AI Compliance Skill
Reference Files
Load only what's needed based on the request type:
Frameworks
- - EU AI Act →
references/eu-ai-act.md — risk tiers, prohibited uses, obligations - ISO 42001 →
references/iso-42001.md — clauses, Annex A controls - NIST AI RMF →
references/nist-ai-rmf.md — GOVERN/MAP/MEASURE/MANAGE - GDPR, OECD, IEEE, UK, Singapore → INLINECODE3
- Financial services (SEC, FCA, FINRA, DORA, MiFID II, MNPI) → INLINECODE4
- Jurisdiction map (global regulatory landscape) → INLINECODE5
- ISO 27001 alignment → INLINECODE6
Output Templates & Tools
- - Checklists, risk assessment, gap analysis templates → INLINECODE7
- Vendor AI risk assessment questionnaire → INLINECODE8
- Acceptable use policy template → INLINECODE9
- Data classification × AI tool matrix → INLINECODE10
- AI system inventory template → INLINECODE11
- AI risk scoring model (0–100) → INLINECODE12
- Training requirements by role → INLINECODE13
Remediation
- - Incident response playbooks → INLINECODE14
- Remediation playbooks (common gaps) → INLINECODE15
When in doubt about which files to load, load the framework files + the relevant output template.
Workflow
1. Understand the AI Tool/Use Case
Gather (or ask for):
- - What does the AI system do? (intended purpose)
- Who uses it and how? (internal staff, customers, automated pipeline)
- What data does it process? (personal, financial, confidential, public)
- Where is it deployed? (EU context? affecting EU residents?)
- Consumer or enterprise tier? Third-party or internal?
2. Select Output Type
| Request | Load | Output |
|---|
| Compliance checklist | Framework files + checklist-templates.md | Full checklist per Template 1 |
| Risk assessment needed? |
eu-ai-act.md + checklist-templates.md | Risk tier determination per Template 2 |
| Gap analysis | All framework files + checklist-templates.md | Gap table per Template 3 |
| Risk score | risk-scoring.md | Scored worksheet + risk level |
| Vendor assessment | vendor-assessment.md | Questionnaire + scoring |
| AUP draft | aup-template.md | Customized policy draft |
| Data classification guidance | data-classification.md | Matrix + decision tree |
| Incident response | incident-response.md | Relevant playbook |
| Remediation steps | remediation-playbooks.md | Relevant playbook(s) |
| Financial services overlay | finserv-regulations.md | Regulatory requirements |
| Training requirements | training-requirements.md | Role-based matrix |
| Jurisdiction guidance | jurisdiction-map.md | Applicable rules by region |
3. Output Structure
Always structure output as:
CODEBLOCK0
Key Principles
- - Reference exact articles, clauses, controls (e.g., "EU AI Act Art.14", "ISO 42001 A.6.1", "NIST GOVERN 1.2")
- Flag HIGH/CRITICAL severity issues prominently — these are blockers
- Always include remediation steps, not just gaps — link to remediation-playbooks.md when relevant
- Cross-reference frameworks where they overlap
- For financial services firms: always check finserv-regulations.md for MNPI and sector-specific rules
- When uncertain about risk tier, err toward higher risk classification
技能名称: ai-compliance
详细描述:
AI合规技能
参考文件
根据请求类型仅加载所需内容:
框架
- - 欧盟AI法案 → references/eu-ai-act.md — 风险等级、禁止用途、义务
- ISO 42001 → references/iso-42001.md — 条款、附录A控制措施
- NIST AI风险管理框架 → references/nist-ai-rmf.md — 治理/映射/衡量/管理
- GDPR、OECD、IEEE、英国、新加坡 → references/other-frameworks.md
- 金融服务(SEC、FCA、FINRA、DORA、MiFID II、MNPI) → references/finserv-regulations.md
- 司法管辖区地图(全球监管格局) → references/jurisdiction-map.md
- ISO 27001对齐 → references/iso27001-alignment.md
输出模板与工具
- - 检查清单、风险评估、差距分析模板 → references/checklist-templates.md
- 供应商AI风险评估问卷 → references/vendor-assessment.md
- 可接受使用政策模板 → references/aup-template.md
- 数据分类×AI工具矩阵 → references/data-classification.md
- AI系统清单模板 → references/ai-inventory.md
- AI风险评分模型(0–100) → references/risk-scoring.md
- 按角色划分的培训要求 → references/training-requirements.md
补救措施
- - 事件响应预案 → references/incident-response.md
- 补救预案(常见差距) → references/remediation-playbooks.md
若不确定加载哪些文件,请加载框架文件及相关的输出模板。
工作流程
1. 理解AI工具/用例
收集(或询问):
- - AI系统做什么?(预期用途)
- 谁使用以及如何使用?(内部员工、客户、自动化流程)
- 处理哪些数据?(个人、财务、机密、公开)
- 部署在哪里?(欧盟环境?影响欧盟居民?)
- 消费者级还是企业级?第三方还是内部?
2. 选择输出类型
| 请求 | 加载 | 输出 |
|---|
| 合规检查清单 | 框架文件 + checklist-templates.md | 按模板1的完整检查清单 |
| 需要风险评估? |
eu-ai-act.md + checklist-templates.md | 按模板2的风险等级判定 |
| 差距分析 | 所有框架文件 + checklist-templates.md | 按模板3的差距表 |
| 风险评分 | risk-scoring.md | 评分工作表 + 风险等级 |
| 供应商评估 | vendor-assessment.md | 问卷 + 评分 |
| AUP草案 | aup-template.md | 定制化政策草案 |
| 数据分类指导 | data-classification.md | 矩阵 + 决策树 |
| 事件响应 | incident-response.md | 相关预案 |
| 补救步骤 | remediation-playbooks.md | 相关预案 |
| 金融服务叠加 | finserv-regulations.md | 监管要求 |
| 培训要求 | training-requirements.md | 基于角色的矩阵 |
| 司法管辖区指导 | jurisdiction-map.md | 按地区适用的规则 |
3. 输出结构
始终按以下结构输出:
AI合规评估:[工具/用例名称]
风险分类
适用框架
合规检查清单(或差距分析或风险评分)
发现的问题
建议
优先行动
关键原则
- - 引用具体条款、条文、控制措施(例如“欧盟AI法案第14条”、“ISO 42001 A.6.1”、“NIST GOVERN 1.2”)
- 突出显示高/严重级别问题——这些是障碍
- 始终包含补救步骤,而不仅仅是差距——必要时链接到remediation-playbooks.md
- 在框架重叠处进行交叉引用
- 对于金融服务公司:始终检查finserv-regulations.md中的MNPI和特定行业规则
- 若对风险等级不确定,倾向于更高风险分类