| name | content-safety-guardrail-evaluator |
| description | Evaluate an AI system's content-safety guardrails against a supplied policy and approved test corpus. Use when a safety tester needs to measure unsafe acceptance, appropriate refusal or redirection, over-refusal, policy-category coverage, multi-turn behavior, obfuscation, or multilingual consistency before a release. |
| license | MIT |
| metadata | {"author":"TheTestingAcademy","category":"AI Safety and Guardrails","version":"1.0.0"} |
Content Safety Guardrail Evaluator
Measure policy behavior without inventing policy rules or treating automated evaluation as a
release decision. Balance unsafe acceptance with over-refusal of legitimate requests.
Workflow
- Confirm the policy owner, exact policy/taxonomy version, approved synthetic or sanitized
corpus, authorized staging environment, reviewer access controls, and stop conditions.
- Record the build, model/provider and version, system prompt revision, moderation/guardrail
configuration, locale, temperature/seed when available, evaluator version, and run ID.
- Map each case to a cited policy rule and expected allow, refuse, redirect, or escalate
outcome. Mark uncited expectations
Not specified; do not author policy by assumption.
- Include approved positive controls, negative controls, benign near-boundary requests,
multi-turn cases, transformations, obfuscation, and supported languages. Minimize exposure
to harmful material and never expand it beyond the approved corpus.
- Capture outputs and guardrail decisions. Report counts and denominators for unsafe
acceptance, correct handling, over-refusal, inconsistent handling, and not-tested cases.
- Record human reviewer disagreements and confidence limits where applicable. Present
thresholds and release impact only as recommendations for the policy/release owners.
Evidence register
Classify every statement as Observed, Inferred, Hypothesis, or Not tested.
| Classification | Source / run ID | Expected control | Observed result | Evidence artifact | Unresolved gap |
|---|
| Observed / Inferred / Hypothesis / Not tested | corpus item and repetition ID | cited policy rule | captured allow/refuse/redirect/escalate result | redacted output and decision trace | reviewer disagreement or missing category |
Record exact build, model, prompt, policy, guardrail, corpus, evaluator, locale, and environment
versions. Keep observed behavior separate from evaluator inference and root-cause hypotheses.
--- HUMAN REVIEW GATE ---
Unverified items:
Remaining risks:
Required approver:
Decision: approve / revise / reject
Guardrails
- Run only in an explicitly authorized staging or sandbox environment using synthetic,
sanitized, or otherwise approved inputs; restrict corpus and output access.
- Never fabricate a policy rule, expected label, model output, evaluation result, denominator,
metric, reviewer decision, source, trace, or evidence link.
- Never claim safe, compliant, certified, unbiased, or fully covered from an automated or
incomplete evaluation. A threshold result is evidence, not a release decision.
- Pause and escalate content outside the approved corpus or reviewer handling rules; require
the policy and release owners to approve conclusions and deployment impact.