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 statusgit 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/status)<a href="https://agentmods.dev/skills/zhou210712/claude-for-legal-zh/status"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/status/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/status"><img src="https://agentmods.dev/badge/skills/zhou210712/claude-for-legal-zh/status.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 | $0.00080 | $0.01902 |
| Opus 5.5 | $0.00032 | $0.00761 |
| Sonnet 5.5 | $0.00016 | $0.00380 |
| Haiku 4.5 | $0.00008 | $0.00190 |
Grade A, and why
status 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 1mo 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
88% identical to client-intake — 277 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/status
- 加载
~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md→ 指导风格、通俗语言标准、管辖地。 - 使用以下工作流。读取案件笔记。
- 为指定受众生成：
client— 通俗语言，发生了什么/下一步/你做什么/联系我们internal— 程序态势、上次检查以来的进展、即将到来、需要指导老师意见、学生评估court— 按本地规则的正式状态报告格式
- 按受众进行指导路由（面向当事人和面向法院通常触发标记）。
/legal-clinic:status client
/legal-clinic:status internal
/legal-clinic:status court
Status：受众感知的案件摘要
目的
诊所产生大量的状态更新——给当事人、给指导老师、给共同代理人、给法院。同一个案件，同样的事实，完全不同的文件。本技能取案件笔记并为正确的读者生成正确的摘要。
加载上下文
~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md → 指导风格、通俗语言标准（用于面向当事人）、管辖地。
案件笔记用于获取事实。
受众模式
面向当事人
读者： 当事人。可能焦虑。可能不熟悉法律程序。阅读水平按 ~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md 通俗语言标准（默认初中水平）。
包含：
- 自上次收到诊所消息以来发生了什么
- 接下来会发生什么以及何时
- 他们（如有）需要做什么
- 如何联系诊所
不包含：
- 法律分析（他们不需要知道 IRAC）
- 他们案件中的弱点（除非是该进行那次对话的时候——而这个判断应由指导老师做出，不是状态更新）
- 法律术语
供学生的审查标签（非给当事人——发送前剥离）：
[AI辅助草稿 —— 需按插件配置经学生审查和指导步骤]
检查你所在法域的学生实践规则，确认法学学生签字的表述要求；部分法域要求特定形式。
[当事人姓名]：
我想向您更新一下您的案件情况。
**发生了什么：** [通俗语言。"我们已于[日期]向法院提交了您的答辩状"，而非"已呈交答辩文书。"]
**接下来是什么：** [什么以及何时。"法院安排在[日期][时间]开庭。您需要出庭。" 或："我们正在等待出租人的律师回复。这可能需要几周。"]
**您需要做什么：** [具体清晰。或："目前什么都不需要——需要时我们会告诉您。"]
**如何联系我们：** [诊所电话、工作时间、学生姓名]
[学生姓名]
法学学生，认证法律实习生
在[指导律师姓名]指导下
[诊所名称]
发送前： 向当事人发送状态更新是一项具有法律后果的行为。门控是 ~/.claude/plugins/config/claude-for-legal/legal-clinic/CLAUDE.md 中 ## 指导风格 描述的指导工作流程，由确认持证指导律师拥有诊所设置的 Part 0 身份检查强化。确认草稿已按指导协议（队列 / 标记 / 较轻触）审查，所有内部审查标签（[AI辅助草稿]、[待核实] 等）已从当事人可见版本中移除。
面向内部（供指导老师）
读者： 指导老师。懂法律。想知道案件处于什么状态以及学生需要他们什么。
包含：
- 程序状态（案件生命周期中的位置）
- 上次检查以来的进展
- 即将到来（截止日期、庭审）
- 需要指导老师意见的问题
- 学生评估（进展如何、关注点）
# 状态：[当事人] — [事项] — [日期]
**学生：** [姓名] | **程序态势：** [提交前 / 答辩状已提交 /
证据交换 / 等待开庭 / 等]
## 上次检查以来的进展
- [已完成事项]
## 即将到来
| 日期 | 事项 | 需要动作的截止日 |
|---|---|---|
| [日期] | [截止日期/庭审] | [日期] |
## 需要指导老师意见
- [具体问题或决策点]
## 学生评估
[进展如何。优势、关注点、策略问题。这是学生思考展示的地方。]
---
[AI辅助草稿 —— 学生尤其应修改评估部分；那是你的思考，不是笔记摘要]
面向法院
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.
- 1mo ago First seen · 186 lines · 80 tokens per session scan A b92b4373d1e5
status is a skill published in the GitHub repository zhou210712/claude-for-legal-ZH (238 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,902 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to client-intake, differing in 277 lines, and is treated as a copy.
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legal-hold
Issue, refresh, release, or report on legal holds — drafts the hold notice as .docx, updates legalhold fields in log.yaml, and calendars the next refresh. Use when the user says "issue a hold", "refresh hold", "release hold", or asks for a portfolio-wide hold status report.
specification-writing
A workflow for writing complete patent specifications from patent claims and an invention disclosure. It adapts the document to a chosen jurisdiction, such as the US, Europe, or China.
terms-of-service
Draft terms of service and a companion privacy notice matched to the product's form and feature modules, not legal advice, delivered as a Word document.
x-scorecard
OpenSSF Scorecard for assessing open source project security. Check security best practices and compliance. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.
ai-risk-management
Apply the NIST AI Risk Management Framework (AI RMF 1.0) and adjacent guidance to AI / ML systems — model lifecycle governance, fairness and bias evaluation, robustness, transparency, accountability, third-party model risk, monitoring for drift, and AI incident response. Broader than prompt-injection (which is the…