Mean It

Guided writing companion that interviews the user, preserves source material, and produces a provenance trace so the final artifact can be traced back to the user's own words.

Mean It is a Next.js app for human-centered writing workflows. Instead of jumping straight to generation, it guides the user through choosing a moment, picking a guide style, interviewing for detail, assembling a spine, rendering the final piece, and sharing a trace of how each line was grounded.

Contents

• At A Glance
• Screenshot Gallery
• Writing Workflow
• Architecture
• Feature Map
• Tech Stack
• Repository Map
• Run Locally
• Verification
• Configuration
• Status
• License

At A Glance

Area	Details
Product	Guided writing and provenance workspace
Users	People turning a personal moment into a grounded written artifact
Core value	Interview first, draft later, and keep a shareable trace of source-to-output grounding
Frontend	Next.js, React, Tailwind
Core modules	guide loader, interview middleware, spine validation, provenance matching, share encoding
Tests	Vitest suite
Design docs	DESIGN.md, docs/techstack.md, wireframes and high-fidelity design files

Screenshot Gallery

Image	Caption
	Moment intake screen where the user chooses emotional intent, recipient, and artifact type.
	Guide selection step with distinct writing guide personas and custom guide entry point.
	Answered interview state with user source material captured for later spine and provenance steps.
	Spine selection screen where the app lifts verbatim user phrases and proposes a three-movement structure.
	Final verified artifact view with the readable letter, 100 percent byline meter, and export/share actions.
	Provenance hover state showing the exact question and user answer that produced a line in the final artifact.
	Export modal for local poster download with caption and byline options.

Writing Workflow

flowchart LR
  A["User chooses a moment"] --> B["Guide style is selected"]
  B --> C["Interview collects concrete details"]
  C --> D["Spine validator checks structure"]
  D --> E["Drafting screen assembles artifact"]
  E --> F["Provenance matcher links lines to source material"]
  F --> G["Share trace or download"]

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Architecture

flowchart TD
  UI["Next.js app screens"] --> STORE["Local session store"]
  UI --> GUIDES["Guide loader"]
  UI --> INTERVIEW["Interview engine"]
  INTERVIEW --> PROMPTS["Prompt templates"]
  INTERVIEW --> AUDIT["Audit middleware"]
  AUDIT --> PROV["Provenance matcher"]
  UI --> MEDIA["Photo, audio, and video helpers"]
  UI --> SHARE["Share encode/decode"]
  SHARE --> TRACE["Traceable output"]
  UI --> MODALS["Save, download, share trace, start over"]

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Feature Map

Feature	Evidence in repo
App shell	components/App.tsx, components/Chrome.tsx
Moment picker	components/screens/PickMoment.tsx
Guide selection	components/screens/GuidePicker.tsx, lib/guides/
Interview flow	components/screens/Interview.tsx, lib/interview/
Spine validation	components/screens/Spine.tsx, lib/spine/validate.ts
Render/download	components/screens/Render.tsx, components/modals/Download.tsx
Provenance	lib/provenance/match.ts, components/modals/ShareTrace.tsx
Media helpers	lib/audio/, lib/video/, lib/images/

Tech Stack

Layer	Technology
App	Next.js, React, TypeScript
Styling	Tailwind CSS
Testing	Vitest
State	Local store modules
Media	Audio transcription/TTS helpers, video curation helpers
Docs	Wireframes, design docs, tech stack notes

Repository Map

components/   Screens, modals, mascots, app chrome
lib/          Interview, provenance, media, guides, sharing, env
prompts/      System and guide prompt templates
docs/         Design docs, wireframes, screenshots

Run Locally

cp .env.example .env.local
npm install
npm run dev

Open http://localhost:3000.

Verification

Local results from the screenshot/docs pass:

Command	Result
npm run typecheck	Passed
npm test	Passed, 254 tests

Configuration

Keep provider keys in .env.local, which is gitignored.

ANTHROPIC_API_KEY=
OPENAI_API_KEY=

Status

The project has a strong product thesis, real screenshots, passing tests, and good design docs. The next step is a short demo video or animated walkthrough showing the full interview-to-trace workflow.

License

MIT. See LICENSE.