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Deterministic CLI that audits a Git repository and generates actionable documentation

Project description

RepoScope AI

PyPI Python License GitHub Actions GitHub stars CLI GitHub Action

RepoScope AI is a fast, deterministic CLI + GitHub Action that audits a Git repository and generates clear, actionable documentation — so you can understand any codebase in minutes, not hours.

It is designed for developers, contributors, freelancers, and maintainers who need to answer one question quickly:

“What am I looking at, and where should I start?”


🚨 The Problem

Opening an unfamiliar repository usually means wasting time figuring out:

  • Where is the entry point?
  • How is the project structured?
  • Which files are risky or too large?
  • Where can I safely make changes?
  • What should a new contributor know first?

Most repositories do not document these answers.


✅ The Solution

RepoScope analyzes a repository (local path or GitHub URL) and generates a small set of opinionated, human‑readable reports:

  • ARCHITECTURE.md — high‑level project structure and layout
  • RISKS.md — large files, missing tests, structural smells
  • ONBOARDING.md — guidance for new contributors
  • SUMMARY.md / SUMMARY.json — concise, shareable snapshot

All outputs are:

  • Deterministic by default
  • Versionable (plain Markdown / JSON)
  • Designed to be read by humans, not dashboards

👥 Who This Is For

  • Contributors — get context before opening a PR
  • Freelancers / consultants — audit a repo quickly and surface risk areas
  • New team members — know where to start and what to avoid
  • Maintainers — document repo shape and obvious smells automatically

If you’ve ever said “I need 30 minutes just to understand this repo”, this tool is for you.


📦 Installation

pip install reposcope-ai

Development install (editable):

pip install -e .

Install dev dependencies (tests):

pip install -e ".[dev]"

⚡ 30‑Second Repo Audit

Analyze a GitHub repository:

reposcope analyze https://github.com/user/repo

Analyze a local repository:

reposcope analyze .

Generated output:

.reposcope/
├── ARCHITECTURE.md
├── RISKS.md
├── ONBOARDING.md
├── SUMMARY.md
└── SUMMARY.json

🧠 Optional AI Explanations (Opt‑In)

RepoScope supports an AI explanations mode that adds explanations only to existing findings.

set REPOSCOPE_OPENAI_API_KEY=YOUR_KEY
reposcope analyze . --ai

AI design rules (important):

  • AI never discovers new issues
  • AI receives structured findings only
  • All AI text is clearly labeled as AI‑assisted explanation
  • If AI fails, RepoScope silently falls back to non‑AI output

AI is disabled by default.


🤖 GitHub Action (PR Integration)

RepoScope ships with a first‑class GitHub Action.

Create .github/workflows/reposcope.yml:

name: RepoScope

on:
  pull_request:
  workflow_dispatch:

permissions:
  contents: read
  pull-requests: write

jobs:
  analyze:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: Siggmond/reposcope-ai@v0.1.0
        with:
          post-comment: "true"
          github-token: ${{ secrets.GITHUB_TOKEN }}

The workflow:

  • Runs RepoScope on the repo
  • Uploads .reposcope/ as artifacts
  • Optionally comments top risks on the PR (opt‑in)

🏷️ One‑Shot Badge

[![RepoScope](https://img.shields.io/badge/RepoScope-Analyzed-blue)](https://github.com/OWNER/REPO/actions)

📄 Example Output

Excerpt from RISKS.md:

## God files (very high line count)
- src/core/big_file.py (1203 lines)

⚠️ Limitations (Honest)

  • Analysis is heuristic, not static analysis
  • Circular import detection is best‑effort
  • Build/run instructions are inferred and may be incomplete
  • Very large repos may take longer depending on file count

🔐 Trust & Safety

  • Deterministic output by default
  • AI is optional and clearly labeled
  • No hallucinated findings
  • No black‑box scoring

📜 License

MIT License


If you maintain repositories, review pull requests, or onboard developers, RepoScope AI is built to save you time.

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