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Contributing to SkillOpt

Thank you for your interest in contributing to SkillOpt! This guide covers how to get started.

Development Setup

git clone https://github.com/microsoft/SkillOpt.git
cd SkillOpt
pip install -e ".[dev]"

Ways to Contribute

🐛 Bug Reports

Open an issue with:

  • Steps to reproduce
  • Expected vs actual behavior
  • Config file used (sanitize API keys)
  • Python version and OS

🔧 New Benchmark

See Add a New Benchmark for the implementation guide.

Checklist:

  • Data loader in skillopt/envs/<benchmark>/loader.py
  • Environment adapter in skillopt/envs/<benchmark>/env.py
  • Config file in configs/<benchmark>/default.yaml
  • Registration in skillopt/envs/__init__.py
  • Documentation page in docs/

🤖 New Model Backend

See Add a New Model Backend for the implementation guide.

Checklist:

  • Backend in skillopt/model/<backend>.py
  • Registration in skillopt/model/__init__.py
  • API key entry in .env.example
  • Documentation update

📝 Documentation

Documentation is built with MkDocs Material:

pip install -e ".[docs]"
mkdocs serve  # Preview at http://localhost:8000

Code Style

  • Follow existing patterns in the codebase
  • Use type hints for function signatures
  • Keep docstrings concise

Pull Request Process

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/my-benchmark
  3. Make your changes
  4. Test with an existing benchmark config
  5. Submit a PR with a clear description

License

By contributing, you agree that your contributions will be licensed under the MIT License.