DevSquad — Multi-Role AI Task Orchestrator

🎯 把「单个 AI 助手」升级成「7 人 AI 专业团队」
One task → Multi-role AI collaboration → One conclusion | V4.3.0 Pre-release (V4.3.0 candidate — pending user approval)

📖 太长不看？先看这个（30 秒）

DevSquad 是什么？

DevSquad 是一个多角色 AI 任务编排器。当你提交一个任务时，它不再是单个 AI 回答，而是让 7 个专业角色（架构师、安全专家、测试员、开发者等）并行协作，最后给出经过多方审核的结论。

传统 AI:  你 ──→ ChatGPT ──→ 一个回答（可能不全面）
DevSquad:  你 ──→ DevSquad ──→ [架构师+安全+测试+开发...] ──→ 多维度共识结论

核心优势（对比单 AI）

痛点	传统单 AI	DevSquad
视角单一	只有通用视角	7 个专业角色并行审视 ✅
质量不可控	可能遗漏安全问题	多维度交叉验证 + 共识机制 ✅
无审计追踪	不知道回答依据什么	完整审计链 + SHA256 完整性校验 ✅
复杂任务崩溃	长任务容易丢失上下文	Checkpoint 断点续传 + 工作流引擎 ✅

最快上手（5 分钟）

# 安装
pip install devsquad

# 运行 - 让 AI 团队帮你设计认证系统
devsquad run "设计一个安全的用户认证系统" --roles architect,security,tester,coder

# 输出结构化报告：
# ✅ 架构师建议：采用 JWT + Refresh Token 方案...
# ✅ 安全专家审查：需防范 CSRF、XSS、SQL 注入...
# ✅ 测试策略：单元测试覆盖率达 90%+...
# ✅ 开发实现：提供完整代码框架...
# 📊 共识结论：方案可行，风险可控...

什么时候用 DevSquad？

你的需求	推荐方案
简单问答（"Python 怎么写 for 循环？"）	直接用 ChatGPT/Claude ✅
代码片段审查	DevSquad 单角色模式 ✅
复杂系统设计（需要多视角）	DevSquad 多角色协作 🎯
生产环境自动化流程	DevSquad + REST API + Dashboard 🎯

📚 想深入了解？ → 完整快速入门指南 | 185+ 模块详细参考

🔍 点击展开：完整功能介绍与架构详解

🚀 V4.3.0 (V4.3.0 candidate): 安全债清理 + 上游精细化升级 + 测试金字塔达标

DevSquad V4.3.0 是 V4.3.0 的预发布候选版本，整合技术债跟踪、pickle→JSON 迁移、上游 TraeMultiAgentSkill v2.6-v2.8 精细化启发三方面输入，按 7-Role 共识推进：

V4.3.0 P0 — 安全债清理（必做）

P0-1 pickle→JSON 迁移阶段 1: 删除 2 处 dead code + fallback 安全收紧（require_password 校验）
P0-2 技术债持续监控: todo_drift_monitor.py 自动扫描 TODO/FIXME/HACK + pre-commit 阻塞 + CI lint 集成

V4.3.0 P1 — 上游精细化升级（重要）

P1-1 Ponytail lite/full 双模式: 8 核心红线（lite）+ 16 红线（full），# ponytail: 债务收集 + [REQ-XXX] 需求追踪
P1-4 LoopKernel RollbackStrategy: D1-D6 失败精准回退 + 独立硬上限（默认 3）+ 累计上下文传递
P1-5 UIUX 子项审计: 4 维度 20 子项注册表 + PASS/WARN/FAIL/NOT_IMPLEMENTED 审计
P1-6 Dashboard V4.3.0 面板: Ponytail 模式 / Loop 回退 / Plugin 事件 / 技术债状态可视化

V4.3.0 P2 — 收尾（一般）

P2-1 pickle fallback 完全移除（用户确认从 V4.3.1 并入 V4.3.0）: allow_pickle_fallback 参数移除，serialization_format="pickle" 构造时拒绝

