent_demo/backend/skills/public/web-design-guidelines/SKILL.md b/libs/hexagent_demo/backend/skills/public/web-design-guidelines/SKILL.md new file mode 100644 index 00000000..ceae92ab --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/web-design-guidelines/SKILL.md @@ -0,0 +1,39 @@ +--- +name: web-design-guidelines +description: Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices". +metadata: + author: vercel + version: "1.0.0" + argument-hint: +--- + +# Web Interface Guidelines + +Review files for compliance with Web Interface Guidelines. + +## How It Works + +1. Fetch the latest guidelines from the source URL below +2. Read the specified files (or prompt user for files/pattern) +3. Check against all rules in the fetched guidelines +4. Output findings in the terse `file:line` format + +## Guidelines Source + +Fetch fresh guidelines before each review: + +``` +https://raw.githubusercontent.com/vercel-labs/web-interface-guidelines/main/command.md +``` + +Use WebFetch to retrieve the latest rules. The fetched content contains all the rules and output format instructions. + +## Usage + +When a user provides a file or pattern argument: +1. Fetch guidelines from the source URL above +2. Read the specified files +3. Apply all rules from the fetched guidelines +4. Output findings using the format specified in the guidelines + +If no files specified, ask the user which files to review. 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zYbg)B2HX7;f6x|WCJowzB*9P$sEKg~{j9vs_oa&9U++il=^p=xKWzUg^fdu8p2-5R zxd*f9e{%VG9|G6oM`zH!1KJtReRID0)PZ|4%y%fl9O%gK|J7Xiz4gDpzyE{%cLNwG zNk89zzu0EJ>_xB;wjY%T8hzc1zwW;cdB18qY|{K5f6$lD;#U*v=Y-AqNuc#@;7{)# zu-#uVfc*gTX@l*>Fd8UM1YkZTzjcA{IP2fq|H1Za{#Lm!=?jBxKuz?E^D&3{*1`1H zFuQSQW+1RS(fcLaZ-yWb-QVI5>ay9uf`2IVog5tiV+{qMzZvKU8e<2{_EdxN$Kh}C z{N}+K*vA~d#UGS)VfwVHZ}R_c6t?F7$iME}3PAa%4)mA(UHuuDp9Q49@6h@!!|&rT zL)y*XYWuh8U_Mq5E6nNP~KsD(pNpn|Gd^3nwgnN0)ERu`6J5D z&xd_;^usj+e#b)#ez#Bt?$v9c9b+3tr)R+S2}ob=Vb8!k!GmY( z5^z0!cWulJ1KSJZ-=)EBz`SL!GG8hHzfr;m_oc560Wg1q&Yb9T9|)M-^GkmLFz+ge z4d=4l>zJ78SJl`mQ zb;JUFg(;v63HpqH=h&`H|KH(%wgKzE;hH?4(AxmWeW?uOf_+%vt^vwipub6y6ENFd zeU9mu?f=pEb%Emt^T&btA`Dl3@9zPY|8D%iO5wn?{I3oEIkG-A^jrQG1+X$-#t#;P z_Y@%Ifdn(UufYg5cTY}%?JxH~Kl=!Vl;4*9HV!_+1&IJ8!e0<9?N5Kx^KG5~lkxu# D9M5(5 From 58de9273e037606c2a9f3aa07c6edfd28c5747f5 Mon Sep 17 00:00:00 2001 From: "Anqi (Anthony) Tang" Date: Sat, 28 Mar 2026 01:22:05 +0800 Subject: [PATCH 8/9] fix(streaming): decouple agent execution from HTTP lifecycle for reconnectable streams Agent responses now run as background asyncio tasks that write SSE events into a per-conversation buffer. This fixes the crash when users refresh during streaming (RuntimeError: aclose() on running generator) and enables reconnecting to in-flight streams after page refresh. Key changes: - Add StreamManager with ConversationStream (event buffer + fan-out) - Extract _generate_events() from event_stream(), run via background task - Add GET /api/chat/{id}/stream endpoint for reconnecting subscribers - Frontend auto-reconnects to active streams on page load via subscribeToStream() - Include server-side timestamps in SSE events for accurate thinking durations on replay - Make STREAM_START idempotent to handle duplicate events during replay --- .../backend/hexagent_api/main.py | 4 +- .../backend/hexagent_api/routes/chat.py | 377 +++++++++++++++--- .../hexagent_api/routes/conversations.py | 25 +- .../backend/hexagent_api/stream_manager.py | 179 +++++++++ libs/hexagent_demo/frontend/src/App.tsx | 145 ++++--- libs/hexagent_demo/frontend/src/api.ts | 39 +- libs/hexagent_demo/frontend/src/store.ts | 48 ++- libs/hexagent_demo/frontend/src/types.ts | 6 +- 8 files changed, 672 insertions(+), 151 deletions(-) create mode 100644 libs/hexagent_demo/backend/hexagent_api/stream_manager.py diff --git a/libs/hexagent_demo/backend/hexagent_api/main.py b/libs/hexagent_demo/backend/hexagent_api/main.py index 9f744b1f..12f0c0c5 100644 --- a/libs/hexagent_demo/backend/hexagent_api/main.py +++ b/libs/hexagent_demo/backend/hexagent_api/main.py @@ -18,7 +18,6 @@ from hexagent_api.agent_manager import agent_manager from hexagent_api.paths import data_dir from hexagent_api.routes import chat, config, conversations, sessions, setup, skills -from hexagent_api.stream_manager import stream_manager _LOG_DIR = data_dir() / "logs" _LOG_DIR.mkdir(parents=True, exist_ok=True) @@ -77,8 +76,9 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]: cleanup_task = asyncio.create_task(_cleanup_expired_sessions()) yield cleanup_task.cancel() + from hexagent_api.stream_manager import stream_manager logger.info("Cancelling active streams...") - await stream_manager.cancel_all() + stream_manager.cancel_all() logger.info("Shutting down agent manager...") await agent_manager.stop() logger.info("Agent manager shut down.") diff --git a/libs/hexagent_demo/backend/hexagent_api/routes/chat.py b/libs/hexagent_demo/backend/hexagent_api/routes/chat.py index cdf5d85f..774df14f 100644 --- a/libs/hexagent_demo/backend/hexagent_api/routes/chat.py +++ b/libs/hexagent_demo/backend/hexagent_api/routes/chat.py @@ -15,7 +15,9 @@ import tempfile import time import urllib.parse +import uuid from pathlib import Path +from typing import AsyncIterator from fastapi import APIRouter, HTTPException, Query, Request, UploadFile, File from fastapi.responses import StreamingResponse @@ -115,22 +117,297 @@ def _build_human_message( blocks.extend(image_blocks) return HumanMessage(content=blocks) +SUBAGENT_TAG_PREFIX = "hexagent:subagent:" +INTERNAL_TOOL_TAG = "hexagent:tool" +# Seconds of silence before sending an SSE keepalive comment. +# Keeps the connection alive through proxies (Vite dev proxy defaults to +# ~120 s, nginx default proxy_read_timeout is 60 s). +_SSE_KEEPALIVE_SECONDS = 15 -@router.get("/api/chat/{conversation_id}/stream") -async def subscribe_stream(conversation_id: str) -> StreamingResponse: - """Reconnect to an active background stream for a conversation. - Returns the full event replay followed by live events. If no stream - is active, returns 204 No Content. +def _extract_tool_output_text(output: object) -> str: + """Extract a plain-text string from tool output. + + Tool output may be a plain string (legacy) or a list of content block + dicts from ``ToolResult.to_content_blocks()``. This helper normalises + both forms to a single string suitable for the frontend. """ - conv = store.get(conversation_id) - if conv is None: - raise HTTPException(status_code=404, detail="Conversation not found") - active = stream_manager.get_stream(conversation_id) - if active is None: - return StreamingResponse(content=iter(()), status_code=204) - return StreamingResponse(active.subscribe(), media_type="text/event-stream") + if isinstance(output, str): + return output + if isinstance(output, list): + parts: list[str] = [] + for block in output: + if isinstance(block, dict) and block.get("type") == "text": + parts.append(block.get("text", "")) + return "\n".join(parts) if parts else str(output) + return str(output) + + +def _get_subagent_task_id(event: dict) -> str | None: + """Extract task_id from subagent event tags, or None if parent.""" + for tag in event.get("tags", []): + if isinstance(tag, str) and tag.startswith(SUBAGENT_TAG_PREFIX): + return tag[len(SUBAGENT_TAG_PREFIX) :] + return None + + +def _extract_text_from_chunk(chunk: object) -> str: + """Extract text content from a chat model stream chunk.""" + if not hasattr(chunk, "content"): + return "" + content = chunk.content + if isinstance(content, str): + return content + if isinstance(content, list): + parts = [] + for block in content: + if isinstance(block, dict) and block.get("type") == "text": + parts.append(block.get("text", "")) + return "".join(parts) + return "" + + +def _extract_reasoning_from_chunk(chunk: object) -> str: + """Extract reasoning/thinking content from a chat model stream chunk. + + Supports multiple conventions: + - ``additional_kwargs["reasoning_content"]`` (DeepSeek / OpenRouter) + - Content blocks with ``type == "reasoning_content"`` + - Content blocks with ``type == "thinking"`` + """ + # Check additional_kwargs first (DeepSeek / OpenRouter convention) + additional = getattr(chunk, "additional_kwargs", None) + if isinstance(additional, dict): + rc = additional.get("reasoning_content") + if isinstance(rc, str) and rc: + return rc + + # Check content blocks + content = getattr(chunk, "content", None) + if isinstance(content, list): + parts = [] + for block in content: + if isinstance(block, dict): + btype = block.get("type", "") + if btype in ("reasoning_content", "thinking"): + parts.append( + block.get("reasoning_content", "") + or block.get("thinking", "") + or block.get("text", "") + ) + return "".join(parts) + return "" + + +async def _generate_events( # noqa: C901 + conversation_id: str, + model_id: str, + mode: str, + session_name: str | None, + msg_id: str, +) -> AsyncIterator[str]: + """Async generator that drives the agent and yields SSE event strings. + + Runs inside a background ``asyncio.Task`` managed by + :pymod:`hexagent_api.stream_manager` so it is **not** tied to any HTTP + connection. Message persistence happens here (always executes). + """ + yield f"event: message_start\ndata: {json.dumps({'id': msg_id})}\n\n" + + full_text = "" + blocks: list[dict[str, object]] = [] + current_thinking = "" + thinking_started_at: float | None = None + tool_index: dict[str, int] = {} + + try: + cfg = load_config() + target_model = next((m for m in cfg.models if m.id == model_id), None) + supports_image = target_model is not None and "image" in target_model.supported_modalities + + raw_messages = store.get_messages_for_agent(conversation_id) + messages = [] + for m in raw_messages: + if m["role"] == "user": + messages.append( + _build_human_message( + m["content"], + m.get("attachments"), + conversation_id, + model_supports_image=supports_image, + ) + ) + else: + messages.append(AIMessage(content=m["content"])) + + input_dict = {"messages": messages} + + # Stream agent events with keepalive support. + # We use asyncio.wait() instead of asyncio.wait_for() because + # wait_for cancels the awaitable on timeout, which would corrupt + # the underlying async generator state. + stream_iter = agent_manager.stream_response( + input_dict, conversation_id, model_id, mode=mode, session_name=session_name, + ).__aiter__() + next_event: asyncio.Task[dict] | None = None # type: ignore[type-arg] + try: + while True: + if next_event is None: + next_event = asyncio.ensure_future(stream_iter.__anext__()) + done, _ = await asyncio.wait( + {next_event}, timeout=_SSE_KEEPALIVE_SECONDS, + ) + if not done: + yield ": keepalive\n\n" + continue + next_event = None + try: + event = done.pop().result() + except StopAsyncIteration: + break + + if INTERNAL_TOOL_TAG in event.get("tags", []): + continue + + kind = event.get("event") + task_id = _get_subagent_task_id(event) + is_subagent = task_id is not None + + if kind == "on_chat_model_stream": + chunk = event.get("data", {}).get("chunk") + if chunk: + reasoning = _extract_reasoning_from_chunk(chunk) + if reasoning: + if is_subagent: + yield ( + f"event: subagent_reasoning_delta\n" + f"data: {json.dumps({'task_id': task_id, 'delta': reasoning})}\n\n" + ) + else: + if not current_thinking: + thinking_started_at = time.time() * 1000 + current_thinking += reasoning + yield f"event: reasoning_delta\ndata: {json.dumps({'delta': reasoning, 'ts': time.time() * 1000})}\n\n" + + tool_call_chunks = getattr(chunk, "tool_call_chunks", None) + if tool_call_chunks: + for tcc in tool_call_chunks: + idx = tcc["index"] if isinstance(tcc, dict) else tcc.index + name = tcc.get("name") if isinstance(tcc, dict) else tcc.name + tid = tcc.get("id") if isinstance(tcc, dict) else tcc.id + args = tcc.get("args") if isinstance(tcc, dict) else tcc.args + payload: dict[str, object] = {"index": idx} + if name: + payload["name"] = name + if tid: + payload["id"] = tid + if args: + payload["args"] = args + if is_subagent: + payload["task_id"] = task_id + yield ( + f"event: subagent_tool_call_delta\n" + f"data: {json.dumps(payload)}\n\n" + ) + else: + payload["ts"] = time.time() * 1000 + yield f"event: tool_call_delta\ndata: {json.dumps(payload)}\n\n" + + text = _extract_text_from_chunk(chunk) + if text: + if is_subagent: + yield ( + f"event: subagent_text_delta\n" + f"data: {json.dumps({'task_id': task_id, 'delta': text})}\n\n" + ) + else: + if current_thinking: + ended = time.time() * 1000 + blocks.append({"type": "thinking", "text": current_thinking, "startedAt": thinking_started_at, "endedAt": ended}) + current_thinking = "" + thinking_started_at = None + full_text += text + if blocks and blocks[-1].get("type") == "text": + blocks[-1]["text"] = str(blocks[-1]["text"]) + text + else: + blocks.append({"type": "text", "text": text}) + yield f"event: text_delta\ndata: {json.dumps({'delta': text, 'ts': time.time() * 1000})}\n\n" + + elif kind == "on_tool_start": + tool_name = event.get("name", "") + run_id = event.get("run_id", "") + tool_input = event.get("data", {}).get("input", {}) + if is_subagent: + yield ( + f"event: subagent_tool_start\n" + f"data: {json.dumps({'task_id': task_id, 'id': run_id, 'name': tool_name, 'input': tool_input})}\n\n" + ) + else: + if current_thinking: + blocks.append({"type": "thinking", "text": current_thinking}) + current_thinking = "" + tool_index[run_id] = len(blocks) + blocks.append({ + "type": "tool_call", + "tool": {"id": run_id, "name": tool_name, "input": tool_input}, + }) + yield ( + f"event: tool_use_start\n" + f"data: {json.dumps({'id': run_id, 'name': tool_name, 'input': tool_input, 'ts': time.time() * 1000})}\n\n" + ) + + elif kind == "on_tool_end": + run_id = event.get("run_id", "") + raw_output = event.get("data", {}).get("output", "") + output_content = getattr(raw_output, "content", raw_output) + output_text = _extract_tool_output_text(output_content) + if is_subagent: + yield ( + f"event: subagent_tool_result\n" + f"data: {json.dumps({'task_id': task_id, 'id': run_id, 'output': output_text})}\n\n" + ) + else: + idx = tool_index.get(run_id) + resolved_tool_name = "" + if idx is not None and idx < len(blocks): + tool_data = blocks[idx].get("tool") + if isinstance(tool_data, dict): + tool_data["output"] = output_text + resolved_tool_name = tool_data.get("name", "") + yield ( + f"event: tool_result\n" + f"data: {json.dumps({'id': run_id, 'output': output_text})}\n\n" + ) + + if resolved_tool_name == "PresentToUser": + _trigger_preconvert( + conversation_id, output_text, + ) + finally: + # Ensure the underlying agent stream generator is properly closed + # even if the background task is cancelled. + await stream_iter.aclose() + + except Exception as exc: + logger.exception("Error streaming agent response") + detail = f"{type(exc).__name__}: {exc}" + yield f"event: error\ndata: {json.dumps({'message': detail})}\n\n" + + # Flush any trailing thinking + if current_thinking: + ended = time.time() * 1000 + blocks.append({"type": "thinking", "text": current_thinking, "startedAt": thinking_started_at, "endedAt": ended}) + + if full_text or blocks: + store.add_message( + conversation_id, + "assistant", + full_text, + blocks=blocks if blocks else None, + ) + + yield f"event: message_end\ndata: {json.dumps({'id': msg_id})}\n\n" @router.post("/api/chat/{conversation_id}/message") @@ -140,7 +417,9 @@ async def send_message(conversation_id: str, body: MessageRequest) -> StreamingR if conv is None: raise HTTPException(status_code=404, detail="Conversation not found") - if stream_manager.is_streaming(conversation_id): + # Reject if conversation already has an active stream + existing = stream_manager.get_stream(conversation_id) + if existing and existing.status == "streaming": raise HTTPException(status_code=409, detail="Conversation already has an active stream") # Resolve model_id: explicit > conversation > default @@ -166,9 +445,6 @@ async def send_message(conversation_id: str, body: MessageRequest) -> StreamingR session_name = returned_session logger.info("Assigned session %s to conversation %s", session_name, conversation_id) - # Ensure the conversation's working_dir is actually mounted. - # It may differ from what the warm session had if the user switched - # folders quickly and the PATCH didn't complete before claiming. if mode == "cowork" and working_dir