Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add zhou210712/claude-for-legal-ZH --skill aia-generationgit clone --depth 1 https://github.com/zhou210712/claude-for-legal-ZHWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zhou210712/claude-for-legal-zh/aia-generation)<a href="https://agentmods.dev/skills/zhou210712/claude-for-legal-zh/aia-generation"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/aia-generation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zhou210712/claude-for-legal-zh/aia-generation"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/aia-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00087 | $0.03180 |
| Opus 5 | $0.00044 | $0.01590 |
| Sonnet 5 | $0.00017 | $0.00636 |
| Haiku 4.5 | $0.00009 | $0.00318 |
Grade A, and why
aia-generation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aia-generation
- 读取
~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md→ 监管注册表（适用法规、阈值、义务）、AI系统清单、科技伦理审查配置。 - 运行以下工作流。
- 判定走快速轨还是全面轨。提取系统描述 → 确定监管角色和风险等级 → 生成评估。
- 输出：定级 + 评估文件，包含具体行动项、负责人和截止日期。
/ai-governance-legal:aia-generation "客户信用评分模型 v2"
AI系统评估生成
事务上下文
事务上下文。 检查实践级 CLAUDE.md 中的 ## 事务工作区。如果 已启用 为 ✗（法务内部用户的默认值），跳过本段其余部分——技能使用实践级上下文，事务机制不可见。如果已启用且无活跃事务，询问："此事务属于哪个事务？运行 /ai-governance-legal:matter-workspace switch <slug> 或回答 实践级。" 加载活跃事务的 matter.md 获取事务特定上下文和覆盖项。将输出写入事务文件夹 ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/matters/<matter-slug>/。除非 跨事务上下文 为 开，否则绝不读取其他事务的文件。
目的
有些AI法规要求进行正式评估——在部署高风险系统之前、在商业模式变更之前、在训练数据或决策逻辑发生实质性变更时。此技能生成评估，并按法规要求保留记录。
适用法规
中国的AI治理框架由多个法规和规范性文件构成，根据系统类型和风险等级适用不同的评估要求：
- 《生成式人工智能服务管理办法》：面向公众提供生成式AI服务的，需进行安全评估和算法备案（第17条
[法条原文]） - 《科技伦理审查办法（试行）》：涉及生命健康、个人信息、社会公共利益等的科技活动需进行伦理审查
[法条原文] - 《互联网信息服务算法推荐管理规定》：使用算法推荐技术的，需进行算法备案（第24条
[法条原文]）和安全评估（第27条[法条原文]） - 《互联网信息服务深度合成管理规定》：提供深度合成服务的，需进行安全评估（第15条
[法条原文]） - 《个人信息保护法》：涉及个人信息处理的AI系统，需进行个人信息保护影响评估（第55-56条
[法条原文]）
加载当前状态
读取 ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md：
## AI系统清单— 系统中每个AI系统的角色和等级## 监管注册表— 适用的法规及阈值## 科技伦理审查配置— 伦理审查委员会设置和审查触发条件
工作流
第1步：轨道判定
| 特征 | 快速轨 | 全面轨 |
|---|---|---|
| 系统类型 | 低风险内部工具（非面向公众） | 高风险系统或面向公众的系统 |
| 数据处理 | 不涉及个人信息或仅涉及内部员工数据 | 涉及用户个人信息、敏感个人信息或大规模数据处理 |
| 算法备案 | 无需备案 | 需要或可能需要进行算法备案 |
| 深度合成/生成式 | 不涉及 | 涉及生成合成内容或深度合成 |
| 评估历史 | 已有近期全面评估记录，仅作小幅更新 | 首次评估或实质性变更 |
如果系统明确匹配左列所有特征 → 快速轨。否则 → 全面轨。
第2步：监管角色判定
根据系统性质确定监管角色：
| 角色 | 定义 | 典型场景 |
|---|---|---|
| AI服务提供者 | 自主研发并向公众提供AI服务的主体 | 自研模型/SaaS AI产品 |
| AI服务使用者 | 使用第三方AI服务进行内部业务活动的主体 | 采购第三方AI能力嵌入自有业务流程 |
| 双重角色 | 同时具备提供者和使用者属性 | 基于第三方模型微调后对外提供服务 |
角色判定影响后续义务范围：
- 提供者：需进行算法备案、安全评估、内容标识，承担更重的合规义务（《生成式人工智能服务管理办法》第7-17条
[法条原文]） - 使用者：需确保合规使用、进行供应商尽职调查，但备案义务较轻
第3步：风险等级判定
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 234 lines · 87 tokens per session scan A db1cac6e7072
aia-generation is a skill published in the GitHub repository zhou210712/claude-for-legal-ZH (212 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 87 tokens to every session and 3,180 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
prowler-compliance
Creates, syncs, audits and manages Prowler compliance frameworks end-to-end. Covers the two supported JSON schemas (universal multi-provider and legacy per-provider), the SDK model tree (legacy attribute classes, universal ComplianceFramework, ConfigRequirements guardrails), output formatters (legacy per-framework +…
policy
Define and enforce decision policies, compliance rules, and exceptions over Semantica graphs. Uses ContextGraph.checkdecisionrules/enforcedecisionpolicy and context.PolicyEngine.
801-regulations-eu-ai-act
Use when reviewing, designing, or modifying Java enterprise systems that use AI, LLMs, AI agents, RAG, tool calling, workflow automation, or model-based decision support and need EU AI Act regulatory awareness. This should trigger for requests such as Review a Java AI system for EU AI Act controls; Design governance…
813-regulations-iso-42001
Use when reviewing, designing, or modifying Java enterprise systems that use GenAI, LLMs, AI-assisted coding, RAG, AI agents, generated code, generated dependencies, prompt workflows, external model providers, or AI-enabled business logic and need ISO/IEC 42001 AI management system-aware engineering guidance. Part of…
open-weights
Use when choosing an open-weight LLM and clearing it for use — which family and size fit the task, the hardware and the budget, and above all whether the license permits shipping. Owns the license-class map (OSI-open versus custom-community versus non-commercial), the always-verify-the-model-card rule, size-to-VRAM…
ai-policy-generator
AI governance policy creation for nonprofits and enterprises with frameworks, risk assessment, ethical guidelines, and compliance templates. Use when drafting AI usage policies, responsible AI frameworks, or organizational AI governance documents.