V4.2+ / V4.3+ Roadmap 已落地项

P2-1 PrototypeSkill: 快速原型生成验证假设
P2-2 TeachSkill: 8 主题新用户引导课程
P2-4 pre-commit hooks: 依赖版本锁检查
P2-UI-1 CLI 命令词表: 基于 impeccable 23 命令词表对齐
P2-UI-2 Live Browser 模式: 实时 UI 审查迭代闭环
P2-UI-3 Meta-skills 分层: 8 子技能 6 层架构

测试金字塔达标

Contract 测试: 3.06% → 5.0%（目标 ≥5% ✅）
Integration 测试: 8.84% → 15.2%（目标 ≥15% ✅）
总测试数: 5250+ → 7681（+2431 测试）

历史特性（V4.0.0-V4.2.1）

V4.0.0 P1-1 Loop Engineering: Discovery → Handoff → Verification → Persistence → Scheduling 五步闭环
V4.0.0 P1-2 UI/UX 巡检: 4 维度审计 + PIL 像素 diff 视觉回归
V4.0.0 P2-1 Adversarial 验证: 红队攻击 + 蓝队防御 + 裁判仲裁
V4.0.0 P2-2 DAG 可视化: Mermaid / JSON / DOT 三格式
V4.0.0 P3-1 Autonomous: plan → dev → verify → fix 4 阶段自主迭代
V4.0.0 P3-2 插件热加载: 3 加载路径 + 路径穿越三层防护 + reload 回滚

7681 tests passing。

⚡ Quick Start (5 Ways to Use DevSquad)

Method 1: CLI (Recommended for Beginners)

# Interactive setup wizard (1-2 minutes)
python scripts/cli.py init

# Then start collaborating!
devsquad dispatch -t "your task description"

Method 2: Web Dashboard (Recommended for Teams)

# Start Streamlit dashboard with authentication
streamlit run scripts/dashboard.py

# Open http://localhost:8501
# Login with default account, then change password immediately.
# Username: admin   Password: admin123   (change in production)

Method 3: REST API (Recommended for Integration)

# Install dependencies
pip install fastapi uvicorn

# Start API server
uvicorn scripts.api_server:app --host 0.0.0.0 --port 8000 --reload

# Access Swagger UI: http://localhost:8000/docs
# Access ReDoc:      http://localhost:8000/redoc

Method 4: Python API (Recommended for Developers)

from scripts.collaboration.dispatcher import MultiAgentDispatcher

dispatcher = MultiAgentDispatcher()
result = dispatcher.dispatch(
    task="Optimize database query performance",
    roles=["architect", "security", "tester"],
)
print(result.report)
print(result.consensus)

Method 5: One-Click Startup Script (V3.9.2+)

# One-click startup — 4 phases: env check → DB init → frontend build → service start
./scripts/start.sh

# Launch Streamlit dashboard instead of API server
./scripts/start.sh --dashboard

# Override API port
DEVSQUAD_API_PORT=9000 ./scripts/start.sh

# Show help
./scripts/start.sh --help

start.sh is the unified entry point introduced in V3.9.2 (P0-2). It validates the environment, initializes the database, builds the frontend, and starts the service in one command. Use requirements.lock alongside it for reproducible builds (pip install -r requirements.lock). V4.1.0 adds Loop Engineering, UI/UX 巡检, Adversarial 验证, DAG 可视化, Autonomous, and 插件热加载.

👥 7 Core Roles

Role	CLI ID	Aliases	Weight	Best For
🏗️ Architect	`arch`	`architect`	1.5	System design, tech stack, performance/security architecture
📋 Product Manager	`pm`	`product-manager`	1.2	Requirements, user stories, acceptance criteria
🛡️ Security Expert	`sec`	`security`	1.1	Threat modeling, vulnerability audit, compliance
🧪 Tester	`test`	`tester`, `qa`	1.0	Test strategy, quality assurance, edge cases
💻 Coder	`coder`	`solo-coder`, `dev`	1.0	Implementation, code review, performance optimization
🔧 DevOps	`infra`	`devops`	1.0	CI/CD, containerization, monitoring, infrastructure
🎨 UI Designer	`ui`	`ui-designer`	0.9	UX flow, interaction design, accessibility

Auto-match: If no roles specified, the dispatcher automatically matches based on task keywords.

