技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 352 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：1kalin/afrexai-ai-safety-audit
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill's requirements and instructions are internally consistent with an AI safety audit: it's an instruction-only skill that asks the agent to produce an inventory, map risk tiers, score 30 controls, and produce deliverables — nothing in the package requests unrelated credentials or installs code.
目的
Name, description, and SKILL.md all describe an AI safety audit and the included controls, scoring, and outputs align with that purpose. There are no unrelated required binaries, environment variables, or install steps that contradict the stated function.
说明范围
The SKILL.md is high-level and prescriptive about what to produce (inventory, classification, scorecard, roadmap) but does not define concrete data sources or safe boundaries. This gives the agent broad discretion to ask for or attempt to collect inventory and evidence; that is reasonable for an audit but creates a scope/privilege risk if the agent is allowed to autonomously access systems or credentials without constraints.
安装机制
No install spec and no code files — instruction-only skill. This minimizes on-disk execution risk because nothing will be downloaded or installed by the skill itself.
证书
The skill declares no required environment variables, credentials, or config paths. That is proportionate to an instruction-only audit template. Note: at runtime the agent may request credentials or access from the user to gather evidence; those requests are not part of the package and should be evaluated before granting.
持久
always:false and no installable components — the skill does not request permanent presence or system-level changes. The agent may still be allowed to invoke the skill autonomously (platform default); that alone is not flagged but users should be mindful of the agent's allowed actions when the skill is active.
综合结论
This instruction-only skill appears coherent for performing an AI safety audit, but its runtime instructions are intentionally high-level and will require the agent to gather evidence (model inventories, documentation, logs, etc.). Before using it: 1) Decide which data sources you permit the agent to access and avoid handing long-lived credentials; prefer scoped, read-only accounts or temporary credentials. 2) Be cautious if you allow autonomo…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「AI Safety Audit」。简介：Performs a comprehensive AI safety audit mapping systems to EU AI Act risk tier…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1kalin/afrexai-ai-safety-audit/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
# 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