SkillOpt/docs/contributing.md

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>/dataloader.py
• Scored rollout implementation in skillopt/envs/<benchmark>/rollout.py
• Per-item predictions/<id>/conversation.json artifacts for shared reflection
• Environment adapter in skillopt/envs/<benchmark>/adapter.py
• Config file in configs/<benchmark>/default.yaml
• Lazy registration in scripts/train.py and scripts/eval_only.py
• Focused tests and an optional seed skill referenced by env.skill_init
• Documentation update

🤖 New Model Backend

See Add a New Model Backend for the implementation guide.

Checklist:

• Function-based backend module in skillopt/model/<name>_backend.py
• Alias and default model in skillopt/model/common.py
• Optimizer/target whitelist entries in skillopt/model/backend_config.py
• Dispatch, token tracking, and setter forwarding in skillopt/model/__init__.py
• YAML/CLI wiring when the backend exposes structured config fields
• Focused routing, configuration, tool-call, and token-accounting tests
• .env.example and backend/configuration reference updates

📝 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 switch -c feature/my-benchmark
3. Make your changes
4. Run focused tests, the full test suite, and mkdocs build --strict when docs change
5. Submit a PR with a clear description

License

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