Litigation Analysis

Community

cat-xierluo

litigation-analysis

诉讼分析工具 - 判决书深度分析，生成上诉/再审决策支持

Overview

Publisher	cat-xierluo
Repository	`legal-skills`
Skill name	`litigation-analysis`
Stars	722
Forks	109
Bundled files	11
License	CC-BY-NC
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
11 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by cat-xierluo on GitHub. Read the source before you install it.

Installation

Install the Litigation Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/cat-xierluo/legal-skills/tree/main/skills/litigation-analysis
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/cat-xierluo/legal-skills.git /tmp/legal-skills
mkdir -p .claude/skills
cp -r /tmp/legal-skills/skills/litigation-analysis .claude/skills/litigation-analysis

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Litigation Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Litigation Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Litigation Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

litigation-analysis

版本: 1.3.2 最后更新: 2026-04-08 说明: 诉讼分析工具，支持起诉状、判决书和庭审笔录全流程分析

功能概述

本技能支持三种诉讼文档分析场景：

场景一：起诉状与证据分析（诉讼起点）

针对案件初期的起诉状和证据材料，进行快速评估和策略制定：

内部版：诉讼请求分析、事实主张梳理、证据评估、风险识别
客户版：案件情况说明、预期风险、补充证据建议

核心目标：快速评估案件基础，识别风险和证据缺口，制定初步策略

场景二：判决书分析（核心功能）

针对上级律师或客户发来的判决书（一审/二审），智能分析案件情况，生成三层递进输出：

内部版：面向主办律师，全面深入，专业论证，快速掌握核心要点
研究版：面向律师/研究人员，基于内部版识别法律问题，生成研究课题
客户版：面向非法律专业人士，基于内部版简化呈现，通俗易懂

核心目标：理解判决发生了什么，决定是否上诉/再审，帮助赢得客户/案子

场景三：庭审笔录分析

针对庭审结束后的笔录文字稿（可能来自录音转写、人工记录或法院系统导出），生成结构化的庭审复盘分析报告：

争议焦点归纳：法庭归纳的核心争议焦点
证据质证情况：双方证据及质证意见
法官提问分析：法官关键提问及可能透露的倾向
时限事项整理：法官要求与时限安排
策略建议：下一步诉讼策略和行动计划

核心目标：庭审复盘、团队沟通、策略调整、时限管理

核心定位

主要处理对象

判决书（一审判决、二审判决）- 结构化深度抽取

这是本技能的核心处理对象
通常 100-500 行，信息密集
需要完整的事实认定链条、法律逻辑分析、判决结果解读

辅助参考文件

当客户或上级律师同时提供其他文件时，可作为辅助参考：

起诉状：了解原告主张和诉讼请求
上诉状：了解上诉理由和新证据
答辩状：了解对方抗辩和反驳证据
庭审笔录：了解庭审过程和质证情况（详见庭审笔录处理）

注意：起诉状、上诉状、答辩状等不是主要处理对象，仅作为辅助参考，帮助理解判决书内容。庭审笔录可独立处理生成庭审复盘分析报告。

核心特性

双场景支持：判决书分析（核心）+ 庭审笔录分析
辅助参考整合：可同时处理起诉状、上诉状、答辩状等辅助文件
结构化深度抽取：针对判决书/庭审笔录的规范结构进行完整抽取
递进输出体系：判决书三层输出（内部版→研究版→客户版），庭审笔录单层输出（复盘分析报告）
决策支持导向：为上诉/再审决策或庭审策略调整提供专业支持

架构设计

通用处理框架

适用范围: 所有诉讼案件

核心能力:

判决书结构化深度抽取（事实认定、法律适用、判决结果）
辅助文件常规分析（起诉状、上诉状、答辩状）
争议焦点识别与法院认定分析
上诉/再审策略建议
胜诉可能性评估

专用领域扩展

现有领域:

知识产权与不正当竞争 (参见 references/domains/01-ip-case-dimensions.md)
- 专利权纠纷：技术特征对比、创造性评估
- 商标权纠纷：近似性判断、混淆可能性
- 著作权纠纷：实质性相似、独创性
- 商业秘密：秘密性、保密措施
- 不正当竞争：虚假宣传、商业诋毁
- 特许经营：信息披露、欺诈认定

未来可扩展领域:

劳动法、公司法、合同法、侵权法等

使用方式

基于文件


/litigation-analysis @判决书路径.md

同时提供辅助文件


/litigation-analysis @判决书路径.md
同时提供：起诉状、答辩状等辅助文件

直接粘贴


/litigation-analysis
[粘贴判决书内容]

输出结构

生成顺序: 内部版 → 研究版 → 客户版（按依赖关系递进）


[案件编号]/
├── [案件编号] 深度分析报告内部版.md  ← 判决书深度分析
├── [案件编号] 研究课题清单.md        ← 识别的法律问题
└── [案件编号] 案件概览客户版.md      ← 简化呈现

内部版核心:

📋 核心要点速览：2-3分钟快速掌握案件全貌
事实与证据：完整的事实认定链条
争议焦点与法院认定：逐一对应分析
判决结果详解：判决主文、诉讼费用、上诉权利
法律分析与策略建议：上诉/再审可行性评估
裁判要点与实务启示：关键裁判规则、实务启示

参考文档

核心处理文档

起诉状与证据分析 - 诉讼起点的快速评估
- 识别特征、抽取规范、处理流程、输出侧重
一审判决书处理 - 一审判决的完整处理流程
- 识别特征、抽取规范、处理流程、输出侧重
二审判决书处理 - 二审判决的完整处理流程
- 识别特征、抽取规范、对比分析、输出侧重

庭审笔录处理文档

庭审笔录处理 - 庭审笔录的完整处理流程
- 识别特征、抽取规范、处理流程、输出格式
- 生成庭审复盘分析报告，包含争议焦点、证据质证、法官提问、策略建议等

输出文档

客户版模板 - 非法律专业人士通俗呈现
研究版模板 - 研究课题清单生成
内部版模板 - 专业深度分析报告

可视化

可视化指南 - Mermaid 图表生成规范与示例
- 当事人关系图、案件时间轴、争议焦点关系图、上诉策略决策图、侵权比对图

领域扩展

领域扩展指南 - IP/不正当竞争等专用分析维度

诉讼分析工具 - 聚焦判决书，支持上诉/再审决策

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Litigation Analysis AI skill do?

诉讼分析工具 - 判决书深度分析，生成上诉/再审决策支持

Why use Litigation Analysis on TypingMind?

Because you install it once and use it with any model. Litigation Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Litigation Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cat-xierluo/legal-skills/tree/main/skills/litigation-analysis. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Litigation Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Litigation Analysis?

As many as you like. As long as a model supports skills, you can use Litigation Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Litigation Analysis AI skill free?

Yes. It is published on GitHub by cat-xierluo under the CC-BY-NC license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

litigation-analysis

功能概述

场景一：起诉状与证据分析（诉讼起点）

场景二：判决书分析（核心功能）

场景三：庭审笔录分析

核心定位

主要处理对象

辅助参考文件

核心特性

架构设计

通用处理框架

专用领域扩展

使用方式

基于文件

同时提供辅助文件

直接粘贴

输出结构

参考文档

核心处理文档

庭审笔录处理文档

输出文档

可视化

领域扩展

Bundled files

Frequently asked questions

Related AI Skills

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