Legal-Agent-Skills: Instructions file for Claude Code

CLAUDE.md

Legal-Agent-Skills CLAUDE.md is an instructions file for Claude Code from code-lawyer/Legal-Agent-Skills. It costs 2,053 tokens per session, scanned A, original, MIT.

A set of repository instructions for Legal-Agent-Skills, a collection of Chinese legal skills for contract review, legal research, and filling document templates.

In plain words
What is it for?
It is for maintaining or creating the repository’s legal-agent skills while following its required structure and quality checks.
Why use it?
It explains the repository’s rules, including how skills must be packaged, how legal sources are checked, and which validation commands to run.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is code-lawyer/Legal-Agent-Skills's own configuration. It tells Claude Code how to work on Legal-Agent-Skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Legal-Agent-Skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to code-lawyer/Legal-Agent-Skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/code-lawyer/Legal-Agent-Skills/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/code-lawyer/Legal-Agent-Skills

Made for: Claude Code.

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Per session 2,053 This file is loaded in full into every session.
When invoked 2,053 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.02053 $0.02053
Opus 5 $0.01026 $0.01026
Sonnet 5 $0.00411 $0.00411
Haiku 4.5 $0.00205 $0.00205

Measured 12d ago against content hash d484d54be665, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

Legal-Agent-Skills CLAUDE.md 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.

CLAUDE.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

本仓库是什么

面向文件系统类 AI agent的一组中文法律执业级 Agent Skills。内容规则为主、工具代码为辅。 交付单元是整个 skill 文件夹,不是单个 SKILL.md——只交 SKILL.md 一个文件,agent 会读不到 references/rules/ 里的正文。当前有三个 skill:contract-review/(中美双法域合同审查)、 legal-research/(法律研究与类案检索)、document-fill/(按本案知识库给文书模板取证填充)。

先读:作者宪章(PRINCIPLES.md)

顶层 PRINCIPLES.md做 skill 时的最高原则(作者宪章),约束的是作者/你,不是终端 agent; 它不写进任何 SKILL.md 正文,skill 运行时不读它动手改任何 skill 或造新 skill 前先通读它, 并按四层原则(元层 M / 工程 E / 法律 L / 产品 P)自检。几条最常踩的:

  • E1 自包含:每个 skill 零依赖本库其他 skill,可单独下载使用;不建共享底座,需要相同内容就 各自复制一份。skill 内所有引用路径相对该 SKILL.md 目录解析,禁止越出本 skill 目录。
  • E3 只补模型做不到/会跳过的不要把 LLM 本就会的法学方法论(三段论、目的解释、IRAC、类推……) 写进 skill 去"提示"它——纯浪费 token。skill 的价值只在五处:①来源核验/防幻觉 ②不可靠的领域事实 (条号/阈值/最新司法解释状态/强制条款)③易跳步骤的强制函数 ④格式与法域行文惯例 ⑤工具编排。
  • L1 防幻觉第一:法条/案例绝不靠模型记忆;每条法律命题挂且仅挂一个来源标签。

宪章若需修订,改 PRINCIPLES.md 并在其《变更日志》追加一行起因。

常用命令

要求 Python 3.8+。

pip install -r requirements-dev.txt              # 装 python-docx + pytest(开发/测试栈)

# 结构校验——改动任一 skill 的 references/ 或 rules/ 后必跑,绿了才提交
python contract-review/validate.py               # 预期 ✅ 通过(退出码 0;有硬错误退 1)
python legal-research/validate.py                # 同上

# 单元测试
python -m pytest contract-review/scripts/test_redline_docx.py legal-research/tests/ -q
python -m pytest contract-review/scripts/test_redline_docx.py -q -k <关键字>   # 跑单个测试

CI(.github/workflows/ci.yml)在每次 push / PR 跑上述 validate + pytest 全部,作为合并前门禁; 打 tag 由 release-skill.yml 自动校验 + 打包 + 发 Release,校验不过不发布。

架构大图(跨文件才能看懂的部分)

渐进式披露是核心架构。 每个 skill 的 SKILL.md 只放常驻底线 + 按需读取索引;正文分层进 references/(法域中立骨架、输出模板、验证、终检门)与 rules/<法域>/(可插拔规则包)。agent 运行时 分阶段按需读取,既省 token 又保证深层规则不被跳过。validate.py行预算把这套结构钉死: SKILL.md ≤80 行(contract)/≤130(research),references 数字前缀文件 ≤260,_general.md ≤200, 领域卡 ≤150。改内容时别把该分层的东西塞回 SKILL.md。

三个 skill 边界互斥、彼此路由:合同相关 → contract-review;法律问题论证/类案检索 → legal-research;按本案知识库给文书模板取证填充 → document-fill(论证说理留空、路由回研究/起草)。 均不做起草论证、续约提醒、流程图。改一个 skill 的边界描述时,注意其余 skill 的路由指向要对得上。

Read the full file on GitHub · 92 lines

Changes

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.

  1. 12d ago First seen · 92 lines · 2,053 tokens per session scan A d484d54be665

Subscribe to this mod's changes

Legal-Agent-Skills CLAUDE.md is an instructions file published in the GitHub repository code-lawyer/Legal-Agent-Skills (2 stars, last pushed 20d ago), licensed MIT. It adds 2,053 tokens to every session, about $0.0103 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 2026-08-31.

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