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Contributing

Thanks for helping make automated hiring fairer and more transparent.

Ground rules

  • Contributions are under Apache 2.0 (LICENSE / NOTICE).
  • Never commit real candidate data. Use app/services/seed_data.py (synthetic, deterministic). Demographic fields are audit-only signals.
  • Keep the method defensible: if you change scoring or attribution, update docs/01-methodology.md and add/adjust tests.

Dev setup

pip install -r requirements.txt
pytest -q
python -m app.services.pipeline_demo

Good first issues

  • A kernel/tree SHAP explainer for a non-linear reference model.
  • Impact-ratio (four-fifths rule) reporting on top of the bias score.
  • An adapter that ingests a real ATS's decision payload.
  • Rendering the Mermaid diagrams to committed SVG/PNG.

Pull requests

  1. Add/adjust a test for any behavioural change (pytest -q must stay green).
  2. Note which endpoint or method your change touches.