🏗️ Five Capability Domains (Architecture Overview)

DevSquad's 235 modules are organized into 5 capability domains, each solving a specific problem:

🎯 Domain 1: Task Orchestration Engine (Core)

让 7 个角色高效协作的「指挥中心」

Module	Purpose	When to Use
MultiAgentDispatcher	Unified dispatch entry point	All tasks automatically
Coordinator	Task decomposition + role assignment	Complex tasks needing breakdown
Scratchpad	Shared blackboard for real-time info exchange	Inter-role collaboration
ConsensusEngine	Weighted voting + veto + escalation mechanism	Security/architecture disputes
BatchScheduler	Parallel/sequential hybrid scheduling	Resource-constrained environments

Core Workflow:

User Task → [InputValidator] → [RoleMatcher] → [Coordinator Orchestration]
           → [ThreadPoolExecutor Parallel Workers] → [Scratchpad Real-time Sharing]
           → [ConsensusEngine] → [ReportFormatter] → [Structured Report]

🛡️ Domain 2: Quality Assurance System

防止 AI 「偷懒」或「幻觉」

Module	Purpose	When to Use
InputValidator	Security validation + 40-pattern detection (14 forbidden + 21 prompt injection + 5 suspicious)	Production environments
VerificationGate	Mandatory evidence requirements + 7 Red Flags detection	Critical decision scenarios
AntiRationalizationEngine	Per-role excuse→rebuttal tables to prevent quality shortcuts	High quality requirements
TestQualityGuard	Test quality audit (API validation / anti-pattern detection / dimension coverage)	Pre-release verification
PermissionGuard	4-level safety gate (PLAN/DEFAULT/AUTO/BYPASS)	Security-sensitive tasks

⚡ Domain 3: Performance & Reliability

让系统更快、更稳定、更省钱

Module	Purpose	When to Use
LLMCache	TTL-based LRU cache with disk persistence (60-80% cost reduction)	High-frequency usage
LLMRetry	Exponential backoff + circuit breaker + multi-backend fallback	Unstable networks
FeedbackControlLoop	Closed-loop feedback control with automatic iteration until quality threshold met	High quality output pursuit
ExecutionGuard	Real-time abort guard (timeout/output/keywords) for safe execution	Long-running tasks
FallbackBackend	Automatic backend failover with health monitoring	High availability requirements

📊 Domain 4: Observability & Governance

知道系统在做什么、做得怎么样

Module	Purpose	When to Use
PerformanceMonitor	P95/P99 response time, CPU/memory tracking, bottleneck detection	Performance tuning
UsageTracker	Token/cost usage tracking and reporting	Cost control
AuditLogger	SHA256 integrity operation logs with CSV/JSON export (Preview)	Compliance auditing
RBAC Engine	15+ fine-grained permissions, 5 roles (SUPER_ADMIN/ADMIN/OPERATOR/ANALYST/VIEWER) (Preview)	Enterprise access control
Multi-Tenancy Manager	3 isolation levels (strict/moderate/shared), tenant-scoped resources (Preview)	Multi-tenant SaaS
Sensitive Data Masker	PII detection and masking (email/phone/ID card/credit card), configurable rules (Preview)	Data compliance
HistoryManager	SQLite time-series storage: metrics snapshots, alert history, API logs	Retrospective analysis

🔌 Domain 5: Integration & Extension

融入你的现有工具链

Module	Purpose	When to Use
CLI	Command-line interface with lifecycle commands	Daily developer usage
REST API (FastAPI)	10+ endpoints with OpenAPI/Swagger docs	Microservice integration
Dashboard (Streamlit)	Interactive web dashboard with authentication	Operations team visualization
MCP Protocol	Integration with TRAE/Claude Code/Cursor	AI Agent ecosystem
Docker Support	Multi-stage build for production deployment	Containerized environments
GitHub Actions CI	Python 3.10-3.11 matrix testing	CI/CD pipelines

🔬 Cybernetics Enhancement Modules (V3.6.1)

非侵入式包装设计 — 可选开关，零修改现有核心逻辑

The 5 cybernetic modules work independently or together without modifying existing core logic:

User Task
    ↓
[SimilarTaskRecommender] ← Optional: suggest roles from history
    ↓
[AdaptiveRoleSelector]   ← Optional: optimize role selection
    ↓
[MultiAgentDispatcher]
    ↓
[FeedbackControlLoop]     ← Wrap dispatcher for auto-iteration
    ↓ [each worker step]
[ExecutionGuard]          ← Guard each worker execution
    ↓
[PerformanceFingerprint]  ← Record after dispatch completes

1️⃣ FeedbackControlLoop (反馈闭环控制器)

Closed-loop feedback control with automatic iteration until quality threshold met
Configurable quality gate (quality_gate) and maximum iterations
Lightweight quality assessment (no LLM calls), supports dry-run mode

2️⃣ ExecutionGuard (执行守护者)

Real-time execution monitoring with 4 abort conditions: timeout, output size, token count, critical keywords
Lightweight checks (<1ms), zero external dependencies
Dynamically configurable thresholds

3️⃣ PerformanceFingerprint (性能指纹系统)

Unified execution fingerprint recording (fuses 4 data sources)
Pure Python TF-IDF implementation (no sklearn/numpy), supports English/Chinese mixed content
JSON persistence to .devsquad_data/fingerprints/, graceful cold-start degradation

4️⃣ SimilarTaskRecommender (相似任务推荐器)

TF-IDF-based task similarity search with historical success configuration recommendations
Intelligent role combination recommendation, intent prediction, execution time estimation
Confidence scoring (high/medium/low), graceful cold-start degradation

5️⃣ AdaptiveRoleSelector (自适应角色选择器)

Three-tier selection strategy based on historical success rates
Configurable minimum success rate and maximum role count
Supports manual statistics updates and comprehensive role effectiveness reporting

Recommended usage (progressive adoption):

from scripts.collaboration import (
    MultiAgentDispatcher, FeedbackControlLoop,
    ExecutionGuard, PerformanceFingerprint
)

dispatcher = MultiAgentDispatcher()
guard = ExecutionGuard()
fingerprint = PerformanceFingerprint()

# Option 1: Full cybernetics stack
loop = FeedbackControlLoop(dispatcher, quality_gate=0.7)
result = loop.run("Your task here")

# Option 2: Guard only (minimal adoption)
result = dispatcher.dispatch("Your task")
for w in result.worker_results:
    abort, reason = guard.check_abort(w.output, w.duration)
    if abort:
        print(f"Aborted: {reason}")

# Option 3: Learning only
fingerprint.record_execution("task", result, result.timing, result.matched_roles)
similar = fingerprint.find_similar("new task", top_k=3)

All modules are optional switches — DevSquad works perfectly without them.

🏗️ Architecture Overview (Layered Design)

┌─────────────────────────────────────────────────────────────┐
│                    User Access Layer                         │
│  ┌──────────────┐ ┌──────────────┐ ┌──────────────┐        │
│  │ Streamlit    │ │ FastAPI REST │ │ CLI/Notebook │        │
│  │ Dashboard    │ │ API Server   │ │ (Existing)   │        │
│  │ (Auth+HTTPS) │ │ (Swagger)    │ │              │        │
│  └──────┬───────┘ └──────┬───────┘ └──────────────┘        │
└─────────┼───────────────┼───────────────────────────────────┘
          │               │
          ▼               ▼
┌─────────────────────────────────────────────────────────────┐
│                   Business Logic Layer                      │
│  ┌─────────────┐ ┌─────────────┐           │
│  │AuthManager  │ │HistoryMgr   │           │
│  │(RBAC Auth)  │ │(SQLite TSDB)│           │
│  └─────────────┘ └─────────────┘           │
│  ┌─────────────────────────────────────────────┐            │
│  │     LifecycleProtocol (11-Phase Engine)       │            │
│  │     UnifiedGateEngine + CheckpointManager     │            │
│  └─────────────────────────────────────────────┘            │
└─────────────────────────┬───────────────────────────────────┘
                          │
                          ▼
┌─────────────────────────────────────────────────────────────┐
│                    Data Persistence Layer                    │
│  ┌────────────┐ ┌────────────┐ ┌────────────────────────┐  │
│  │ SQLite DB  │ │ YAML Config│ │ Checkpoint Files       │  │
│  │ (History)  │ │ (Deploy)   │ │ (Lifecycle State)      │  │
│  └────────────┘ └────────────┘ └────────────────────────┘  │
└─────────────────────────────────────────────────────────────┘

