spectr
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- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 5 GitHub stars
Code Fail
- spawnSync — Synchronous process spawning in bin/spectr.js
- os.homedir — User home directory access in bin/spectr.js
- process.env — Environment variable access in bin/spectr.js
- fs module — File system access in bin/spectr.js
- network request — Outbound network request in frontend/app/HomeClient.tsx
- network request — Outbound network request in frontend/app/admin/AdminTable.tsx
- process.env — Environment variable access in frontend/app/admin/page.tsx
- network request — Outbound network request in frontend/app/admin/page.tsx
- process.env — Environment variable access in frontend/app/api/admin/data/route.ts
- process.env — Environment variable access in frontend/app/api/admin/fulfill/route.ts
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- Permissions — No dangerous permissions requested
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See an app. Ship an app. — Turn a screen recording into a production-ready spec.md for Claude Code.
See an app. Ship an app.
Turn a screen recording of any iOS app into a production-ready spec.md — exact hex codes, exact font weights, every screen state.
Drop it into Claude Code and build the clone.
What it does
Spectr watches a screen recording the way a senior product engineer would, then writes down everything it sees in seven sections:
| Section | What it covers |
|---|---|
| App Overview | What the app is, who it serves, primary value prop |
| Navigation Architecture | Tab structure, modals, screen graph |
| Screen Specifications | Every screen visible, with layout, components, states |
| Component Library | Reusable UI pieces, props, states |
| Design System | Exact hex codes, font families/sizes/weights, spacing scale, radius/shadow tokens |
| Implementation Notes | Gotchas, edge cases, Expo / RN baseline assumptions |
| Claude Code Prompt | A ready-to-paste prompt to start building |
The output targets Expo SDK 54 / React Native / iPhone 15 baseline by default. Roughly 80–150 KB of structured markdown — big enough to be complete, small enough to fit in a Claude Code context window.
Quick start
Three ways to install. Pick one — they all share the same vision pipeline and write the same spec.
1. MCP server (recommended for Claude Code)
claude mcp add spectr -- uvx spectr-mcp
Then in any Claude Code conversation, drop an .mp4 and ask Claude to spec it. Runs on your Claude subscription — no API key required.
2. CLI
npx -y spectr-cli generate ./recording.mp4 --app "Duolingo"
Or install globally:
npm install -g spectr-cli
spectr generate ./recording.mp4 --app "Duolingo"
3. Claude Code skill
npx -y spectr-cli install-skill
Drops a SKILL.md into ~/.claude/skills/spectr/. Mention "spec it" or "use Spectr" in any Claude Code conversation with a recording attached and Claude picks up the skill automatically.
Requirements
- Node 18+ (for the CLI / skill installer)
- Python 3.10+ +
uv(for the MCP / pipeline) ffmpegonPATH—brew install ffmpegon macOS- Authenticated
claudeCLI orANTHROPIC_API_KEYin env
Spectr never asks for an API key directly. It uses the credentials already on your machine.
How it works
Screen recording (.mp4 / .mov)
│
▼
┌───────────────────────────────────────┐
│ 1. Frame extraction │
│ ffmpeg scene-change → pHash dedup │
│ → 20 unique frames │
└───────────────────────────────────────┘
│
▼
┌───────────────────────────────────────┐
│ 2. Vision analysis (parallel) │
│ • Screen documentation (Haiku) │
│ • Design token extraction (Haiku) │
└───────────────────────────────────────┘
│
▼
┌───────────────────────────────────────┐
│ 3. Spec generation (4 lanes parallel) │
│ 7 sections (Sonnet) │
│ → validate → assemble │
└───────────────────────────────────────┘
│
▼
spec.md (~80–150 KB)
Typical run: 5–10 minutes for a 30–60 second recording. Cost on your own Anthropic key: ~$0.60–$1.20 per spec at default settings (or $0 on a Claude Pro/Max subscription via the CLI).
The pipeline is deliberately frame-driven, not transcript-driven. Screen recordings have long static periods (loading, reading) — scene-change detection captures every meaningful UI transition while skipping the noise. Perceptual hashing then dedupes near-identical frames so the vision model only sees what's actually new.
Repository layout
spectr/
├── bin/spectr.js # Node CLI wrapper (npm/npx entry point)
├── spectr_mcp/ # Python MCP server + standalone CLI
│ ├── server.py # FastMCP stdio + streamable-http transports
│ ├── cli.py # spectr-cli generate <mp4>
│ └── pipeline.py # DB-free orchestrator (calls worker.local_worker)
├── worker/ # Vision pipeline + prompts
│ ├── local_worker.py # All processing logic
│ └── prompts/ # screen_analysis, design_tokens, legacy_spec
├── claude_skill/spectr/ # SKILL.md for Claude Code
├── mcp_server/ # Dockerfile for hosted streamable-http MCP
├── frontend/ # Next.js 14 app (powers spectr.to)
└── supabase/ # Schema + migrations for the hosted product
The worker pipeline is the heart of the project. Everything else — MCP, CLI, skill, web UI — is a different shape of the same vision passes.
Contributing
Issues and PRs welcome. A few principles to follow:
- Don't bypass
_resize_frame_for_api()— Claude's vision API rejects images larger than 2000px in multi-image batches. Every frame goes through the resizer. - Keep prompts in
worker/prompts/— never inline them inlocal_worker.py. - Preserve the dual Claude interface (
claude_text()/claude_vision()) — both CLI and SDK paths must work. - Spec sections are 7, in order. Changing the count or order is a coordinated change across
legacy_spec.py, assembly logic, and frontend rendering.
See open issues for ideas, or open one to propose changes.
License
MIT. Use it, fork it, ship from it.
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