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Contributing

Contributions are welcome. agentstats keeps its dependency list short (numpy, scipy, pandas, tabulate) and its claims honest.

What fits here

  • Loaders for other agent benchmarks
  • Additional variance, significance or minimum-runs methods
  • Worked examples on public run data
  • Bug fixes, clearer docs, faster code

Ground rules

  1. No new dependencies without an issue first. The current set is declared in pyproject.toml.
  2. Tests for behavior changes. python3 -m pytest tests/ -q must stay green.
  3. Deterministic. Seed everything.
  4. Honest numbers. If a method does not change the conclusion on the bundled example, say so in the PR.
  5. Real data needs a license. New bundled examples must come from public datasets with a stated license (the current one is ASSERT-KTH, CC-BY-4.0).

How to contribute

  1. Fork the repo and create a branch from main.
  2. Make your change with tests.
  3. Run the full suite: python3 -m pytest tests/ -q.
  4. Open a pull request describing what changed and the before/after numbers.