🧩 Layered Sub-Skill Architecture (V3.6.0)

DevSquad provides 6 atomic sub-skills that can be used independently or together. Each sub-skill is a thin wrapper (~50 lines) importing existing core modules — no duplicated logic.

skills/
├── dispatch/       → DispatchSkill — MultiAgentDispatcher (7-role orchestration)
├── intent/         → IntentSkill   — IntentWorkflowMapper (6 intents × 3 languages)
├── review/         → ReviewSkill   — FiveAxisConsensusEngine (5-axis code review)
├── security/       → SecuritySkill — InputValidator + OperationClassifier + PermissionGuard
├── test/           → TestSkill     — TestQualityGuard + test strategy generation
└── retrospective/  → RetroSkill    — RetrospectiveEngine + pattern extraction

Sub-Skill Quick Reference

Skill	Core Method	Wraps	Mock Mode
`dispatch`	`run(task, roles, mode)`	MultiAgentDispatcher	✅
`intent`	`detect(text, lang)`	IntentWorkflowMapper	✅
`review`	`review(code)`	FiveAxisConsensusEngine	✅
`security`	`scan_input(text)`	InputValidator + OpClassifier	✅
`test`	`generate_strategy(module)`	TestQualityGuard	✅
`retrospective`	`run_retrospective(results)`	RetrospectiveEngine	✅

Usage Examples

# Direct import (recommended for single skill)
from skills.dispatch.handler import DispatchSkill
result = DispatchSkill().run("Fix login bug", roles=["coder", "tester"])

# Via registry (dynamic discovery)
from skills import get_skill, list_skills
print(list_skills())  # ['dispatch', 'intent', 'review', 'security', 'test', 'retrospective']
skill = get_skill("security")
result = skill.scan_input("DROP TABLE users; --")

All sub-skills work without any API key in Mock mode.

📋 Plan C Architecture (Core Engine)

Unified Lifecycle Architecture - Resolves CLI 6 commands vs 11-phase lifecycle:

CLI View Layer (6 commands)          Core Engine (11 phases)
┌─────────────────────┐            ┌──────────────────────────┐
│ spec → P1, P2       │───View ──→│ P1: Requirements         │
│ plan → P7           │   Mapping │ P2: Architecture         │
│ build → P8          │            │ P3: Technical Design     │
│ test → P9           │            │ ...                      │
│ review → P8,P6      │            │ P10: Deployment          │
│ ship → P10          │            │ P11: Operations          │
└─────────────────────┘            └──────────────────────────┘
        ↓                                    ↓
  UnifiedGateEngine                   CheckpointManager
  (Phase + Worker gates)              (Lifecycle state persistence)

Core Components:

✅ LifecycleProtocol - Abstract interface for unified lifecycle management
✅ UnifiedGateEngine - Integrates VerificationGate + Phase transition gates
✅ FullLifecycleAdapter - Complete 11-phase lifecycle with dependency resolution
✅ Enhanced CheckpointManager - Auto save/restore lifecycle state across sessions

📦 Installation

Prerequisites

Python 3.10+ (3.10, 3.11 supported, tested in CI)
pip or pipenv for package management

Option A: PyPI Install (Recommended)

# Install from PyPI — zero setup, ready to use
pip install devsquad

# With optional dependencies
pip install "devsquad[api]"    # FastAPI + Streamlit dashboard
pip install "devsquad[all]"    # All optional features

Option B: Git Clone + Local Install

git clone https://github.com/lulin70/DevSquad.git
cd DevSquad

# Install core package (minimal dependencies)
pip install -e .

# Ready to use!
devsquad dispatch -t "Design user authentication system"

Verify Installation

# Check version
devsquad --version
# Expected: devsquad 4.3.0

# Run tests
pytest tests/ -v --tb=short
# Expected: 7681 passed

⚙️ Configuration

Create .devsquad.yaml in your project root:

quality_control:
  enabled: true
  strict_mode: true
  min_quality_score: 85

llm:
  backend: auto
  base_url: ""  # Set via DEVSQUAD_OPENAI_BASE_URL env var
  model: ""     # Set via DEVSQUAD_OPENAI_MODEL env var
  timeout: 120

