No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ZongziForu · MCP Server · ★ 75
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cn-law-hub safe to install? View the security audit →
CN Law Hub — 中国法条检索 / PRC Statute & Regulation Search for AI Agents 面向 Claude Code、Codex、Kimi 等 AI Agent 的中国大陆法条与法律法规检索 Skill，直接检索全国人大、国务院、司法部、最高人民法院等 10 个官方来源，支持具体条文检索、跨法规正文搜索、现行有效筛选与官方原文下载。 Chinese legal research Agent Skill for retrieving and verifying Chinese laws from official sources. 覆盖 10 个官方数据源： 国家法律法规数据库（NPC） — 国家规章库（Gov Rules） — 外交条约库（Treaty） — 国务院政策文件库 — 司法部行政法规库 — 党内法规库 — 国防部法规文库 — 税务法规库 — 生态环境部法规规章 — 最高人民法院发布栏目 — 什么时候使用这个 Skill 当你需要查询、核验、下载或引用中国官方法律法规、规章、条约和具体法条时，可以直接让 agent 使用本 skill。多数情况下，你不需要手动运行脚本，只需要用自然语言说明任务，agent 会根据 自动选择合适的数据源、脚本和参数。 如果你希望确保在当前工作中使用本 skill，也可以在请求中直接使用 指令（尤其在你没有使用能力较强的模型时）。 典型场景包括：查法规全文、核验现行有效状态、查询某法第几条、按关键词检索具体法条、为法律咨询/案例分析/合规审查提供官方法条依据、批量下载法规文件或导出法规目录。 例如： text 帮我查《劳动合同法》第三十八条，并引用现行有效版本。 找一下关于物业管理的现行有效地方性法规。 帮我检索包含“违约金”的
| Stars | 75 |
| Forks | 15 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 61.7040994455867/100 |
| Last Updated | 2026-09-21 |
| Created | 2026-06-25 |
| Platforms | aws, claude-code, codex, mcp, python |
| Est. Tokens | ~17k |
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cn-law-hub is 中国法条与法律法规检索 Agent Skill｜Chinese legal research Agent Skill for retrieving and verifying Chinese laws from official sources｜支持具体法条检索、现行有效核验、10 个官方法律数据源. It is categorized as a MCP Server with 75 GitHub stars.
cn-law-hub is primarily written in Python. It covers topics such as agent-skills, china-law, chinese-law.
You can find installation instructions and usage details in the cn-law-hub GitHub repository at github.com/ZongziForu/cn-law-hub. The project has 75 stars and 15 forks, indicating an active community.
The top alternatives to cn-law-hub on Agent Skills Hub include legal-skills-open, tw-legal-rag, awesome-ai-agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: