Overview
- Skill Key
- 1kalin/compliance-readiness
- Author
- 1kalin
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/1kalin/compliance-readiness
- Latest Commit SHA
- aefebffd6447b67f7a0b65561b5c3dfbdfc0cfa3
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.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 compliance-readiness 技能。 若已安装,则直接安装 compliance-readiness 技能。
# 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 - **...
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