{"id":53980,"plugin_id":"plugins_6ac95be4543c81918667980ea4f8dc05","kind":"skill","collection_source":"plugin_package","comparison_source":null,"observed_at":"2026-10-24T13:55:33.762Z","digest":"9c433575446d19bc2dfa9ec3c568faea514efb47ecf277c58175837de505affc","against":null,"payload":{"description":"Use when the user asks for a AI Governance Auditor review based on supplied evidence.","included_files":[],"name":"ai-governance-auditor","skill_md_contents":"---\nname: ai-governance-auditor\ndescription: Use when the user asks for a AI Governance Auditor review based on supplied evidence.\n---\n\n# AI Governance Auditor\n\nPerform an evidence-scoped review for the stated workflow. Produce a defensible\nworking report, not a certification, legal opinion, incident determination, or\nsecurity authorization.\n\n## Boundaries\n\n- Use only material supplied by the user or an explicitly identified authoritative source.\n- Preserve evidence pointers and distinguish verified, partially verified, unverified and contradicted evidence.\n- Never invent identifiers, clauses, controls, incidents, findings, approvals, owners, dates or outcomes.\n- Redact secrets, credentials, unnecessary personal identifiers and confidential operational details.\n- Keep documented/design gaps separate from implementation gaps and operating-effectiveness gaps.\n- If scope or authorization is missing, stop and request it before making a substantive conclusion.\n\n## Workflow\n\n1. State the assessment scope, evidence reviewed, evidence date, exclusions and limitations.\n2. Extract only explicit claims, requirements, records, approvals, timestamps, owners and results.\n3. Link each finding to a filename, section, page, record ID, timestamp or short quote.\n4. Separate positive evidence, document/design gaps, implementation gaps, operating-effectiveness gaps and mapping/evidence uncertainty.\n5. Assign a practical priority with a plain-language basis; do not present it as a formal certification or legal score.\n6. End with the smallest evidence requests and closure conditions.\n\n## Intended workflow\n\nReview the evidence behind AI governance claims across the system lifecycle.\n\n### What it helps with\n- Separate documented design from deployed controls.\n- Assess testing and monitoring records in their stated scope.\n- Map to supplied framework requirements without guessing identifiers.\n\n### What to provide\nAn AI system inventory, governance records, test results and the authoritative framework version.\n\n### Limits\nIt does not certify an AI system or make a legal determination.\n\n## Report format\n\n```markdown\n# AI Governance Auditor — Evidence-Scoped Review\n\n## Status\n- Overall status:\n- Scope:\n- Evidence reviewed:\n- Evidence date / freshness:\n- Exclusions and limitations:\n\n## Executive summary\n\n## Findings\n| ID | Category | Mapping or subject | Conclusion | Evidence pointer | Evidence quality | Priority | Closure evidence |\n|---|---|---|---|---|---|---|---|\n\n## Positive evidence\n\n## Uncertainty and blockers\n\n## Evidence request list\n\n## Action plan\n| Action | Owner | Target evidence | Dependency | Acceptance condition |\n|---|---|---|---|---|\n\n## Assessor notes\n```\n"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}