Auto-generate AI agent context files. Keep them in sync with your code.
Your AI agents (Claude Code, Cursor, Copilot) read from AGENTS.md to understand your project. When your code changes, that file gets stale. Agents miss patterns, violate conventions, hallucinate.
Braxis solves this: one command generates four context files that stay in sync with your codebase.
Before Braxis:
Day 1: Agent reads stale AGENTS.md from 2 weeks ago Sees old directory structure Doesn't know about new error handling pattern Makes bad suggestions based on outdated info
After Braxis:
Every push: GitHub Actions runs Braxis Analyzes current codebase Regenerates AGENTS.md, CLAUDE.md, .cursorrules, .agentic-config.json Creates PR with updates Your agents always see current reality
- ✅ One Command - Generate all context files with
braxis generate - ✅ Zero Config - Works out of the box, no setup needed
- ✅ Auto-Score - Measure your project's AI agent readiness (0-100)
- ✅ Score History - Track improvements over time with trends & analytics
- ✅ LLM Recommendations - AI-powered suggestions using Claude API (optional)
- ✅ Multi-Language - Supports Python, JavaScript, TypeScript, Go, Rust, Java, and more
- ✅ CI/CD Ready - GitHub Actions workflow included
- ✅ Pre-commit Hooks - Validate before every commit
- ✅ Safe & Reliable - Input validation, atomic writes, comprehensive error handling
- ✅ Well-Tested - 30+ unit tests with 100% pass rate
- ✅ No Dependencies - Pure Python, zero external packages (LLM features optional)
- ✅ Production-Grade - Used in real projects, actively maintained
pip install braxis
pip install braxis[llm]
For LLM-powered recommendations:
export ANTHROPIC_API_KEY='sk-ant-...'
Get your API key: https://console.anthropic.com
cd /path/to/your/project
braxis generate
That's it. Braxis creates:
your-project/ ├── AGENTS.md (Universal agent instructions) ├── CLAUDE.md (Claude Code optimized) ├── .cursorrules (Cursor IDE rules) ├── .agentic-config.json (Machine-readable metadata) └── (your existing files)
cat AGENTS.md
git add AGENTS.md CLAUDE.md .cursorrules .agentic-config.json
git commit -m "chore: add AI agent context files"
git push
In Claude Code: Automatically reads CLAUDE.md
In Cursor: Copy .cursorrules into Cursor Settings → Rules
In any agent: Reads AGENTS.md (universal format)
Automatically regenerate context files on every push using GitHub Actions.
Braxis includes a ready-to-use workflow. Copy it to your repo:
mkdir -p .github/workflows
cp /path/to/braxis/.github/workflows/braxis-score.yml .github/workflows/
git add .github/workflows/braxis-score.yml
git commit -m "chore: add braxis auto-update workflow"
git push
Or manually create .github/workflows/braxis-score.yml:
name: Braxis Score Check
on:
push:
branches: [ main, develop ]
paths:
- '**.py'
- 'package.json'
- 'pyproject.toml'
- 'setup.py'
jobs:
score:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v4
with:
python-version: '3.11'
- run: pip install braxis
- run: braxis score
- run: braxis generate
- name: Create Pull Request for updates
uses: peter-evans/create-pull-request@v5
with:
commit-message: 'chore: regenerate braxis context files'
title: 'chore: update agent context files'
branch: braxis/auto-update
Result: Every push automatically regenerates context files and creates a PR if needed. ✨
Validate context files before every commit using pre-commit.
pip install pre-commit
pre-commit install
The hooks will run automatically on git commit.
Copy the example config to your project:
cp /path/to/braxis/.pre-commit-config.example.yaml .pre-commit-config.yaml
Then install:
pip install pre-commit
pre-commit install
Now braxis will validate your project before each commit! 🔐
Track your project's AI agent readiness score over time.
braxis history
braxis history --trends
Example output:
- 2026-10-01 - 65/100 (AI-Native)
- 2026-10-05 - 72/100 (AI-Native)
- 2026-10-10 - 78/100 (AI-Native-Plus)
Trend: 📈 +13 points
**Features:**
- Automatic score persistence on every `braxis score` run
- Project-specific tracking (stored in `~/.braxis/history/` )
- Trend indicators: 📈 (improving) 📉 (declining) ➡️ (stable)
- Configurable history limits
- Timestamps and tier information included
Get intelligent, actionable recommendations from Claude AI.
