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 reg-gap-analysisgit 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/reg-gap-analysis)<a href="https://agentmods.dev/skills/zhou210712/claude-for-legal-zh/reg-gap-analysis"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/reg-gap-analysis/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/reg-gap-analysis"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/reg-gap-analysis.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 | $0.00071 | $0.02951 |
| Opus 5 | $0.00036 | $0.01476 |
| Sonnet 5 | $0.00014 | $0.00590 |
| Haiku 4.5 | $0.00007 | $0.00295 |
Grade A, and why
reg-gap-analysis 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.
This is a copy
81% identical to smart-search — 239 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/reg-gap-analysis
- 读取
~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md→ AI系统清单、监管注册表、AI政策承诺。 - 运行以下工作流。
- 范围:该法规是否适用?(管辖权、阈值、行业)
- 提取要求 → 与当前状态对比 → 差距清单。
- 整改计划附负责人、日期、优先级。
- 保存注明日期的文档。即使"无差距"也应记录。
/ai-governance-legal:reg-gap-analysis "生成式人工智能服务管理办法"
AI法规与政策差距分析
目的
网信办发布新的AI管理规定。科技部更新伦理审查标准。某省出台AI治理细则。法规有所变化——现在你需要知道哪些地方需要跟进。
此技能将新要求与你当前的AI实践(按照 ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md → AI系统清单 + AI使用政策承诺 + 已完成的评估记录)进行对比,产出差距清单和整改计划。
加载当前状态
读取 ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md:
## AI系统清单— 已部署、在评估和已退役的系统## 监管注册表— 已经适用的法规## AI使用政策— 已对外公开的AI使用承诺或内部AI治理政策## 科技伦理审查配置— 伦理审查委员会的设置和流程
如果该法规不适用于你(错误管辖权、低于阈值、不同行业),差距分析只有一行:"不适用。理由:[原因]。无需行动。"
工作流
第1步:法规范围界定
在对比之前,先回答:
- 是否适用? 法规是否覆盖你的业务类型、系统类型或数据规模?
- 是否向中国境内公众提供AI服务?(《生成式人工智能服务管理办法》第2条
[法条原文]) - 是否使用算法推荐技术?(《互联网信息服务算法推荐管理规定》第2条
[法条原文]) - 是否涉及深度合成?(《互联网信息服务深度合成管理规定》第2条
[法条原文]) - 是否涉及需科技伦理审查的科技活动?(《科技伦理审查办法(试行)》
[法条原文])
- 是否向中国境内公众提供AI服务?(《生成式人工智能服务管理办法》第2条
- 何时生效? 生效日期、执法开始日期(通常晚于生效日期)、是否有过渡期
- 真正的新内容是什么? 识别与已有合规义务的增量差异,而非全文重述
第2步:提取要求
阅读法规文本(或摘要/指南)。将每项实质性要求列为离散条目:
| # | 要求 | 法条引用 | 类别 |
|---|---|---|---|
| 1 | [要求原文或摘要] | [条款] | [训练数据 / 透明度 / 安全 / 备案 / 伦理 / 其他] |
类别:
- 训练数据 — 训练数据的合法性、来源、知识产权、个人信息保护
- 透明度 — 告知用户、标识AI生成内容、算法说明
- 安全 — 安全评估、技术措施、内容安全管理
- 备案 — 算法备案要求、备案变更义务
- 伦理 — 科技伦理审查要求
- 治理 — 个人信息保护负责人、投诉机制、审计日志留存
- 责任 — 提供者/使用者责任分配
第3步:与当前状态对比
对每项要求:
### [要求 #N]:[简短名称]
**法规要求:** [要求原文或概述]
**我方现状:** [当前AI系统清单 / 政策 / 实践显示的现状]
**差距:** [无 / 部分 / 完全]
**如为部分/完全差距——缺什么:** [具体说明]
**弥补难度:** [仅政策更新 / 产品变更 / 供应商重新谈判 / 新流程建设]
**违规风险:** [行政处罚/责令整改/罚款幅度、执法可能性、声誉影响]
中国AI法规的行政处罚参考:
- 《生成式人工智能服务管理办法》第21条:警告、通报批评、责令限期改正;拒不改正或情节严重者,责令暂停服务,处一万元以上十万元以下罚款
[法条原文] - 《互联网信息服务算法推荐管理规定》第31条:警告、通报批评、责令限期改正;拒不改正或情节严重者,责令暂停信息更新,处一万元以上十万元以下罚款
[法条原文] - 《个人信息保护法》第66条:情节严重的,处五千万元以下或者上一年度营业额百分之五以下罚款
[法条原文]
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 · 190 lines · 71 tokens per session scan A 5e48972bd07c
reg-gap-analysis 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 71 tokens to every session and 2,951 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to smart-search, differing in 239 lines, and is treated as a copy.
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