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/responsible-ai-assessment

Gap-assess an AI system or program against a responsible-AI / governance framework — NIST AI RMF, ISO/IEC 42001, EU AI Act, OECD principles — covering governance, transparency, accountability, human oversight, documentation, and monitoring, then produce a prioritized roadmap.

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$ npx -y skills add jassics/awesome-claude-security --skill responsible-ai-assessment --agent claude-code

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Gap-assess an AI system or program against a responsible-AI / governance framework — NIST AI RMF, ISO/IEC 42001, EU AI Act, OECD principles — covering governance, transparency, accountability, human oversight, documentation, and monitoring, then produce a prioritized roadmap.

SKILL.md

responsible-ai-assessment.SKILL.md
name: responsible-ai-assessment
description: >-
  Gap-assess an AI system or program against a responsible-AI / governance
  framework — NIST AI RMF, ISO/IEC 42001, EU AI Act, OECD principles — covering
  governance, transparency, accountability, human oversight, documentation, and
  monitoring, then produce a prioritized roadmap. Use for AI governance, audit
  readiness, or compliance gap analysis.

Goal

A governance gap analysis: where the system/program stands against the chosen framework(s), the gaps, and a prioritized roadmap to close them.

Steps

1. **Pick the framework(s)** for the context:

  • **NIST AI RMF** — lifecycle functions: Govern, Map, Measure, Manage.
  • **EU AI Act** — first classify the risk tier (unacceptable / high / limited /

minimal); high-risk triggers specific obligations.

  • **ISO/IEC 42001** — AI management system controls (org governance).
  • **OECD principles** — values-level checkpoints.

(See `harm-modeling/reference.md` for the framework map.) 2. **Assess each control/function**: governance & accountability (who owns AI risk), risk mapping (intended use, harms — reuse `harm-modeling`), measurement (evals, bias, monitoring — reuse `safety-evaluation`, `bias-fairness-assessment`), transparency (model/data cards, user disclosures), human oversight, data governance, incident response, and ongoing monitoring/drift. 3. **Score each** (e.g. absent / partial / met) with evidence. 4. **Prioritize the roadmap** by risk (and regulatory deadline, for EU AI Act high-risk), with owners.

Output

A gap-analysis table: framework area · requirement · status · evidence · gap · priority · owner, plus a phased roadmap. Use `security-reporting` for the report and an executive summary for leadership; this feeds a CISO/CTO or `ai-safety-engineer` program view.

Notes

Governance ties the technical safety work (harm modeling, evals, guardrails, fairness) to organizational accountability and regulation. Start by classifying the use case's risk tier — it determines how much rigor each control needs. Verify current framework versions and any jurisdiction-specific obligations.

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