/cs:aims-audit — AIMS ISO 42001 Forcing Questions

SkillAI & models

This skill lets your AI run a six-question internal audit of your AI management system against ISO/IEC 42001, so you find gaps before a formal auditor does. It fits three moments: before certification stage 1, before annual internal audit cycles, and when bringing a new AI system into an existing AI management system. You name the scope, and your AI works through the checklist with you.

Available today. Use it from your connected AI after setup.

After adding it, tell your AI the scope you want examined and it will run the six-question interrogation for that area. Use what it flags to close gaps before a formal audit.

Then ask your AI: use the /cs:aims-audit — AIMS ISO 42001 Forcing Questions skill

What your AI can do with it

  • Run a six-question internal audit of your AI management system
  • Check ISO/IEC 42001 readiness before certification stage 1
  • Work through the checklist ahead of annual internal audit cycles
  • Assess a new AI system before it joins an existing AI management system
  • Audit a scope you name instead of everything at once

What this skill tells your AI

The instructions your AI receives, as published by alirezarezvani/claude-skills in .gemini/skills/aims-audit/SKILL.md and read by ahel’s review.

Command: /cs:aims-audit <scope>

The ISO 42001 AIMS specialist pressure-tests any AI Management System work. Six questions before any certification commitment, internal audit cycle, or new-system onboarding.

When to Run

  • Before stage 1 ISO 42001 certification audit
  • Before annual internal audit cycle (Clause 9.2)
  • When onboarding a new AI system into existing AIMS scope
  • When AI risk register hasn't been refreshed in > 6 months
  • After material model change (re-evaluate risks per Clause 6.1.2)
  • When audit findings hint at AIMS / ISMS / QMS duplication

The Six AIMS Questions

1. Does the AIMS scope statement name every AI system?

Scope omission = certification finding.

  • Including: embedded models, third-party AI services, "experimental" production systems
  • Run aims_gap_analyzer.py to verify Clause 4.3 evidence
  • "AI features added by SaaS vendors we use" = in scope if they affect the company's services

2. Does the AI policy commit to lawful use AND beneficial purpose AND human oversight AND continual improvement?

Missing any of the four = critical nonconformity at stage 1.

  • AI policy is NOT info-sec policy — it has separate substantive content
  • Reference ISO 42001 Annex A.2.2 + Clause 5.2
  • Marketing-copy "AI ethics" doesn't pass

3. What's the risk register coverage, and which Annex A controls treat each risk?

Risk identification without control mapping = Clause 6.1.3 fails.

  • Run ai_risk_register_builder.py per ISO 23894 methodology
  • Every high/critical risk must link to ≥ 1 Annex A control
  • "Residual verdict: additional_treatment_required" must be closed before stage 1

4. Has the AI risk assessment been re-run since the last material model change?

Concept drift is not a one-time event.

  • Article 9 EU AI Act + ISO 42001 Clause 6.1.2 both require iterative risk assessment
  • Material change = retraining on new data, fine-tuning, architecture change, deployment context change
  • If "we did it 18 months ago and haven't touched it," the AIMS is broken

5. What's the Clause 9.2 internal audit plan, and is auditor independence respected?

Without 9.2 plan, the AIMS is incomplete.

  • Run aims_audit_scheduler.py with scope + auditors + prior findings
  • Audit every clause + applicable Annex A control over rolling 3-year cycle
  • Same auditor cannot audit own work
  • Cross-check with cs-quality-regulatory if integrated with 13485 audit programme

6. Has the AIMS been integrated with existing ISMS / QMS, or built in parallel?

Parallel systems = 5x ongoing maintenance cost.

  • 60% of Clauses 4-10 evidence reuses ISO 27001 / 13485 with AI scope appended
  • CAPA loop should be ONE loop with AI-tagged nonconformities, not separate
  • Reference cross_framework_mapping_ai.md for the reuse map
  • Cross-check with cs-ciso-advisor on ISO 27001 alignment

Workflow

# 1. AIMS gap analysis
python ra-qm-team/skills/iso42001-specialist/scripts/aims_gap_analyzer.py evidence.json

# 2. AI risk register
python ra-qm-team/skills/iso42001-specialist/scripts/ai_risk_register_builder.py risks.json

# 3. Internal audit plan
python ra-qm-team/skills/iso42001-specialist/scripts/aims_audit_scheduler.py audit_scope.json

# 4. Cross-framework reuse map (via compliance-os)
python ../../skills/compliance-os/scripts/cross_framework_mapper.py program.json

Output Format

# AIMS Audit: <scope>
**Date:** YYYY-MM-DD

## The Decision Being Made
[gap-closure | risk-treatment | audit-scope | new-system-onboarding]

## Gap Analysis (Clauses 4-10)
- Weighted coverage: X%
- Critical gaps: N
- Major gaps: M
- Certification readiness: ready | stage_2_candidate | not_ready

## AI Risk Register
- Total risks: N
- By severity: critical=X, high=Y, medium=Z, low=W
- Requires additional treatment: K
- Top risk requiring action: <description>

## Clause 9.2 Audit Plan
- 12-month coverage: clauses=X, controls=Y
- Auditor independence: clean | issues
- Prior-year follow-up: scheduled in Q1

## Cross-Framework Reuse
- ISO 27001 evidence reused: % of AIMS Clauses 4-10
- 13485 evidence reused: % (if applicable)
- Net-new for AIMS: % (mostly Annex A)

## Verdict
🟢 STAGE-1-READY | 🟡 CLOSE-CRITICALS-FIRST | 🔴 NOT-READY

## Top 3 Actions
[3 concrete next steps with owner + date]

Routing

  • /cs:compliance-readiness — for multi-framework view
  • /cs:ai-act-readiness — if EU AI Act also applies
  • /cs:caio-review — for executive AI strategy decisions
  • /cs:ciso-review — for ISO 27001 cross-framework alignment
  • /cs:decide — to log the verdict
  • /cs:freeze 30 — on certification commitments

Related


Version: 1.0.0

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Source
github.com/alirezarezvani/claude-skills