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Eu ai act

Skill bromso/metapowers/plugins/compliance/skills/eu-ai-act

A Claude Code plugin that adds an agentic skills framework, with MCP's and a meta prompting processes. Inspired by "Superpowers" & "Figma Console MCP", but not just for development or design; but for all aspect within the digital production cycle.

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npx -y skills add bromso/metapowers --skill eu-ai-act

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Assess EU AI Act compliance — risk classification, prohibited uses, high-risk requirements, transparency

SKILL.md

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EU AI Act Assessment

Assess EU AI Act compliance for "$ARGUMENTS". Classify AI systems by risk level, evaluate prohibited practice avoidance, assess high-risk system requirements, and review transparency obligations.

Prerequisites

Read .metapowers/compliance/$ARGUMENTS/00-scope.md. If this file does not exist, tell the user:

Phase 0 (Scope) has not been completed for "$ARGUMENTS". Run /compliance:regulatory-landscape $ARGUMENTS first, or use --skip-checks to bypass.

If --skip-checks is present in $ARGUMENTS, skip this check.

Process

  1. Read context files:

    • Read plugins/compliance/shared/grc-lifecycle-guide.md for GRC methodology reference
    • Read plugins/compliance/shared/assessment-template.md for output structure
    • Read .metapowers/compliance/$ARGUMENTS/00-scope.md for scope and control framework context

  2. AI system inventory and risk classification:

    • Inventory all AI systems deployed or under development
    • Classify each system by EU AI Act risk level:
      • Unacceptable risk (prohibited): social scoring, real-time remote biometric identification (with exceptions), manipulation/exploitation, emotion recognition in workplace/education
      • High-risk: Annex III systems (biometrics, critical infrastructure, education, employment, essential services, law enforcement, migration, justice) and safety components of Annex I products
      • Limited risk: transparency obligations (chatbots, emotion recognition, deepfakes, AI-generated content)
      • Minimal risk: voluntary codes of conduct
    • Document classification rationale for each system

  3. Prohibited practices assessment:

    • Check all AI systems against the prohibited practices list (Art 5)
    • Assess subliminal manipulation techniques, exploitation of vulnerabilities
    • Review social scoring systems or behavioral prediction for detrimental treatment
    • Evaluate real-time remote biometric identification usage and exemptions
    • Document any systems requiring immediate remediation or discontinuation

  4. High-risk system requirements (if applicable):

    • Risk management system (Art 9): Assess continuous risk identification, estimation, evaluation, and mitigation throughout the AI lifecycle
    • Data governance (Art 10): Evaluate training, validation, and testing data quality, relevance, representativeness, and bias examination
    • Technical documentation (Art 11): Review documentation completeness for demonstrating conformity
    • Record-keeping (Art 12): Assess automatic logging capabilities for traceability
    • Transparency to users (Art 13): Evaluate instructions for use, intended purpose, accuracy levels, and known limitations
    • Human oversight (Art 14): Assess human-in-the-loop, human-on-the-loop, or human-in-command measures
    • Accuracy, robustness, cybersecurity (Art 15): Evaluate performance metrics, resilience to errors, and security measures

  5. General-purpose AI model obligations:

    • Determine if any GPAI models are used or provided (Art 51-56)
    • Assess technical documentation and information sharing obligations
    • Evaluate compliance with Copyright Directive obligations
    • For GPAI with systemic risk: assess model evaluation, adversarial testing, incident reporting, and cybersecurity requirements

  6. Transparency obligations:

    • Assess AI interaction disclosure (users must know they are interacting with AI)
    • Evaluate emotion recognition and biometric categorization disclosure
    • Review deepfake and AI-generated content labeling
    • Assess AI-generated content marking requirements

  7. Conformity assessment and registration:

    • Determine applicable conformity assessment procedure (self-assessment or third-party)
    • Assess EU database registration requirements
    • Evaluate CE marking requirements for high-risk systems
    • Review EU representative appointment for non-EU providers

  8. Timeline and phased enforcement:

    • Map current compliance against enforcement timeline (prohibited practices: Feb 2025, GPAI: Aug 2025, high-risk Annex III: Aug 2026, high-risk Annex I: Aug 2027)
    • Identify time-critical compliance activities
    • Assess readiness for applicable enforcement phases

  9. Write the artifact to .metapowers/compliance/$ARGUMENTS/01-assess/eu-ai-act.md following the assessment template structure with:

    • AI System Inventory — complete inventory with risk classification per system
    • Prohibited Practices — screening results and any systems requiring action
    • High-Risk Requirements — assessment per Art 9-15 requirement for each high-risk system
    • GPAI Obligations — general-purpose AI model compliance status
    • Transparency — disclosure and labeling obligations coverage
    • Conformity and Registration — assessment procedure readiness
    • Enforcement Timeline — phased compliance readiness map
    • Evidence Inventory — existing evidence and evidence gaps
    • Remediation Priorities — ranked list of gaps to address

Output

The EU AI Act assessment written to .metapowers/compliance/$ARGUMENTS/01-assess/eu-ai-act.md. Present a summary to the user highlighting:

  • Number of AI systems inventoried and risk classification distribution
  • Any prohibited practice concerns requiring immediate action
  • High-risk system compliance readiness score
  • Top 3 gaps requiring remediation

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