AI Safety Audit

Comprehensive AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and NIST AI RMF.

3,891 stars
Complexity: easy

About this skill

The AI Safety Audit skill provides a structured framework for AI agents to conduct thorough safety and alignment audits of an organization's AI deployments. Upon activation, the agent will systematically inventory all AI models and automated decision systems, classify each according to EU AI Act risk tiers, and then assess 30 specific controls across six critical domains. This process identifies missing safeguards, evaluates their severity, and estimates remediation costs, culminating in a detailed gap analysis. Organizations can utilize this skill to proactively ensure their AI systems are compliant with evolving global regulations and best practices, mitigating potential legal, ethical, and operational risks. It's particularly valuable for businesses scaling their AI initiatives or operating in regulated industries, providing a clear pathway to responsible AI deployment and governance. The audit framework covers critical areas from model governance and data protection to output safety, security, and ongoing monitoring. The audit encompasses vital aspects such as hallucination detection, bias testing, prompt injection defense, data provenance, access control, and real-time performance tracking. By generating a prioritized 90-day action plan, the skill empowers businesses to systematically address identified vulnerabilities and build more trustworthy and compliant AI operations.

Best use case

The primary use case for the AI Safety Audit skill is to help organizations systematically evaluate their AI deployments against established safety and regulatory frameworks. It's ideal for businesses that need to ensure compliance with upcoming regulations like the EU AI Act and UK standards, identify potential risks, and proactively mitigate them, thereby fostering trust and reducing legal exposure related to their AI systems. Compliance officers, legal teams, AI ethics committees, and AI development leads will benefit most.

Comprehensive AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and NIST AI RMF.

Users should expect a detailed report outlining AI system risks, compliance gaps, and a prioritized 90-day action plan for remediation.

Practical example

Example input

Conduct a full AI Safety Audit for our company's deployed AI agents, ensuring compliance with the EU AI Act and UK AI Security Institute standards.

Example output

AI Safety Audit Report Summary:
- 8 AI systems inventoried (2 High-Risk, 4 Limited-Risk).
- 11 compliance gaps identified across Data Protection (e.g., PII handling documentation) and Output Safety (e.g., hallucination mitigation for LLMs).
- High severity remediation required for 3 items.
- Prioritized 90-day action plan generated for immediate implementation.

When to use this skill

  • Before deploying new AI systems or agents into production.
  • Annually or semi-annually to review existing AI deployments for ongoing compliance.
  • When preparing for external regulatory audits or internal governance reviews related to AI.
  • After significant updates to AI models or changes in AI operational procedures.

When not to use this skill

  • For personal or hobby AI projects where regulatory compliance is not a concern.
  • If you only need a very specific, narrow check (e.g., only bias testing) rather than a full audit.
  • When an organization has no AI systems deployed or has no immediate plans to deploy them.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/afrexai-ai-safety-audit/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1kalin/afrexai-ai-safety-audit/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/afrexai-ai-safety-audit/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How AI Safety Audit Compares

Feature / AgentAI Safety AuditStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityeasyN/A

Frequently Asked Questions

What does this skill do?

Comprehensive AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and NIST AI RMF.

How difficult is it to install?

The installation complexity is rated as easy. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# AI Safety Audit

Comprehensive AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and NIST AI RMF.

## What This Skill Does

When activated, the agent performs a structured safety audit of your AI deployment:

1. **AI System Inventory** — Catalogs all AI models, agents, and automated decision systems in use
2. **Risk Classification** — Maps each system to EU AI Act risk tiers (Unacceptable/High/Limited/Minimal)
3. **Safety Controls Assessment** — Evaluates 30 controls across 6 domains
4. **Gap Analysis** — Identifies missing safeguards with severity and remediation cost
5. **Compliance Roadmap** — Generates a prioritized 90-day action plan

## 6 Audit Domains (30 Controls)

### 1. Model Governance (5 controls)
- Model registry with version tracking
- Access control and deployment permissions
- Update and rollback procedures
- Vendor risk assessment for third-party models
- Model retirement and data deletion policy

### 2. Data Protection (5 controls)
- Data residency and sovereignty mapping
- PII detection and handling in AI pipelines
- Training data provenance documentation
- Data retention aligned with AI lifecycle
- Cross-border data transfer compliance

### 3. Output Safety (5 controls)
- Hallucination detection and mitigation
- Bias testing across protected characteristics
- Content filtering for harmful outputs
- Confidence scoring and uncertainty flagging
- Human-in-the-loop for high-stakes decisions

### 4. Security (5 controls)
- Prompt injection defense
- Model extraction prevention
- API rate limiting and abuse detection
- Adversarial input testing
- Supply chain security for AI dependencies

### 5. Monitoring & Observability (5 controls)
- Real-time output quality tracking
- Drift detection (data and model)
- Incident logging and alerting
- Performance degradation monitoring
- Cost tracking per AI workflow

### 6. Organizational Readiness (5 controls)
- Named AI safety officer
- Staff training program with completion tracking
- Board-level AI risk reporting
- Incident response playbook
- Third-party audit schedule

## Scoring

Each control scores 0-3:
- **0** — Not implemented
- **1** — Partially implemented, no documentation
- **2** — Implemented with documentation
- **3** — Implemented, documented, tested, and audited

**Total: 90 points max**
- 0-30: Critical risk — stop deploying until gaps are addressed
- 31-55: High risk — remediate within 30 days
- 56-75: Moderate risk — address within 90 days
- 76-90: Strong posture — maintain and iterate

## Regulatory Mapping

| Framework | Status | Key Requirements |
|-----------|--------|-----------------|
| EU AI Act | Enforcing 2026 | Risk classification, conformity assessment, transparency |
| UK AI Safety Institute | Active 2026 | Alignment testing, frontier model evaluation |
| NIST AI RMF | Published | Govern, Map, Measure, Manage lifecycle |
| ISO 42001 | Published | AI management system certification |
| SOC 2 + AI | Emerging | Agent-specific controls (CC6/CC7/CC8) |

## Cost Benchmarks

| Company Size | Full Audit Cost | Annual Compliance | Non-Compliance Risk |
|-------------|----------------|-------------------|-------------------|
| 15-50 employees | $8K – $20K | $18K – $45K | $200K+ |
| 50-200 employees | $20K – $55K | $45K – $120K | $500K – $2M |
| 200-1000 employees | $55K – $150K | $120K – $400K | $2M – $10M |

## Output Format

The agent delivers:
1. **Executive Summary** — Overall score, top 3 risks, recommended actions
2. **Detailed Scorecard** — All 30 controls with scores and evidence
3. **Gap Analysis** — Missing controls ranked by risk severity
4. **90-Day Roadmap** — Phased remediation plan with cost estimates
5. **Board Report Template** — One-page summary for leadership

## Industry Adjustments

The audit adjusts control weighting based on industry:
- **Healthcare**: Output safety and data protection weighted 2x
- **Financial Services**: Model governance and monitoring weighted 2x
- **Legal**: Output safety (hallucination) weighted 3x
- **Manufacturing**: Security and monitoring weighted 2x
- **Government/Defense**: All domains weighted equally at maximum

---

## Go Deeper

- **[AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)** — Quantify what safety gaps cost your business
- **[Industry Context Packs ($47)](https://afrexai-cto.github.io/context-packs/)** — Pre-built compliance frameworks for your specific vertical
- **[Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)** — Deploy agents with safety controls from day one

### Bundles
- AI Playbook — $27
- Pick 3 Industries — $97
- All 10 Industries — $197
- Everything Bundle — $247

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