Metadata-Version: 2.5
Name: ai-vibecheck
Version: 0.1.4
Summary: Audit how much of a GitHub repo was written by AI and check vibe-coding risk.
Author: Daniyar N
License: MIT
Keywords: ai-code,claude-code,copilot,gemini,github,vibecheck,vibecoding
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Quality Assurance
Requires-Python: >=3.10
Requires-Dist: anthropic>=1.8.0
Requires-Dist: google-genai>=2.25.0
Requires-Dist: openai>=3.19.2
Requires-Dist: pydantic>=2.10.0
Requires-Dist: python-dotenv>=1.2.3
Requires-Dist: requests>=2.34.2
Requires-Dist: rich>=15.0.0
Requires-Dist: typesafe-sdk>=0.7.2
Description-Content-Type: text/markdown

# vibecheck 🔮

A little terminal tool that checks how much of a GitHub repo was actually written by AI.

It digs through commit messages, co-author tags, and project setup files to tell you:
1. **How much AI code is in here?** (0% to 100%)
2. **What kind of project is this?** (e.g. AI-built with human tests, a weekend prototype, or 100% hand-crafted)
3. **Is it tested and reviewed, or just "vibe-coded"?**

---

## Quickstart

You don't need to install anything! Run directly with [`uvx`](https://docs.astral.sh/uv/):

```bash
uvx ai-vibecheck <github-repo>
```

Or install via `pip`:

```bash
pip install ai-vibecheck
vibecheck <github-repo>
```

### Examples:

```bash
# Check any repo (e.g. open-metadata has ~60% AI co-authored commits)
vibecheck open-metadata/OpenMetadata

# Check an open-source project
vibecheck pallets/flask

# Or paste the full URL
vibecheck https://github.com/torvalds/linux
```

---

## 🌟 Cool Features

### 1. ⚔️ Side-by-Side Comparison
Compare two repositories head-to-head in a split-screen table:

```bash
vibecheck compare open-metadata/OpenMetadata pallets/flask
```

### 2. 🔀 Pull Request Vibe Check
Audit a specific Pull Request to see if it was written by an AI coding agent:

```bash
vibecheck pallets/flask --pr 5000
```

### 3. 🏆 Organization Leaderboard
Rank an entire GitHub organization's active repos by AI adoption:

```bash
# Rank top repos in an organization
vibecheck org pallets --limit 5
vibecheck org encode --limit 5
```

---

## Plain-English Categories

* 🤖 **AI-Built, Human-Tested:** Lots of AI code (>75%), but backed by real tests, CI/CD, and code reviews.
* 🚀 **Pure Vibe-Code:** Built fast by prompting an AI in 1 or 2 big commits. No tests, just vibes.
* 🍝 **AI Spaghetti:** Lots of erratic commits like *"fix bug"*, *"try again"*, showing someone pasted terminal errors into an LLM until it compiled.
* 🛠️ **100% Hand-Crafted:** Classic, hand-written software with human commit discipline and zero AI footprints.
* 🤝 **Human + AI Tag Team:** A healthy human codebase where engineers use AI assistants for parts of the work.

---

## How It Works Under the Hood

1. **GitHub login:** Automatically uses your existing GitHub CLI session (`gh auth`). Higher rate limits and access to private repos you can view. Falls back to public HTTP if not logged in.
2. **AI analysis:** Runs via your local Gemini CLI session by default (no API keys required).
3. **Forensic detection:**
   - Finds agent steering files (`CLAUDE.md`, `.cursorrules`, `.agents`).
   - Parses git trailers (`Generated with Claude Code`, `gemini-code-assist[bot]`, `copilot[bot]`).
   - Automatically filters out automated release bumps so metrics reflect real feature engineering.

---

## Options

```bash
# Switch to TypeSafe Jev (ultra-fast, requires TYPESAFE_API_KEY or OPENROUTER_API_KEY)
vibecheck <repo> -p jev

# Switch to Claude
vibecheck <repo> -p claude

# Switch to OpenAI
vibecheck <repo> -p openai -m gpt-4o

# Run tests
uv run pytest

# Check code quality
uv run ruff check .
```