and session_name: try: await agent_manager.mount_working_dir(session_name, working_dir) @@ -181,41 +457,46 @@ async def send_message(conversation_id: str, body: MessageRequest) -> StreamingR if conv.title == "New conversation": conv.title = body.content[:50].strip() - # Build agent input - cfg = load_config() - target_model = next((m for m in cfg.models if m.id == model_id), None) - supports_image = target_model is not None and "image" in target_model.supported_modalities - - raw_messages = store.get_messages_for_agent(conversation_id) - messages = [] - for m in raw_messages: - if m["role"] == "user": - messages.append( - _build_human_message( - m["content"], - m.get("attachments"), - conversation_id, - model_supports_image=supports_image, - ) - ) - else: - messages.append(AIMessage(content=m["content"])) - - input_dict = {"messages": messages} - - # Start the agent as a background task and subscribe to events - active = stream_manager.start_stream( + # Spawn background task and subscribe to its event stream. + msg_id = str(uuid.uuid4()) + # Capture values for the closure + _model_id, _mode, _session_name, _msg_id = model_id, mode, session_name, msg_id + stream = stream_manager.start_stream( conversation_id, - agent_manager=agent_manager, - input_dict=input_dict, - model_id=model_id, - mode=mode, - session_name=session_name, - store=store, - preconvert_callback=_trigger_preconvert, + lambda: _generate_events(conversation_id, _model_id, _mode, _session_name, _msg_id), + msg_id, ) - return StreamingResponse(active.subscribe(), media_type="text/event-stream") + async def sse_subscriber(): + async for event_str in stream.subscribe(last_event_idx=0): + yield event_str + + return StreamingResponse(sse_subscriber(), media_type="text/event-stream") + + +@router.get("/api/chat/{conversation_id}/stream") +async def subscribe_stream( + conversation_id: str, + last_event_id: int = Query(0, alias="last_event_id"), +) -> StreamingResponse: + """Subscribe to an active (or recently finished) event stream for a conversation. + + Replays buffered events from *last_event_id*, then streams live events. + Returns 204 if there is no stream to subscribe to. + """ + stream = stream_manager.get_stream(conversation_id) + if stream is None: + return StreamingResponse(iter([]), media_type="text/event-stream", status_code=204) + + # If the stream is already done and the client has all events, nothing to send. + if stream.status != "streaming" and last_event_id >= len(stream.events): + return StreamingResponse(iter([]), media_type="text/event-stream", status_code=204) + + async def sse_subscriber(): + async for event_str in stream.subscribe(last_event_idx=last_event_id): + yield event_str + + return StreamingResponse(sse_subscriber(), media_type="text/event-stream") @router.post("/api/chat/{conversation_id}/upload") diff --git a/libs/hexagent_demo/backend/hexagent_api/routes/conversations.py b/libs/hexagent_demo/backend/hexagent_api/routes/conversations.py index ea7e40e1..600442cd 100644 --- a/libs/hexagent_demo/backend/hexagent_api/routes/conversations.py +++ b/libs/hexagent_demo/backend/hexagent_api/routes/conversations.py @@ -70,16 +70,22 @@ async def browse_folder() -> dict: raise HTTPException(status_code=501, detail=f"Folder picker not supported on {sys.platform}") +def _enrich_with_stream_status(d: dict, conversation_id: str) -> dict: + """Add streaming metadata to a conversation dict.""" + stream = stream_manager.get_stream(conversation_id) + if stream is not None and stream.status == "streaming": + d["streaming"] = True + d["stream_msg_id"] = stream.msg_id + d["stream_event_count"] = len(stream.events) + else: + d["streaming"] = False + return d + + @router.get("/api/conversations") async def list_conversations() -> list[dict]: """List all conversations sorted by updated_at descending.""" - result = [] - for c in store.list_all(): - d = c.to_detail() - if stream_manager.is_streaming(c.id): - d["streaming"] = True - result.append(d) - return result + return [_enrich_with_stream_status(c.to_detail(), c.id) for c in store.list_all()] @router.post("/api/conversations", status_code=201) @@ -128,10 +134,7 @@ async def get_conversation(conversation_id: str) -> dict: conv = store.get(conversation_id) if conv is None: raise HTTPException(status_code=404, detail="Conversation not found") - d = conv.to_detail() - if stream_manager.is_streaming(conversation_id): - d["streaming"] = True - return d + return _enrich_with_stream_status(conv.to_detail(), conversation_id) @router.delete("/api/conversations/{conversation_id}", status_code=204) diff --git a/libs/hexagent_demo/backend/hexagent_api/stream_manager.py b/libs/hexagent_demo/backend/hexagent_api/stream_manager.py new file mode 100644 index 00000000..50fa89d4 --- /dev/null +++ b/libs/hexagent_demo/backend/hexagent_api/stream_manager.py @@ -0,0 +1,179 @@ +"""Background stream manager for decoupling agent execution from HTTP lifecycle. + +Agent responses run as background ``asyncio.Task`` instances that write SSE +events into a per-conversation buffer. SSE endpoints become thin consumers +that can connect, disconnect, and reconnect freely — the buffer is the source +of truth. +""" + +from __future__ import annotations + +import asyncio +import logging +import time +from typing import AsyncIterator, Callable, Literal + +logger = logging.getLogger(__name__) + +_CLEANUP_DELAY_SECONDS = 120.0 + + +class ConversationStream: + """Per-conversation event buffer with fan-out to live subscribers.""" + + __slots__ = ( + "conversation_id", + "msg_id", + "status", + "events", + "_subscribers", + "_task", + "_created_at", + ) + + def __init__( + self, + conversation_id: str, + msg_id: str, + task: asyncio.Task, # type: ignore[type-arg] + ) -> None: + self.conversation_id = conversation_id + self.msg_id = msg_id + self.status: Literal["streaming", "done", "error"] = "streaming" + self.events: list[str] = [] + self._subscribers: set[asyncio.Queue[str | None]] = set() + self._task = task + self._created_at = time.monotonic() + + def push(self, event_str: str) -> None: + """Append an SSE event string to the buffer and notify subscribers.""" + self.events.append(event_str) + for q in self._subscribers: + q.put_nowait(event_str) + + def finish(self, status: Literal["done", "error"]) -> None: + """Mark the stream as complete and wake all subscribers.""" + self.status = status + for q in self._subscribers: + q.put_nowait(None) # sentinel + + async def subscribe(self, last_event_idx: int = 0) -> AsyncIterator[str]: + """Yield SSE events, replaying from *last_event_idx* then live. + + The caller can break out or let the iterator end naturally when the + stream finishes (``None`` sentinel). + + Ordering guarantee: the queue is registered in ``_subscribers`` + *before* taking the replay snapshot, and both happen synchronously + (no ``await`` in between). Since ``push()`` appends to ``events`` + and enqueues in a single synchronous call, there is no window for + an event to be missed or duplicated. + """ + queue: asyncio.Queue[str | None] = asyncio.Queue() + self._subscribers.add(queue) + try: + # Replay buffered events the subscriber missed. + # Snapshot length taken synchronously after queue registration. + snapshot_len = len(self.events) + for event_str in self.events[last_event_idx:snapshot_len]: + yield event_str + + # If the stream already finished, nothing more to wait for. + if self.status != "streaming": + return + + # Live events from the queue. + while True: + item = await queue.get() + if item is None: + return + yield item + finally: + self._subscribers.discard(queue) + + +class StreamManager: + """Manages background agent tasks and their event buffers.""" + + def __init__(self) -> None: + self._streams: dict[str, ConversationStream] = {} + self._cleanup_handles: dict[str, asyncio.TimerHandle] = {} + + def get_stream(self, conversation_id: str) -> ConversationStream | None: + return self._streams.get(conversation_id) + + def start_stream( + self, + conversation_id: str, + generator_factory: Callable[[], AsyncIterator[str]], + msg_id: str, + ) -> ConversationStream: + """Spawn a background task that consumes *generator_factory* and buffers events.""" + # Cancel any pending cleanup for this conversation (e.g. user sent a + # new message right after previous stream finished). + handle = self._cleanup_handles.pop(conversation_id, None) + if handle is not None: + handle.cancel() + + # We need the stream reference inside _run, so create it with a + # temporary task, then immediately replace with the real one. + # Both happen synchronously before yielding to the event loop, + # so _run never sees the dummy. + dummy_task: asyncio.Task[None] = asyncio.get_running_loop().create_future() # type: ignore[assignment] + stream = ConversationStream(conversation_id, msg_id, dummy_task) + task = asyncio.create_task( + self._run(stream, generator_factory), + name=f"stream-{conversation_id}", + ) + stream._task = task + self._streams[conversation_id] = stream + return stream + + async def _run( + self, + stream: ConversationStream, + generator_factory: Callable[[], AsyncIterator[str]], + ) -> None: + """Consume the async generator and push events into the stream.""" + status: Literal["done", "error"] = "done" + try: + async for event_str in generator_factory(): + stream.push(event_str) + except asyncio.CancelledError: + logger.info("Stream cancelled for %s", stream.conversation_id) + status = "error" + except Exception: + logger.exception( + "Background stream error for %s", stream.conversation_id + ) + status = "error" + finally: + stream.finish(status) + self._schedule_cleanup(stream.conversation_id) + + def _schedule_cleanup(self, conversation_id: str) -> None: + """Remove stream buffer after a TTL so reconnecting clients can replay.""" + loop = asyncio.get_running_loop() + handle = loop.call_later( + _CLEANUP_DELAY_SECONDS, + self._do_cleanup, + conversation_id, + ) + self._cleanup_handles[conversation_id] = handle + + def _do_cleanup(self, conversation_id: str) -> None: + self._streams.pop(conversation_id, None) + self._cleanup_handles.pop(conversation_id, None) + logger.debug("Cleaned up stream buffer for %s", conversation_id) + + def cancel_all(self) -> None: + """Cancel all active stream tasks (used during shutdown).""" + for stream in self._streams.values(): + if not stream._task.done(): + stream._task.cancel() + for handle in self._cleanup_handles.values(): + handle.cancel() + self._cleanup_handles.clear() + + +stream_manager = StreamManager() diff --git a/libs/hexagent_demo/frontend/src/App.tsx b/libs/hexagent_demo/frontend/src/App.tsx index 0f31b871..3da8d60b 100644 --- a/libs/hexagent_demo/frontend/src/App.tsx +++ b/libs/hexagent_demo/frontend/src/App.tsx @@ -1,6 +1,6 @@ import { useReducer, useEffect, useCallback, useRef, useState } from "react"; import { AppContext, initialState, reducer } from "./store"; -import { listConversations, createConversation, createWarmSession, deleteWarmSession, sendMessage, getServerConfig, getVMStatus, type ServerConfig } from "./api"; +import { listConversations, createConversation, createWarmSession, deleteWarmSession, sendMessage, subscribeToStream, getServerConfig, getVMStatus, type ServerConfig } from "./api"; import { useSettings } from "./hooks/useSettings"; import Sidebar from "./components/Sidebar"; import ChatArea from "./components/ChatArea"; @@ -227,6 +227,93 @@ function App() { const streamingRef = useRef(state.streamingByConversation); streamingRef.current = state.streamingByConversation; + // Build stream callbacks for a given conversationId. + // Shared between doSendMessage and the reconnect effect. + const makeStreamCallbacks = useCallback( + (conversationId: string) => ({ + onMessageStart: (id: string) => { + dispatch({ type: "REQUEST_END" }); + dispatch({ type: "STREAM_START", payload: { messageId: id, conversationId } }); + }, + onTextDelta: (delta: string, ts?: number) => { + dispatch({ type: "STREAM_TEXT_DELTA", payload: { conversationId, delta, ts } }); + }, + onReasoningDelta: (delta: string, ts?: number) => { + dispatch({ type: "STREAM_REASONING_DELTA", payload: { conversationId, delta, ts } }); + }, + onToolCallDelta: (data: { index: number; name?: string; id?: string; args?: string; ts?: number }) => { + dispatch({ type: "STREAM_TOOL_CALL_DELTA", payload: { conversationId, ...data } }); + }, + onToolUseStart: (tool: { id: string; name: string; input: Record; ts?: number }) => { + dispatch({ type: "STREAM_TOOL_USE_START", payload: { conversationId, tool } }); + }, + onToolResult: (result: { id: string; output: string }) => { + dispatch({ type: "STREAM_TOOL_RESULT", payload: { conversationId, ...result } }); + }, + onSubagentTextDelta: (data: { task_id: string; delta: string }) => { + dispatch({ type: "STREAM_SUBAGENT_TEXT_DELTA", payload: { conversationId, ...data } }); + }, + onSubagentReasoningDelta: (data: { task_id: string; delta: string }) => { + dispatch({ type: "STREAM_SUBAGENT_REASONING_DELTA", payload: { conversationId, ...data } }); + }, + onSubagentToolCallDelta: (data: { task_id: string; index: number; name?: string; id?: string; args?: string }) => { + dispatch({ type: "STREAM_SUBAGENT_TOOL_CALL_DELTA", payload: { conversationId, ...data } }); + }, + onSubagentToolStart: (data: { task_id: string; id: string; name: string; input: Record }) => { + dispatch({ type: "STREAM_SUBAGENT_TOOL_START", payload: { conversationId, ...data } }); + }, + onSubagentToolResult: (data: { task_id: string; id: string; output: string }) => { + dispatch({ type: "STREAM_SUBAGENT_TOOL_RESULT", payload: { conversationId, ...data } }); + }, + onMessageEnd: (id: string) => { + dispatch({ type: "STREAM_END", payload: { conversationId, messageId: id } }); + abortMapRef.current.delete(conversationId); + }, + onError: (error: string) => { + dispatch({ type: "REQUEST_END" }); + if (streamingRef.current[conversationId]) { + dispatch({ type: "STREAM_ERROR", payload: { conversationId, error } }); + } else { + dispatch({ type: "SHOW_NOTIFICATION", payload: { message: error, type: "error" } }); + } + abortMapRef.current.delete(conversationId); + }, + }), + [dispatch], + ); + + // Reconnect to active streams after page load or conversation switch. + // If the backend reports a conversation is streaming (agent running in + // background), subscribe to the event stream so the UI picks up where + // it left off. + // + // We use refs (conversationsRef, streamingRef) instead of state to avoid + // re-running (and aborting the connection) whenever conversations or + // streaming state change during normal streaming. The effect should only + // fire when activeConversationId changes. + const makeStreamCallbacksRef = useRef(makeStreamCallbacks); + makeStreamCallbacksRef.current = makeStreamCallbacks; + useEffect(() => { + if (!state.activeConversationId) return; + // Don't reconnect if we're already streaming for this conversation + if (streamingRef.current[state.activeConversationId]) return; + const conv = conversationsRef.current.find((c) => c.id === state.activeConversationId); + if (!conv?.streaming) return; + + const conversationId = conv.id; + const controller = subscribeToStream( + conversationId, + makeStreamCallbacksRef.current(conversationId), + 0, + ); + abortMapRef.current.set(conversationId, controller); + return () => { + controller.abort(); + abortMapRef.current.delete(conversationId); + }; + // eslint-disable-next-line react-hooks/exhaustive-deps + }, [state.activeConversationId]); + const doSendMessage = useCallback( async (conversationId: string, content: string, attachments?: Attachment[]) => { const allAttachments = attachments ?? []; @@ -271,59 +358,15 @@ function App() { const conv = state.conversations.find((c) => c.id === conversationId); const modelId = conv?.model_id || state.selectedModelId || undefined; - const controller = sendMessage(conversationId, fullContent, { - onMessageStart: (id) => { - dispatch({ type: "REQUEST_END" }); - dispatch({ type: "STREAM_START", payload: { messageId: id, conversationId } }); - }, - onTextDelta: (delta) => { - dispatch({ type: "STREAM_TEXT_DELTA", payload: { conversationId, delta } }); - }, - onReasoningDelta: (delta) => { - dispatch({ type: "STREAM_REASONING_DELTA", payload: { conversationId, delta } }); - }, - onToolCallDelta: (data) => { - dispatch({ type: "STREAM_TOOL_CALL_DELTA", payload: { conversationId, ...data } }); - }, - onToolUseStart: (tool) => { - dispatch({ type: "STREAM_TOOL_USE_START", payload: { conversationId, tool } }); - }, - onToolResult: (result) => { - dispatch({ type: "STREAM_TOOL_RESULT", payload: { conversationId, ...result } }); - }, - onSubagentTextDelta: (data) => { - dispatch({ type: "STREAM_SUBAGENT_TEXT_DELTA", payload: { conversationId, ...data } }); - }, - onSubagentReasoningDelta: (data) => { - dispatch({ type: "STREAM_SUBAGENT_REASONING_DELTA", payload: { conversationId, ...data } }); - }, - onSubagentToolCallDelta: (data) => { - dispatch({ type: "STREAM_SUBAGENT_TOOL_CALL_DELTA", payload: { conversationId, ...data } }); - }, - onSubagentToolStart: (data) => { - dispatch({ type: "STREAM_SUBAGENT_TOOL_START", payload: { conversationId, ...data } }); - }, - onSubagentToolResult: (data) => { - dispatch({ type: "STREAM_SUBAGENT_TOOL_RESULT", payload: { conversationId, ...data } }); - }, - onMessageEnd: (id) => { - dispatch({ type: "STREAM_END", payload: { conversationId, messageId: id } }); - abortMapRef.current.delete(conversationId); - }, - onError: (error) => { - dispatch({ type: "REQUEST_END" }); - if (streamingRef.current[conversationId]) { - dispatch({ type: "STREAM_ERROR", payload: { conversationId, error } }); - } else { - dispatch({ type: "SHOW_NOTIFICATION", payload: { message: error, type: "error" } }); - } - abortMapRef.current.delete(conversationId); - }, - }, modelId, allAttachments.length > 0 ? allAttachments : undefined); + const controller = sendMessage( + conversationId, fullContent, + makeStreamCallbacks(conversationId), + modelId, allAttachments.length > 0 ? allAttachments : undefined, + ); abortMapRef.current.set(conversationId, controller); }, - [dispatch, state.conversations, state.selectedModelId, state.isStreaming] + [dispatch, state.conversations, state.selectedModelId, makeStreamCallbacks] ); const handleNewConversation = useCallback(() => { diff --git a/libs/hexagent_demo/frontend/src/api.ts b/libs/hexagent_demo/frontend/src/api.ts index 1f1438c1..6bc4dc43 100644 --- a/libs/hexagent_demo/frontend/src/api.ts +++ b/libs/hexagent_demo/frontend/src/api.ts @@ -111,10 +111,10 @@ export async function deleteConversation(id: string): Promise { export interface StreamCallbacks { onMessageStart: (id: string) => void; - onTextDelta: (delta: string) => void; - onReasoningDelta: (delta: string) => void; - onToolCallDelta: (data: { index: number; name?: string; id?: string; args?: string }) => void; - onToolUseStart: (tool: { id: string; name: string; input: Record }) => void; + onTextDelta: (delta: string, ts?: number) => void; + onReasoningDelta: (delta: string, ts?: number) => void; + onToolCallDelta: (data: { index: number; name?: string; id?: string; args?: string; ts?: number }) => void; + onToolUseStart: (tool: { id: string; name: string; input: Record; ts?: number }) => void; onToolResult: (result: { id: string; output: string }) => void; onSubagentTextDelta: (data: { task_id: string; delta: string }) => void; onSubagentReasoningDelta: (data: { task_id: string; delta: string }) => void; @@ -125,9 +125,14 @@ export interface StreamCallbacks { onError: (error: string) => void; } -/** Read an SSE response body and dispatch events to callbacks. */ -async function _readSSEStream(response: Response, callbacks: StreamCallbacks): Promise { - const reader = response.body!.getReader(); +/** + * Parse an SSE stream and dispatch events to callbacks. + * Shared by sendMessage() and subscribeToStream(). + */ +async function _parseSSEStream( + reader: ReadableStreamDefaultReader, + callbacks: StreamCallbacks, +): Promise { const decoder = new TextDecoder(); let buffer = ""; let currentEvent = ""; @@ -151,10 +156,10 @@ async function _readSSEStream(response: Response, callbacks: StreamCallbacks): P callbacks.onMessageStart(data.id); break; case "text_delta": - callbacks.onTextDelta(data.delta); + callbacks.onTextDelta(data.delta, data.ts); break; case "reasoning_delta": - callbacks.onReasoningDelta(data.delta); + callbacks.onReasoningDelta(data.delta, data.ts); break; case "tool_call_delta": callbacks.onToolCallDelta(data); @@ -221,7 +226,7 @@ export function sendMessage( callbacks.onError(detail?.detail || `HTTP ${response.status}: ${response.statusText}`); return; } - await _readSSEStream(response, callbacks); + await _parseSSEStream(response.body!.getReader(), callbacks); }) .catch((err: Error) => { if (err.name !== "AbortError") { @@ -233,22 +238,22 @@ export function sendMessage( } /** - * Reconnect to an active background stream for a conversation. - * Returns null if no active stream exists (HTTP 204). + * Subscribe to an active (or recently finished) event stream for a conversation. + * Used to reconnect after page refresh. */ -export function subscribeStream( +export function subscribeToStream( conversationId: string, callbacks: StreamCallbacks, + lastEventId: number = 0, ): AbortController { const controller = new AbortController(); - fetch(`${API_BASE}/api/chat/${conversationId}/stream`, { + fetch(`${API_BASE}/api/chat/${conversationId}/stream?last_event_id=${lastEventId}`, { signal: controller.signal, }) .then(async (response) => { - if (response.status === 204) return; // No active stream - if (!response.ok) return; - await _readSSEStream(response, callbacks); + if (response.status === 204 || !response.ok) return; // no active stream + await _parseSSEStream(response.body!.getReader(), callbacks); }) .catch((err: Error) => { if (err.name !== "AbortError") { diff --git a/libs/hexagent_demo/frontend/src/store.ts b/libs/hexagent_demo/frontend/src/store.ts index 3ad04d72..a0d4c045 100644 --- a/libs/hexagent_demo/frontend/src/store.ts +++ b/libs/hexagent_demo/frontend/src/store.ts @@ -87,10 +87,10 @@ export type Action = | { type: "REQUEST_END" } | { type: "ADD_USER_MESSAGE"; payload: { conversationId: string; message: Message } } | { type: "STREAM_START"; payload: { messageId: string; conversationId: string } } - | { type: "STREAM_TEXT_DELTA"; payload: { conversationId: string; delta: string } } - | { type: "STREAM_REASONING_DELTA"; payload: { conversationId: string; delta: string } } - | { type: "STREAM_TOOL_CALL_DELTA"; payload: { conversationId: string; index: number; name?: string; id?: string; args?: string } } - | { type: "STREAM_TOOL_USE_START"; payload: { conversationId: string; tool: ToolCall } } + | { type: "STREAM_TEXT_DELTA"; payload: { conversationId: string; delta: string; ts?: number } } + | { type: "STREAM_REASONING_DELTA"; payload: { conversationId: string; delta: string; ts?: number } } + | { type: "STREAM_TOOL_CALL_DELTA"; payload: { conversationId: string; index: number; name?: string; id?: string; args?: string; ts?: number } } + | { type: "STREAM_TOOL_USE_START"; payload: { conversationId: string; tool: ToolCall & { ts?: number } } } | { type: "STREAM_TOOL_RESULT"; payload: { conversationId: string; id: string; output: string } } | { type: "STREAM_SUBAGENT_TEXT_DELTA"; payload: { conversationId: string; task_id: string; delta: string } } | { type: "STREAM_SUBAGENT_REASONING_DELTA"; payload: { conversationId: string; task_id: string; delta: string } } @@ -131,8 +131,8 @@ function finalizeStreamingTool(blocks: ContentBlock[]): ContentBlock[] { return blocks; } -function appendTextDelta(blocks: ContentBlock[], delta: string): ContentBlock[] { - const finalized = finalizeStreamingTool(finalizeThinking(blocks)); +function appendTextDelta(blocks: ContentBlock[], delta: string, ts?: number): ContentBlock[] { + const finalized = finalizeStreamingTool(finalizeThinking(blocks, ts)); const last = finalized[finalized.length - 1]; if (last && last.type === "text") { return [...finalized.slice(0, -1), { type: "text", text: last.text + delta }]; @@ -140,22 +140,22 @@ function appendTextDelta(blocks: ContentBlock[], delta: string): ContentBlock[] return [...finalized, { type: "text", text: delta }]; } -function appendReasoningDelta(blocks: ContentBlock[], delta: string): ContentBlock[] { +function appendReasoningDelta(blocks: ContentBlock[], delta: string, ts?: number): ContentBlock[] { const finalized = finalizeStreamingTool(blocks); const last = finalized[finalized.length - 1]; if (last && last.type === "thinking") { return [...finalized.slice(0, -1), { ...last, text: last.text + delta }]; } - return [...finalized, { type: "thinking", text: delta, startedAt: Date.now() }]; + return [...finalized, { type: "thinking", text: delta, startedAt: ts ?? Date.now() }]; } /** Mark the last thinking block as ended (if it has no endedAt yet). */ -function finalizeThinking(blocks: ContentBlock[]): ContentBlock[] { +function finalizeThinking(blocks: ContentBlock[], ts?: number): ContentBlock[] { for (let i = blocks.length - 1; i >= 0; i--) { const b = blocks[i]; if (b.type === "thinking" && !b.endedAt) { const updated = [...blocks]; - updated[i] = { ...b, endedAt: Date.now() }; + updated[i] = { ...b, endedAt: ts ?? Date.now() }; return updated; } // Only finalize the most recent thinking block — stop searching once we hit a non-thinking block @@ -166,9 +166,9 @@ function finalizeThinking(blocks: ContentBlock[]): ContentBlock[] { function appendToolCallDelta( blocks: ContentBlock[], - delta: { index: number; name?: string; id?: string; args?: string }, + delta: { index: number; name?: string; id?: string; args?: string; ts?: number }, ): ContentBlock[] { - blocks = finalizeThinking(blocks); + blocks = finalizeThinking(blocks, delta.ts); const last = blocks[blocks.length - 1]; // Append to existing streaming block only if same index if (last && last.type === "tool_call" && last.tool.streaming && last.tool.streamIndex === delta.index) { @@ -238,8 +238,8 @@ function subAppendToolCallDelta( ]; } -function appendToolStart(blocks: ContentBlock[], tool: ToolCall): ContentBlock[] { - blocks = finalizeThinking(blocks); +function appendToolStart(blocks: ContentBlock[], tool: ToolCall & { ts?: number }): ContentBlock[] { + blocks = finalizeThinking(blocks, tool.ts); blocks = finalizeStreamingTool(blocks); // Find existing block: match by id first, then by name (first incomplete one) @@ -557,6 +557,10 @@ export function reducer(state: AppState, action: Action): AppState { case "STREAM_START": { const { conversationId: cid, messageId } = action.payload; + // Check if a message with this ID already exists (reconnect replay). + // If so, just re-create the streaming entry without adding a duplicate. + const conv = state.conversations.find((c) => c.id === cid); + const alreadyExists = conv?.messages?.some((m) => m.id === messageId) ?? false; const placeholder: Message = { id: messageId, role: "assistant", @@ -570,22 +574,24 @@ export function reducer(state: AppState, action: Action): AppState { ...state.streamingByConversation, [cid]: { messageId, blocks: [] }, }, - conversations: state.conversations.map((c) => - c.id === cid - ? { ...c, messages: [...(c.messages ?? []), placeholder] } - : c - ), + conversations: alreadyExists + ? state.conversations + : state.conversations.map((c) => + c.id === cid + ? { ...c, messages: [...(c.messages ?? []), placeholder] } + : c + ), }; } case "STREAM_TEXT_DELTA": return updateStreamBlocks(state, action.payload.conversationId, (blocks) => - appendTextDelta(blocks, action.payload.delta), + appendTextDelta(blocks, action.payload.delta, action.payload.ts), ); case "STREAM_REASONING_DELTA": return updateStreamBlocks(state, action.payload.conversationId, (blocks) => - appendReasoningDelta(blocks, action.payload.delta), + appendReasoningDelta(blocks, action.payload.delta, action.payload.ts), ); case "STREAM_TOOL_CALL_DELTA": diff --git a/libs/hexagent_demo/frontend/src/types.ts b/libs/hexagent_demo/frontend/src/types.ts index 02598c67..86b0a247 100644 --- a/libs/hexagent_demo/frontend/src/types.ts +++ b/libs/hexagent_demo/frontend/src/types.ts @@ -10,8 +10,12 @@ export interface Conversation { messages: Message[]; created_at: string; updated_at: string; - /** True when the backend has an active background stream for this conversation. */ + /** True when a background agent stream is active for this conversation. */ streaming?: boolean; + /** The assistant message ID of the active stream (for reconnect). */ + stream_msg_id?: string; + /** Number of SSE events buffered so far (for resume offset). */ + stream_event_count?: number; } export interface Attachment { From 259a526fe938b86e4a182b0908de7bbf5dbd7ae2 Mon Sep 17 00:00:00 2001 From: "Anqi (Anthony) Tang" Date: Sat, 28 Mar 2026 09:52:23 +0800 Subject: [PATCH 9/9] feat(i18n): add multi-language support with English and Simplified Chinese Add internationalization infrastructure using react-i18next with namespaced JSON translation files. All hardcoded UI strings across 14 components are extracted into translation keys. Language setting persists in both localStorage (for instant load) and backend config.json (for cross-device sync). Adding a new language requires only: (1) copy en/ locale folder, (2) translate values, (3) register in i18n.ts, (4) add to LANGUAGES array in SettingsModal. Co-Authored-By: Claude Opus 4.6 (1M context) --- .../backend/hexagent_api/config.py | 4 +- .../backend/hexagent_api/routes/config.py | 3 + libs/hexagent_demo/frontend/package-lock.json | 95 +++- libs/hexagent_demo/frontend/package.json | 2 + libs/hexagent_demo/frontend/src/App.tsx | 9 +- libs/hexagent_demo/frontend/src/api.ts | 3 +- .../frontend/src/components/ChatArea.tsx | 8 +- .../frontend/src/components/ChatInput.tsx | 24 +- .../frontend/src/components/FolderPicker.tsx | 20 +- .../src/components/InputSettingsMenu.tsx | 26 +- .../frontend/src/components/MessageBubble.tsx | 4 +- .../frontend/src/components/ModelPicker.tsx | 8 +- .../src/components/OnboardingWizard.tsx | 223 +++++----- .../src/components/RestartRequiredModal.tsx | 12 +- .../frontend/src/components/RightPanel.tsx | 6 +- .../frontend/src/components/SearchModal.tsx | 22 +- .../frontend/src/components/SettingsModal.tsx | 405 ++++++++++-------- .../frontend/src/components/Sidebar.tsx | 24 +- .../src/components/VMSetupFloater.tsx | 12 +- .../frontend/src/components/WelcomeScreen.tsx | 50 +-- .../frontend/src/hooks/useSettings.ts | 11 + libs/hexagent_demo/frontend/src/i18n.ts | 79 ++++ .../frontend/src/locales/en/chat.json | 20 + .../frontend/src/locales/en/common.json | 20 + .../frontend/src/locales/en/misc.json | 37 ++ .../frontend/src/locales/en/onboarding.json | 116 +++++ .../frontend/src/locales/en/search.json | 11 + .../frontend/src/locales/en/settings.json | 200 +++++++++ .../frontend/src/locales/en/sidebar.json | 16 + .../frontend/src/locales/en/welcome.json | 29 ++ .../frontend/src/locales/zh-CN/chat.json | 20 + .../frontend/src/locales/zh-CN/common.json | 20 + .../frontend/src/locales/zh-CN/misc.json | 37 ++ .../src/locales/zh-CN/onboarding.json | 116 +++++ .../frontend/src/locales/zh-CN/search.json | 11 + .../frontend/src/locales/zh-CN/settings.json | 200 +++++++++ .../frontend/src/locales/zh-CN/sidebar.json | 16 + .../frontend/src/locales/zh-CN/welcome.json | 29 ++ libs/hexagent_demo/frontend/src/main.tsx | 1 + 39 files changed, 1547 insertions(+), 402 deletions(-) create mode 100644 libs/hexagent_demo/frontend/src/i18n.ts create mode 100644 libs/hexagent_demo/frontend/src/locales/en/chat.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/common.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/misc.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/onboarding.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/search.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/settings.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/sidebar.json create mode 100644 libs/hexagent_demo/frontend/src/locales/en/welcome.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/chat.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/common.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/misc.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/onboarding.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/search.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/settings.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/sidebar.json create mode 100644 libs/hexagent_demo/frontend/src/locales/zh-CN/welcome.json diff --git a/libs/hexagent_demo/backend/hexagent_api/config.py b/libs/hexagent_demo/backend/hexagent_api/config.py index 53696e60..869114a4 100644 --- a/libs/hexagent_demo/backend/hexagent_api/config.py +++ b/libs/hexagent_demo/backend/hexagent_api/config.py @@ -92,6 +92,7 @@ class AppConfig: sandbox: SandboxConfig = field(default_factory=SandboxConfig) disabled_skills: list[str] = field(default_factory=list) mcp_servers: list[McpServerConfig] = field(default_factory=list) + language: str = "en" @property def main_model(self) -> ModelConfig | None: @@ -120,7 +121,8 @@ def load_config() -> AppConfig: sandbox = SandboxConfig(**file_data["sandbox"]) if "sandbox" in file_data else SandboxConfig() disabled_skills = file_data.get("disabled_skills", []) mcp_servers = [McpServerConfig(**m) for m in file_data.get("mcp_servers", [])] - return AppConfig(models=models, main_model_id=main_id, fast_model_id=fast_id, agents=agents, tools=tools, sandbox=sandbox, disabled_skills=disabled_skills, mcp_servers=mcp_servers) + language = file_data.get("language", "en") + return AppConfig(models=models, main_model_id=main_id, fast_model_id=fast_id, agents=agents, tools=tools, sandbox=sandbox, disabled_skills=disabled_skills, mcp_servers=mcp_servers, language=language) # No config.json — return empty config (frontend will show setup flow) config = AppConfig() diff --git a/libs/hexagent_demo/backend/hexagent_api/routes/config.py b/libs/hexagent_demo/backend/hexagent_api/routes/config.py index f7b1ef26..3e56a389 100644 --- a/libs/hexagent_demo/backend/hexagent_api/routes/config.py +++ b/libs/hexagent_demo/backend/hexagent_api/routes/config.py @@ -82,6 +82,9 @@ async def put_config(body: dict[str, Any]) -> dict[str, Any]: if "mcp_servers" in body: current.mcp_servers = [McpServerConfig(**m) for m in body["mcp_servers"]] + if "language" in body: + current.language = body["language"] + save_config(current) # Invalidate cached agents so they pick up new config on next use diff --git a/libs/hexagent_demo/frontend/package-lock.json b/libs/hexagent_demo/frontend/package-lock.json index ec9d4b22..2a40d5b2 100644 --- a/libs/hexagent_demo/frontend/package-lock.json +++ b/libs/hexagent_demo/frontend/package-lock.json @@ -10,12 +10,14 @@ "dependencies": { "docx-preview": "^0.3.7", "echarts": "^6.0.0", + "i18next": "^25.10.10", "lucide-react": "^0.577.0", "mermaid": "^11.13.0", "pdfjs-dist": "^5.4.296", "pptx-viewer": "^0.1.0", "react": "^19.0.0", "react-dom": "^19.0.0", + "react-i18next": "^17.0.0", "react-markdown": "^9.0.1", "react-pdf": "^10.4.1", "react-syntax-highlighter": "^16.1.1", @@ -290,9 +292,9 @@ } }, "node_modules/@babel/runtime": { - "version": "7.28.6", - "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.28.6.tgz", - "integrity": "sha512-05WQkdpL9COIMz4LjTxGpPNCdlpyimKppYNoJ5Di5EUObifl8t4tuLuUBBZEpoLYOmfvIWrsp9fCl0HoPRVTdA==", + "version": "7.29.2", + "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.29.2.tgz", + "integrity": "sha512-JiDShH45zKHWyGe4ZNVRrCjBz8Nh9TMmZG1kh4QTK8hCBTWBi8Da+i7s1fJw7/lYpM4ccepSNfqzZ/QvABBi5g==", "license": "MIT", "engines": { "node": ">=6.9.0" @@ -4116,6 +4118,15 @@ "integrity": "sha512-PDEfEF102G23vHmPhLyPboFCD+BkMGu+GuJe2d9/eH4FsCwvgBpnc9n0pGE+ffKdph38s6foEZiEjdgHdzp+IA==", "license": "CC0-1.0" }, + "node_modules/html-parse-stringify": { + "version": "3.0.1", + "resolved": "https://registry.npmjs.org/html-parse-stringify/-/html-parse-stringify-3.0.1.tgz", + "integrity": "sha512-KknJ50kTInJ7qIScF3jeaFRpMpE8/lfiTdzf/twXyPBLAGrLRTmkz3AdTnKeh40X8k9L2fdYwEp/42WGXIRGcg==", + "license": "MIT", + "dependencies": { + "void-elements": "3.1.0" + } + }, "node_modules/html-url-attributes": { "version": "3.0.1", "resolved": "https://registry.npmjs.org/html-url-attributes/-/html-url-attributes-3.0.1.tgz", @@ -4136,6 +4147,37 @@ "url": "https://github.com/sponsors/wooorm" } }, + "node_modules/i18next": { + "version": "25.10.10", + "resolved": "https://registry.npmjs.org/i18next/-/i18next-25.10.10.tgz", + "integrity": "sha512-cqUW2Z3EkRx7NqSyywjkgCLK7KLCL6IFVFcONG7nVYIJ3ekZ1/N5jUsihHV6Bq37NfhgtczxJcxduELtjTwkuQ==", + "funding": [ + { + "type": "individual", + "url": "https://www.locize.com/i18next" + }, + { + "type": "individual", + "url": "https://www.i18next.com/how-to/faq#i18next-is-awesome.-how-can-i-support-the-project" + }, + { + "type": "individual", + "url": "https://www.locize.com" + } + ], + "license": "MIT", + "dependencies": { + "@babel/runtime": "^7.29.2" + }, + "peerDependencies": { + "typescript": "^5 || ^6" + }, + "peerDependenciesMeta": { + "typescript": { + "optional": true + } + } + }, "node_modules/iconv-lite": { "version": "0.6.3", "resolved": "https://registry.npmjs.org/iconv-lite/-/iconv-lite-0.6.3.tgz", @@ -5868,6 +5910,33 @@ "react": "^19.2.4" } }, + "node_modules/react-i18next": { + "version": "17.0.0", + "resolved": "https://registry.npmjs.org/react-i18next/-/react-i18next-17.0.0.tgz", + "integrity": "sha512-L7aqwOePCExt6nlF7000lN2YKWnR7IpSpQId9sj01798Xn3LAncBdTHKl9lA/nr+YrG78BTqWPJxq9mlrrmH7Q==", + "license": "MIT", + "dependencies": { + "@babel/runtime": "^7.29.2", + "html-parse-stringify": "^3.0.1", + "use-sync-external-store": "^1.6.0" + }, + "peerDependencies": { + "i18next": ">= 25.10.10", + "react": ">= 16.8.0", + "typescript": "^5 || ^6" + }, + "peerDependenciesMeta": { + "react-dom": { + "optional": true + }, + "react-native": { + "optional": true + }, + "typescript": { + "optional": true + } + } + }, "node_modules/react-markdown": { "version": "9.1.0", "resolved": "https://registry.npmjs.org/react-markdown/-/react-markdown-9.1.0.tgz", @@ -6419,7 +6488,7 @@ "version": "5.6.3", "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.6.3.tgz", "integrity": "sha512-hjcS1mhfuyi4WW8IWtjP7brDrG2cuDZukyrYrSauoXGNgx0S7zceP07adYkJycEr56BOUTNPzbInooiN3fn1qw==", - "dev": true, + "devOptional": true, "license": "Apache-2.0", "bin": { "tsc": "bin/tsc", @@ -6587,6 +6656,15 @@ "punycode": "^2.1.0" } }, + "node_modules/use-sync-external-store": { + "version": "1.6.0", + "resolved": "https://registry.npmjs.org/use-sync-external-store/-/use-sync-external-store-1.6.0.tgz", + "integrity": "sha512-Pp6GSwGP/NrPIrxVFAIkOQeyw8lFenOHijQWkUTrDvrF4ALqylP2C/KCkeS9dpUM3KvYRQhna5vt7IL95+ZQ9w==", + "license": "MIT", + "peerDependencies": { + "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" + } + }, "node_modules/utif2": { "version": "4.1.0", "resolved": "https://registry.npmjs.org/utif2/-/utif2-4.1.0.tgz", @@ -6732,6 +6810,15 @@ } } }, + "node_modules/void-elements": { + "version": "3.1.0", + "resolved": "https://registry.npmjs.org/void-elements/-/void-elements-3.1.0.tgz", + "integrity": "sha512-Dhxzh5HZuiHQhbvTW9AMetFfBHDMYpo23Uo9btPXgdYP+3T5S+p+jgNy7spra+veYhBP2dCSgxR/i2Y02h5/6w==", + "license": "MIT", + "engines": { + "node": ">=0.10.0" + } + }, "node_modules/vscode-jsonrpc": { "version": "8.2.0", "resolved": "https://registry.npmjs.org/vscode-jsonrpc/-/vscode-jsonrpc-8.2.0.tgz", diff --git a/libs/hexagent_demo/frontend/package.json b/libs/hexagent_demo/frontend/package.json index 3ce315d2..a33e4436 100644 --- a/libs/hexagent_demo/frontend/package.json +++ b/libs/hexagent_demo/frontend/package.json @@ -12,12 +12,14 @@ "dependencies": { "docx-preview": "^0.3.7", "echarts": "^6.0.0", + "i18next": "^25.10.10", "lucide-react": "^0.577.0", "mermaid": "^11.13.0", "pdfjs-dist": "^5.4.296", "pptx-viewer": "^0.1.0", "react": "^19.0.0", "react-dom": "^19.0.0", + "react-i18next": "^17.0.0", "react-markdown": "^9.0.1", "react-pdf": "^10.4.1", "react-syntax-highlighter": "^16.1.1", diff --git a/libs/hexagent_demo/frontend/src/App.tsx b/libs/hexagent_demo/frontend/src/App.tsx index 3da8d60b..6e40130e 100644 --- a/libs/hexagent_demo/frontend/src/App.tsx +++ b/libs/hexagent_demo/frontend/src/App.tsx @@ -1,4 +1,5 @@ import { useReducer, useEffect, useCallback, useRef, useState } from "react"; +import i18n from "./i18n"; import { AppContext, initialState, reducer } from "./store"; import { listConversations, createConversation, createWarmSession, deleteWarmSession, sendMessage, subscribeToStream, getServerConfig, getVMStatus, type ServerConfig } from "./api"; import { useSettings } from "./hooks/useSettings"; @@ -86,6 +87,10 @@ function App() { loadedConfig = cfg; dispatch({ type: "SET_SERVER_CONFIG", payload: cfg }); if (cfg.models.length === 0) setSetupNeeded(true); + // Sync language from backend config if it differs from local + if (cfg.language && cfg.language !