compliance-readiness
AI Compliance Readiness Assessment — evaluate how prepared an organization is for AI governance regulations (EU AI Act, NIST AI RMF, HHS mandates, state bar AI rules). Scores readiness across 8 dimensions and generates an action plan. Use when assessing AI compliance gaps, preparing for audits, or building a governance roadmap.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/compliance-readiness/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How compliance-readiness Compares
| Feature / Agent | compliance-readiness | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
AI Compliance Readiness Assessment — evaluate how prepared an organization is for AI governance regulations (EU AI Act, NIST AI RMF, HHS mandates, state bar AI rules). Scores readiness across 8 dimensions and generates an action plan. Use when assessing AI compliance gaps, preparing for audits, or building a governance roadmap.
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AI Compliance Readiness Assessment Evaluate organizational readiness for AI governance regulations and generate an actionable compliance roadmap. ## When to Use - Assessing AI compliance posture before an audit - Preparing for EU AI Act (Aug 2026), HHS AI mandates, NIST AI RMF - Building a governance roadmap for AI deployments - Evaluating risk exposure from current AI usage ## How to Use When asked to assess AI compliance readiness, gather these inputs: ### Required Inputs 1. **Industry** (legal, healthcare, financial-services, insurance, construction, manufacturing, government, other) 2. **Company size** (employees or revenue range) 3. **AI systems in use** (list: chatbots, document review, fraud detection, hiring tools, customer service, analytics, other) 4. **Jurisdictions** (US-only, EU-exposed, both, global) ### Optional Inputs - Current governance framework (if any) - Upcoming audit dates - Existing compliance certifications (SOC2, ISO 27001, HIPAA, etc.) - Number of AI vendors/tools in use ## Assessment Framework Score each dimension 1-5 (1=no controls, 5=mature): ### 8 Dimensions 1. **Risk Classification** — Have you categorized AI systems by risk level per EU AI Act / NIST? 2. **Documentation** — Technical docs, model cards, data lineage for each AI system? 3. **Human Oversight** — Defined human-in-the-loop processes for high-risk decisions? 4. **Bias & Fairness** — Regular bias audits, fairness metrics, disparate impact testing? 5. **Data Governance** — Training data provenance, consent, retention, and deletion policies? 6. **Incident Response** — AI-specific incident playbook, reporting procedures, rollback plans? 7. **Vendor Management** — AI vendor risk assessments, contractual AI governance requirements? 8. **Audit Trail** — Logging, explainability, decision traceability for AI-assisted outputs? ### Scoring - **35-40**: Compliance-ready — minor gaps to address - **25-34**: Partially prepared — significant work needed in specific areas - **15-24**: High risk — major gaps across multiple dimensions - **8-14**: Critical — immediate action required before any regulatory review ## Output Format Generate a report with: 1. **Executive Summary** — Overall score, risk level, top 3 gaps 2. **Dimension Scores** — Table with score, evidence, and gap description per dimension 3. **Regulatory Exposure** — Which regulations apply and key deadlines: - EU AI Act: Aug 2, 2026 (high-risk system requirements) - HHS AI Transparency: April 3, 2026 (healthcare) - NIST AI RMF: Ongoing (federal contractors + best practice) - State bar AI rules: Varies (legal industry)