Or use environment variables (higher priority):

# Default: auto tries real backends first, then falls back to mock
export DEVSQUAD_LLM_BACKEND=auto
export DEVSQUAD_OPENAI_BASE_URL=https://api.openai.com/v1
export DEVSQUAD_OPENAI_MODEL=gpt-4
export DEVSQUAD_OPENAI_API_KEY=sk-...

Environment Variables Reference:

Variable	Purpose	Default
`DEVSQUAD_LLM_BACKEND`	Default backend type (auto\|mock\|trae\|openai\|anthropic\|fallback)	`auto`
`DEVSQUAD_OPENAI_API_KEY`	OpenAI/MOKA AI API key	None
`DEVSQUAD_OPENAI_BASE_URL`	OpenAI-compatible base URL	None
`DEVSQUAD_OPENAI_MODEL`	OpenAI model name	`gpt-4`
`DEVSQUAD_ANTHROPIC_API_KEY`	Anthropic API key	None
`DEVSQUAD_ANTHROPIC_BASE_URL`	Anthropic-compatible base URL	None
`DEVSQUAD_ANTHROPIC_MODEL`	Anthropic model name	`claude-sonnet-4-20250514`
`DEVSQUAD_LOG_LEVEL`	Logging level	`WARNING`

🧪 Testing

Quick Smoke Test (< 30 seconds)

python3 scripts/cli.py --version       # Expected: DevSquad 4.1.0
python3 scripts/cli.py status          # Expected: System ready
python3 scripts/cli.py roles           # Expected: 7 core roles listed

Full Test Suite

# Run all tests (7681 tests passing)
python3 -m pytest tests/ -q --tb=line

# With coverage report
python3 -m pytest tests/ --cov=scripts --cov-report=term-missing

Test Layering Strategy

Priority	Scope	Examples	Count
P0	Quality Framework Core	AntiRationalization, VerificationGate, IntentWorkflowMapper, AuthManager	~200
P1	Enhancement Modules	FiveAxisConsensus, OperationClassifier, OutputSlicer	~150
P1+	Cybernetics (V3.6.6)	FeedbackControlLoop, ExecutionGuard, PerformanceFingerprint, etc.	110
P2	Integration & E2E	Full lifecycle dispatch, cross-module integration	~200
P3	Unit per Module	Core dispatcher, RoleMapping, MCEAdapter, LLM backends	~400+

Total: 7681 CI tests / 266 e2e (7681 collected)

Run by priority:

# P0 only (critical path, < 10s)
python3 -m pytest tests/ -k "anti_ratif or verification or intent_workflow or auth" -q

# P0 + P1 (quality + enhancement, < 30s)
python3 -m pytest tests/ -k "anti_ratif or verification or intent or auth or five_axis or operation" -q

# Full suite
python3 -m pytest tests/ -q --tb=line

📚 Documentation

Document	Description	Language
QUICKSTART.md	⭐ 30 秒快速入门指南（推荐新用户）	中文
SKILL.md	完整技能手册 + 185+ 模块参考	EN/CN/JP
GUIDE.md	完全用户指南	中文
INSTALL.md	安装指南 (Unix + Windows)	EN/CN
EXAMPLES.md	实际使用示例	EN
CHANGELOG.md	版本历史记录	EN
README-CN.md	中文说明	中文
README-JP.md	日本語説明	日本語
docs/PRD.md	产品需求文档	中文
docs/ARCHITECTURE.md	技术架构文档	中文
docs/planning/V43_ROADMAP_PROPOSAL.md	V4.3 统一推进方案 v1.2（7-Role 共识达成）	中文
docs/prd/V4.3.0_PRD.md	V4.3.0 PRD（需求/用户故事/验收标准）	中文
docs/architecture/V4.3.0_ARCHITECTURE.md	V4.3.0 架构设计（模块边界/接口契约/依赖图）	中文
docs/testing/V4.3.0_TEST_PLAN.md	V4.3.0 测试方案（测试金字塔/E2E/真实用户模拟）	中文

