decision-threshold-policy
gmanch94/claude-code-aidlc-template/.claude/skills/decision-threshold-policy/SKILL.md
Turns calibrated model scores into operational decisions — operating-point selection from a confusion-cost matrix (expected-cost minimization, not default 0.5), threshold-vs-prevalence and prevalence-drift shift, ROC-vs-PR operating-point choice by imbalance (Youden's J / F-beta / cost curves), multi-tier auto-approve/review/auto-reject bands, and an abstention / reject-option that routes low-confidence cases to humans sized against review capacity. Emits a threshold-policy design doc. Use when asked "what threshold should I use", "is 0.5 right", how to set an operating point, how to band scores into auto/review/reject, when to send a case to human review, or why a tuned threshold broke after prevalence drifted. Defers calibrated-probability production to `/model-calibration`, deployment wiring to `/model-deployment`, drift-detection math to `/model-drift`.
No licence file, so all rights are reserved — read it at the source. Read it on GitHub.
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CLAUDE.md
Skill
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