openbench-privacy-preservin.../AGENTS.md

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OpenBench SWARM Agent Guidelines

  • Architecture: MVP focusing on a privacy-preserving KPI share/aggregation pipeline with offline-first storage.
  • Tech Stack: Python 3.8+, standard library, no heavy dependencies for MVP; packaging via setuptools; tests with pytest.
  • Testing: pytest for unit tests; python3 -m build to verify packaging metadata and directory structure.
  • Running tests: bash test.sh in the repo root.
  • Contribution Rules: one feature per patch; keep changes minimal; avoid touching unrelated areas.
  • Data Model: KPIRecord with revenue, COGS, inventory_turns, lead_time, CAC, LTV; anonymous sharing via anon_id.
  • Privacy: aggregate with optional Laplace noise (simple, deterministic in tests when anonymize=False).
  • How to Extend: add new adapters, contracts, or playbooks under respective namespaces; ensure tests cover new behavior.