AI-assisted repo analysis for turning rough prototypes into clear, documented, publishable GitHub projects.
Project description
repo-signal
AI-native repository intelligence for structured reasoning systems.
repo-signal turns local repository state into clear analysis reports and
high-signal AI context exports. It helps you turn messy, undocumented
prototypes into clear, publishable GitHub projects.
Install
After PyPI publish (v0.2.0 target):
pipx install repo-signal
Current local development install:
git clone https://github.com/MCamner/repo-signal.git
cd repo-signal
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[ai]"
pipx install repo-signal will replace the dev install once the package is
published to PyPI. See PyPI publishing guide.
Try this in 60 seconds
# Get a high-level overview
repo-signal analyze
# Fast status report and next commit suggestion
repo-signal inspect
# Machine-readable status for integrations
repo-signal inspect --json
# Full readiness diagnosis
repo-signal doctor
# Check public-readiness signals
repo-signal publish-checklist .
Command Surface
repo-signal
├── analyze # Front-door orientation
├── inspect # Fast status and next commit
├── inspect --json # Machine-readable inspect.v1 contract
├── doctor # Full readiness diagnosis
├── publish-checklist # Public signal quality gate
├── repoaware # AI context export
└── demo # Generate example reports
See the Command Surface, Command Reference, and Roadmap for full details.
Screenshots
Examples
- Doctor Report (Markdown)
- Doctor Report (JSON)
- Analyze Report
- Inspect Report
- Inspect JSON (inspect.v1)
- RepoAware Review
Generate your own local demo reports:
repo-signal demo --generate
Deep Documentation
- Integrations — How mqlaunch, mq-mcp, mq-hal, and Bridget consume
inspect.v1 - RepoAware — High-signal AI context ranking and export
- Semantic Memory — Uploading symbol maps to vector stores
- Publish Checklist — CI quality gates and portfolio checks
- Command Reference — Detailed CLI usage and flags
- Roadmap — Release direction, integration plan, and readiness checklist
- Generated Examples — How examples are generated and verified before release
- Packaging — PyPI / pipx readiness plan and packaging smoke tests
- TestPyPI — Safe dry-run path before real PyPI publishing
- Trusted Publishing — TestPyPI Trusted Publisher setup values and safety rules
- PyPI — Real PyPI publishing guide and Trusted Publisher values
- Inspect Schema — Machine-readable contract for
inspect --json - Doctor Schema — Machine-readable contract for
doctor --json - Repo Structure — Best practices for project layout
Planned features
Not started:
- safe patch suggestions
- positioning report
Partially implemented:
- GitHub Pages detection
- project type detection
- script/tool discovery
- wiki suggestion generator
- roadmap suggestion generator
Author
Mattias Camner
Infrastructure / Platform Architect
Builder of command surfaces, endpoint readiness prototypes, and structured
workflow systems.
License
MIT
Project details
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