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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>/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

Code Review Guidelines

See the code review checklist for common considerations that may help reviewers and contributors. Apply the items relevant to the scope and risk of each change.

License

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