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Shay f9dc1cd71b docs: add domain boundary READMEs for governance anchors
2026-07-03 12:05:56 -07:00
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__init__.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00
params.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00
README.md docs: add domain boundary READMEs for governance anchors 2026-07-03 12:05:56 -07:00
replay.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00
report.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00
tune.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00

README.md

Calibration Package

calibration/ is the deterministic operator-parameter replay and tuning package. It explores bounded CalibrationParams candidates against eval cases and emits before/after metrics for review.

It is not the ADR-0175 reliability ledger and it does not grant serving licenses. Serving discipline is owned by core.reliability_gate; Workbench reads that evidence through workbench/calibration.py without re-running lanes or mutating license state.

This boundary is intentional:

  • calibration/params.py, calibration/replay.py, calibration/tune.py, and calibration/report.py support deterministic parameter audits.
  • workbench/calibration.py projects committed practice and serving artifacts into a read-only UI/API surface.