
AIMS Audit
FreeStreamline your ISO 42001 AIMS compliance process.
Free · Opens the source repo
What AIMS Audit does
The AIMS Audit skill provides a structured approach to ensure compliance with ISO/IEC 42001 standards for AI Management Systems (AIMS). It features a command, /cs:aims-audit <scope>, which guides users through a series of six critical questions designed to pressure-test their AIMS before certification, during internal audits, or when integrating new AI systems. This skill is particularly useful for compliance teams and AI system managers who need to maintain rigorous standards in AI governance.
Each of the six questions addresses key areas of compliance, such as ensuring all AI systems are included in the scope, verifying the AI policy's commitments, and assessing the coverage of the risk register. The skill also emphasizes the importance of ongoing risk assessments, especially after significant changes to AI models, and encourages users to maintain a clear internal audit plan that respects auditor independence. By following this structured interrogation, users can identify gaps in their compliance and take corrective actions before formal audits.
The workflow consists of several Python scripts that automate the analysis process. Users can run gap analyses, build risk registers, and schedule internal audits, all of which are essential for maintaining compliance with ISO 42001. The output format provides a clear summary of the audit findings, including critical gaps, risk coverage, and actionable next steps, making it easier for teams to track their compliance status and prepare for audits.
This skill is ideal for organizations that are either preparing for their initial ISO 42001 certification or those looking to refine their existing compliance processes. It is also beneficial for teams that have recently onboarded new AI systems or made significant changes to their AI models, ensuring that compliance is continuously monitored and maintained.
When to use it
Use this skill when preparing for ISO 42001 certification audits, during annual internal audit cycles, or when onboarding new AI systems.
When not to use it
This skill may not be suitable for organizations not pursuing ISO 42001 certification or those without established AI management systems.
What you can build with it
Preparing for ISO Certification
Run the AIMS Audit skill to ensure all aspects of your AI Management System are compliant before the certification audit.
Conducting Internal Audits
Utilize the skill during your annual internal audit cycle to identify and address compliance gaps.
Onboarding New AI Systems
Use the AIMS Audit skill when integrating new AI systems to ensure they meet existing compliance requirements.
How to install AIMS Audit
View source1. Install with the skills CLI
npx skills add alirezarezvani/claude-skills/aims-audit --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by alirezarezvani/cs:aims-audit — AIMS ISO 42001 Forcing Questions
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.pyto 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.pyper 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.pywith 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.mdfor 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
- Agent:
cs-aims-iso42001 - Skill:
iso42001-specialist - Adjacent:
../../skills/compliance-os/,../ai-act-readiness/,../compliance-readiness/
Version: 1.0.0
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