**Setup:**
pip install braxis[llm]
export ANTHROPIC_API_KEY='sk-ant-...'
**Usage:**
braxis recommendations
**Example output:**
1. Add Comprehensive Test Suite
Why it matters: Testing is the foundation of reliable code.
Current state: Only 7% testing coverage
How to implement:
- Start with pytest fixtures for common patterns
- Aim for 80%+ coverage on core modules
- Run: pytest --cov to measure progress
2. Implement Input Validation Framework
Why it matters: Validation prevents bugs and security issues
Current state: No systematic validation detected
How to implement:
- Use Pydantic for request validation
- Add schema validation to all API endpoints
- Example: from pydantic import BaseModel
[... more recommendations ...]
Features:
- Uses Claude Opus 5.5 for high-quality analysis
- 5-7 actionable recommendations per run
- Concrete implementation steps for each suggestion
- Focuses on improving Agent Readiness Score
- Gracefully handles missing API keys
- Optional dependency (braxis works without it)
Braxis welcomes contributions! Read CONTRIBUTING.md for:
- Setup instructions
- Development workflow
- Testing guidelines
- Code style guide
- PR process
Quick start:
git clone https://github.com/YOUR_USERNAME/braxis.git
cd braxis
python3 -m venv venv
source venv/bin/activate
pip install -e .
python3 -m unittest test_braxis -v
Create .agentic-config.json:
{
"name": "MyApp",
"description": "A production API service",
"exclude_patterns": [
"node_modules/**",
".venv/**",
"build/**"
],
"custom_conventions": {
"error_handling": "Always use try/except and log",
"async_patterns": "All I/O must be async",
"validation": "Use Pydantic models for inputs"
},
"critical_files": [
"src/main.py",
"src/api/routes.py",
"README.md"
]
}
AGENTS.md - Universal format read by any AI agent
CLAUDE.md - Optimized for Claude Code
.cursorrules - Rules for Cursor IDE
.agentic-config.json - Machine-readable metadata
Check how ready your codebase is for AI agents:
braxis score
Example output:
Breakdown:
Architecture 10/100 [██░░░░░░░░░░░░░░░░░░] Testing 7/100 [█░░░░░░░░░░░░░░░░░░] Dependencies 12/100 [██░░░░░░░░░░░░░░░░░] Conventions 10/100 [██░░░░░░░░░░░░░░░░░░] Entry Points 4/100 [░░░░░░░░░░░░░░░░░░░] Security 10/100 [██░░░░░░░░░░░░░░░░░░] Build 10/100 [██░░░░░░░░░░░░░░░░░░] Documentation 8/100 [█░░░░░░░░░░░░░░░░░░]
Tier: AI-Native
Detected: Languages: python Build System: Python (pip/setuptools) Test Frameworks: pytest, unittest Test Files: 1 Critical Files: 0
Recommendations:
- Increase test coverage
- Add input validation and security checks
| Score | Tier | Meaning |
|---|---|---|
| 90-100 | **Agent-Optimized** | Production-ready for AI agents |
| 80-89 | **AI-Native-Plus** | Excellent agent compatibility |
| 60-79 | **AI-Native** | Good agent support |
| 30-59 | **Agent-Aware** | Basic agent compatibility |
| 0-29 | **Not Ready** | Needs improvements |
- **Architecture** - Critical files, entry points, project structure
- **Testing** - Test coverage and test framework detection
- **Dependencies** - Build system and dependency management
- **Conventions** - Code patterns, error handling, type hints
- **Entry Points** - Main functions and executable files
- **Security** - Input validation, security checks, config management
- **Build** - Build files and dependency tracking
- **Documentation** - README and project documentation
python3 braxis.py score --path /path/to/project braxis --version
braxis score braxis score --path /path/to/project # Score a specific project
braxis generate braxis generate --path /path/to/project
braxis inspect braxis inspect --path /path/to/project
braxis validate braxis validate --path /path/to/project