🗺️ Roadmap

V4.3.0（进行中 — 7-Role 共识达成，文档先行）

版本策略: V4.3.0 预发布（全部代码+文档+E2E 验证）→ 用户确认 → V4.3.0 正式版

整合三方面输入:

技术债持续治理（todo_drift_monitor + CI 阻塞）
pickle→JSON 迁移（dead code 删除 + fallback 安全收紧 + 移除）
上游 TraeMultiAgentSkill v2.6-v2.8 精细化启发（Ponytail 双模式 / LoopKernel 回退 / UIUX 审计 / Dashboard 可视化）

V4.3.0 范围（9 项）:

ID	名称	优先级
P0-1	pickle dead code 删除 + fallback 安全收紧	P0
P0-2	`todo_drift_monitor.py` + CI 阻塞 + PR template	P0
P1-1	Ponytail lite/full 双模式 + DebtCollector + RequirementTracer	P1
P1-4	LoopKernel RollbackStrategy + 独立硬上限	P1
P1-5	UIUXAnalyzer 子项审计 + 按需补全	P1
P1-6	Dashboard 状态可视化	P1
P2-1	pickle fallback 移除	P2
P2-2	Autonomous SmartConfirmation 文档补全	P2
P2-4	V4.3.0 发布文档同步	P2

7-Role 共识: 7/7 APPROVE_WITH_CONCERNS，按 10 项调整修订后达成共识。详见 V43_ROADMAP_PROPOSAL.md v1.2。

项目生命周期: 按 11-Phase 模型推进（P1 需求 → P2 架构 → P3 技术设计 → P7 测试计划 → P8 实施 → P9 测试执行 → P10 部署发布）

测试金字塔保障: unit ≥60% / integration 15-25% / e2e ≤10% / contract 5-10% / smoke ≤5%

🤝 Contributing

Fork the repository
Create feature branch (git checkout -b feature/amazing-feature)
Commit changes (git commit -m 'Add amazing feature')
Push to branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

⭐ 如果 DevSquad 对你有帮助，请给个 Star！⭐
让更多开发者享受到「AI 团队协作」的力量

🙏 Acknowledgments
Inspired by TraeMultiAgentSkill upstream project
Built with ❤️ by the DevSquad team

Last updated: 2026-07-24 | Version: V4.2.1 (V4.3.0 in progress — see Roadmap)

Name		Name	Last commit message	Last commit date
Latest commit History 214 Commits
.github		.github
config		config
docs		docs
examples		examples
helm/devsquad		helm/devsquad
scripts		scripts
skills		skills
templates/concerns		templates/concerns
tests		tests
.devsquad.yaml		.devsquad.yaml
.dockerignore		.dockerignore
.editorconfig		.editorconfig
.env.example		.env.example
.gitignore		.gitignore
.gitleaks.toml		.gitleaks.toml
.pre-commit-config.yaml		.pre-commit-config.yaml
CHANGELOG-CN.md		CHANGELOG-CN.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
COMPARISON.md		COMPARISON.md
CONTRIBUTING.md		CONTRIBUTING.md
Dockerfile		Dockerfile
EXAMPLES.md		EXAMPLES.md
GUIDE.md		GUIDE.md
INSTALL.md		INSTALL.md
LICENSE		LICENSE
QUICKSTART.md		QUICKSTART.md
README-CN.md		README-CN.md
README-JP.md		README-JP.md
README.md		README.md
RELEASE_CHECKLIST.md		RELEASE_CHECKLIST.md
SKILL.md		SKILL.md
VERSION		VERSION
conftest.py		conftest.py
docker-compose.redis.yml		docker-compose.redis.yml
docker-compose.yml		docker-compose.yml
pyproject.toml		pyproject.toml
requirements-dev.lock		requirements-dev.lock
requirements-dev.txt		requirements-dev.txt
requirements.lock		requirements.lock
requirements.txt		requirements.txt
skill-manifest.yaml		skill-manifest.yaml

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