== settings.language) { + setSettings((prev) => ({ ...prev, language: cfg.language })); + } }) .catch(() => {}); Promise.all([convP, cfgP]).then(() => { @@ -202,7 +207,7 @@ function App() { warmSessionPromiseRef.current = p; p.catch(() => { dispatch({ type: "SHOW_NOTIFICATION", payload: { - message: "Session setup failed. You can still send messages.", + message: i18n.t("misc:sessionSetupFailed"), type: "info", }}); }) @@ -418,7 +423,7 @@ function App() { doSendMessage(conv.id, content, options?.attachments); } catch { dispatch({ type: "REQUEST_END" }); - dispatch({ type: "SHOW_NOTIFICATION", payload: { message: "Failed to create conversation", type: "error" } }); + dispatch({ type: "SHOW_NOTIFICATION", payload: { message: i18n.t("misc:failedToCreateConversation"), type: "error" } }); } }, [dispatch, state.activeConversationId, state.isRequestPending, state.streamingByConversation, state.selectedModelId, state.selectedMode, state.warmSessionId, doSendMessage] diff --git a/libs/hexagent_demo/frontend/src/api.ts b/libs/hexagent_demo/frontend/src/api.ts index 6bc4dc43..3f68238b 100644 --- a/libs/hexagent_demo/frontend/src/api.ts +++ b/libs/hexagent_demo/frontend/src/api.ts @@ -359,13 +359,14 @@ export interface ServerConfig { tools: ToolsConfig; sandbox: SandboxConfig; mcp_servers: McpServerEntry[]; + language: string; } export async function getServerConfig(): Promise { const res = await fetch(`${API_BASE}/api/config`); if (!res.ok) throw new Error(`Failed to get config: ${res.statusText}`); const data = await res.json(); - return { agents: [], tools: { search_provider: "", search_api_key: "", fetch_provider: "jina", fetch_api_key: "" }, sandbox: { e2b_api_key: "", chat_enabled: false }, mcp_servers: [], ...data }; + return { agents: [], tools: { search_provider: "", search_api_key: "", fetch_provider: "jina", fetch_api_key: "" }, sandbox: { e2b_api_key: "", chat_enabled: false }, mcp_servers: [], language: "en", ...data }; } export async function updateServerConfig(config: ServerConfig): Promise { diff --git a/libs/hexagent_demo/frontend/src/components/ChatArea.tsx b/libs/hexagent_demo/frontend/src/components/ChatArea.tsx index 81144cdf..5da9fb81 100644 --- a/libs/hexagent_demo/frontend/src/components/ChatArea.tsx +++ b/libs/hexagent_demo/frontend/src/components/ChatArea.tsx @@ -1,5 +1,6 @@ import { useState, useCallback, useRef, useEffect, useMemo } from "react"; import { PanelRight } from "lucide-react"; +import { useTranslation } from "react-i18next"; import { useAppContext } from "../store"; import { getVMStatus } from "../api"; import WelcomeScreen from "./WelcomeScreen"; @@ -18,6 +19,7 @@ interface ChatAreaProps { } export default function ChatArea({ conversation, onSendMessage, onOpenSettings, rightPanel }: ChatAreaProps) { + const { t } = useTranslation("chat"); const { state, dispatch } = useAppContext(); const [editingTitle, setEditingTitle] = useState(false); const chatAreaRef = useRef(null); @@ -155,9 +157,9 @@ export default function ChatArea({ conversation, onSendMessage, onOpenSettings, onClick={() => handleModeChange(mode)} type="button" > - {mode === "chat" ? "Chat" : "Cowork"} + {t(`mode.${mode}`)} - {mode === "chat" ? "Chat" : "Cowork"} + {t(`mode.${mode}`)} {isMac ? "⇧⌘" : "Ctrl+Shift+"}{idx + 1} @@ -170,7 +172,7 @@ export default function ChatArea({ conversation, onSendMessage, onOpenSettings, diff --git a/libs/hexagent_demo/frontend/src/components/ChatInput.tsx b/libs/hexagent_demo/frontend/src/components/ChatInput.tsx index 088c68c8..8296f754 100644 --- a/libs/hexagent_demo/frontend/src/components/ChatInput.tsx +++ b/libs/hexagent_demo/frontend/src/components/ChatInput.tsx @@ -1,5 +1,6 @@ import { useState, useCallback, useRef, useEffect } from "react"; import { Paperclip, ArrowUp, ArrowDown, X, FileText, Loader2, CircleAlert } from "lucide-react"; +import { useTranslation } from "react-i18next"; import { useAppContext } from "../store"; import { uploadChatFile, deleteChatFile } from "../api"; import { useFileDrop } from "../hooks/useFileDrop"; @@ -37,6 +38,7 @@ function shouldShowScrollButton(container: HTMLElement, inputContainer: HTMLElem } export default function ChatInput({ conversationId, onSend, scrollContainerRef, onOpenSettings }: ChatInputProps) { + const { t } = useTranslation("chat"); const { state, dispatch } = useAppContext(); const noModels = !state.serverConfig?.models?.length; const missingE2bKey = state.selectedMode === "chat" && !state.serverConfig?.sandbox?.e2b_api_key; @@ -152,7 +154,7 @@ export default function ChatInput({ conversationId, onSend, scrollContainerRef, // Check for name collision against existing pending files const collision = pendingFilesRef.current.some((f) => f.name === file.name && f.status !== "failed"); if (collision) { - const error = `"${file.name}" already attached. Rename the file and try again.`; + const error = t("alreadyAttached", { filename: file.name }); setPendingFiles((prev) => [...prev, { id, name: file.name, status: "failed" as const, error }]); dispatch({ type: "SHOW_NOTIFICATION", payload: { message: error, type: "error" } }); return; @@ -167,13 +169,13 @@ export default function ChatInput({ conversationId, onSend, scrollContainerRef, ); }) .catch((err) => { - const message = err instanceof Error ? err.message : "Upload failed"; + const message = err instanceof Error ? err.message : t("uploadFailed"); setPendingFiles((prev) => prev.map((f) => f.id === id ? { ...f, status: "failed" as const, error: message } : f) ); dispatch({ type: "SHOW_NOTIFICATION", - payload: { message: `Failed to upload ${file.name}: ${message}`, type: "error" }, + payload: { message: t("failedToUpload", { filename: file.name, message }), type: "error" }, }); }); }, [conversationId, dispatch]); @@ -231,7 +233,7 @@ export default function ChatInput({ conversationId, onSend, scrollContainerRef, return (

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+----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/WorkSans-Regular.ttf b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/WorkSans-Regular.ttf new file mode 100644 index 0000000000000000000000000000000000000000..d24586cc0336949d49a1c2bf3fb3b306c47b431e GIT binary patch literal 188916 zcmdqK2Yi&p)(1Rochh@;0AZ65l2F2Kl1-tfYyt!l2oPE*=?SEf0tD$GVnbBy4HO&L zXcoZU1r-a54HdkKC>BH%Me_Y;o@Yw{%YEN_zwiBh+25J|%$%7yGjrz5nF*nUkN_Bh zkh~mw?)aW#ZG^Dl2z@SZY~lDhKDlEEz3p2e{S4`6jh~P?;j15fXHi5U-;8(gjV1LF6~2?~e55hSK`Vk2d?362ehC;~PzlEv*6XT^mfuv{wj8 z>Cx0&*;He^;$o!tL3-2UwBzDO#Fg+8+R;J$VG~0rcp3$ob9=U!)q? 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(https://github.com/cyrealtype/Lora-Cyrillic), with Reserved Font Name "Lora". + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/Lora-Regular.ttf b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/Lora-Regular.ttf new file mode 100644 index 0000000000000000000000000000000000000000..dc751db00dc171fc19737d9da800d7a583bb2c6d GIT binary patch literal 133888 zcmcGX2YgjU`uAt%+!R7+=?M@*2)(7!1SFMS1O!1uLI^b^7!oNeB25%fL{?qbRbGh}G?(1WwL1atoo_q~dy7EbFqx&1^E$P^-U!Gyx;)3C3Ldlc8u z2_>_}?^^cK5+P1*5i%itVsYWPW^2FMg8LZUJ50nPbgZY0`>x!lOq^OV^XUWghC?nF zqSn5WvZBJDF0R=uM2#Lo1fQN-ICGkHm-rR`4e*~-S~#_M{*>3|k~#9^`Egp=^orxF zF5N9eI(#%NpH^NxZDR1!h4>H0f53T+3)*&6scgrH*G1tfDec`?H(kai6 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b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/InstrumentSans-OFL.txt new file mode 100644 index 00000000..247d8d3a --- /dev/null +++ b/libs/hexagent_demo/backend/skills/public/frontend-dev/canvas-fonts/InstrumentSans-OFL.txt @@ -0,0 +1,93 @@ +Copyright 2022 The Instrument Sans Project Authors (https://github.com/Instrument/instrument-sans) + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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and is also available with a FAQ at: +https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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+https://openfontlicense.org + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. 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