braxis history braxis history --path /path/to/project braxis history --trends # Show trends with emoji indicators braxis history --path /path/to/project --trends
braxis recommendations braxis recommendations --path /path/to/project
Braxis is production-grade with enterprise-level quality standards:
- **Input Validation** - Validates project paths and file inputs with clear error messages
- **Atomic File Writing** - Uses temporary files and atomic operations to prevent partial writes
- **Error Handling** - Comprehensive error handling with informative feedback
- **Path Normalization** - Converts relative paths to absolute paths safely
- **Comprehensive Tests** - 30+ unit tests covering all major functionality
- **Test Coverage** - 100% pass rate across all test suites
- **Automated Testing** - GitHub Actions runs tests on every commit
- **Pre-commit Hooks** - Validates before every commit
- **Code Style** - Follows PEP 8 standards
- **Zero Dependencies** - No external packages required
python3 -m unittest test_braxis -v
python3 -m unittest test_braxis.TestValidateProjectPath -v
pip install coverage coverage run -m unittest test_braxis coverage report
**Status:** All 30 tests passing ✅
| Feature | Braxis | CursorRules | .cursorrules | Other Tools |
|---|---|---|---|---|
| **Auto-generates context** | ✅ Four formats | ❌ Manual | ❌ Manual | Varies |
| **Scores readiness** | ✅ 0-100 with 5 tiers | ❌ No | ❌ No | ❌ Limited |
| **Tracks history** | ✅ Over time with trends | ❌ No | ❌ No | ❌ No |
| **AI recommendations** | ✅ Claude-powered | ❌ No | ❌ No | ❌ Limited |
| **Multi-language** | ✅ 15+ languages | ❌ Limited | ❌ Limited | Varies |
| **CI/CD integration** | ✅ GitHub Actions ready | | | Varies |
| **Zero dependencies** | ✅ Core only | ✅ Yes | ✅ Yes | Varies |
| **Production-tested** | ✅ 30+ tests | | | Varies |
| **Atomic file ops** | ✅ Safe writes | ❌ No | ❌ No | ❌ No |
| **Active updates** | ✅ Latest Claude models | | | Varies |
**The difference:** Braxis goes beyond rules files. It continuously analyzes your codebase, scores your readiness, tracks progress, and provides AI-driven guidance—all automatically.
- Python 3.8+
- Zero external dependencies
- Works on macOS, Linux, Windows
- **Report Issues** -[GitHub Issues](https://github.com/jaykrishna316/braxis/issues)
- **Discussions** -[GitHub Discussions](https://github.com/jaykrishna316/braxis/discussions)
- **Contributing** - See[CONTRIBUTING.md](https://github.com/jaykrishna316/braxis/blob/main/CONTRIBUTING.md)
``` bash
$ braxis score
Agent Readiness: 78/100 (AI-Native-Plus)
bash
$ braxis score
Score: 45/100 (Agent-Aware)
$ braxis history --trends
📈 +28 points
bash
$ braxis score
$ braxis generate
bash
$ braxis recommendations
AI agents need current context to work effectively. Without it, they:
- ❌ Miss recent code patterns
- ❌ Violate project conventions
- ❌ Make outdated suggestions
- ❌ Waste your time with hallucinations
Braxis solves this automatically:
- Generates context files from real code analysis
- Scores your readiness for AI agents (0-100)
- Tracks improvements over time with trends
- Recommends actionable next steps via Claude AI
One command. Always in sync. Always improving. ✨
MIT - Free to use in personal and commercial projects
See LICENSE for details.
Upcoming features in development:
- 🚧 Custom scoring rules engine
- 🚧 Project comparison & benchmarking
- 🚧 Web dashboard for visualization
- 🚧 Score forecasting & predictions
- 🚧 Integration with more IDE platforms
Have a feature request? Open an issue
Braxis — Keep your agents aligned. Keep your code context current.
Continuously analyze. Automatically improve. Always sync. ✨
Made with ❤️ for AI-native development by developers, for developers.