# Audit Verifier Reliability

> Use when deciding whether a verifier reward is trustworthy for optimization.

- Skill: `understudylabs/audit-verifier-reliability` (Agent Skill)
- Install (CLI): `npx skillmds@latest add understudylabs/audit-verifier-reliability`
- Raw SKILL.md: https://api.skillmd.com/api/skills/understudylabs/audit-verifier-reliability/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: understudylabs (https://skillmd.com/u/understudylabs)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/understudylabs/audit-verifier-reliability

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# Audit verifier reliability

Trust requires two independent, offline arms: deterministic adversarial probes
and replayed natural trajectories. The receipt is trusted only when both meet
the predeclared gate and carries source, verifier, and fixture SHA-256 bindings.

Never read holdout data, call providers, upload traces, include customer data,
or spend money in this audit. Natural evidence cannot override an adversarial
failure; missing natural coverage is `insufficient-evidence`.

Use `evaluateTrustGate` from `src/verifier-trust/`. Keep raw trajectories out of
receipts and retain the resulting hash-bound receipt with the calibration
artifact (`understudy.verifier_calibration.v1`).

## Safety Gates

- Operate only on already-approved local calibration summaries; never read a
  holdout, call a provider, upload trajectories, or include customer content.
- Require valid source-binding, verifier, and fixture SHA-256 values plus both
  natural and adversarial arms. Missing evidence is never trusted.
- Treat the receipt as verifier-calibration evidence, not model-quality or
  promotion evidence.

## Resolve CLI

No CLI command is required. Build the package and call `evaluateTrustGate` from
`dist/verifier-trust/index.js` in an offline script or test. Preserve only the
hash-bound receipt; keep raw probes in their approved local evidence store.