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Normative Meaning Argumentation

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THUYRan
normative-meaning-argumentation

分析法律规范的目的、价值导向,以及事实应如何进入规范评价,判断涵摄的限度,需要适当区别于法律解释中的规范目的解释。

Overview

PublisherTHUYRan
RepositoryLegal-Skills-Chinese
Skill namenormative-meaning-argumentation
Stars
929
Forks
102
Bundled files
Instructions only
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by THUYRan on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/THUYRan/Legal-Skills-Chinese/tree/main/skills/Normative-Meaning-Argumentation
  4. 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.
2

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/THUYRan/Legal-Skills-Chinese.git /tmp/Legal-Skills-Chinese
mkdir -p .claude/skills
cp -r /tmp/Legal-Skills-Chinese/skills/Normative-Meaning-Argumentation .claude/skills/normative-meaning-argumentation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Normative Meaning Argumentation 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 Normative Meaning Argumentation 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 Normative Meaning Argumentation 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.

Skill Title

法律论证之规范意义解释,是指在法律适用过程中,不仅说明法律规范“是什么意思”,还要进一步论证该规范为何能够评价特定事实、评价到何种程度,以及事实是否落入该规范所欲调整的风险、利益或行为类型之中。该 skill 的重点不是抽象解释法律条文,而是在具体案件中建立“规范目的—事实特征—评价结论”之间的论证链条。

Capabilities

List what this skill can do:

  • Capability 1:识别法律规范的规范目的与价值导向。能够分析某一法律规范旨在保护何种利益、防止何种风险、维持何种法律秩序,并区分其主要目的、附随目的与制度背景。
  • Capability 2:判断案件事实是否具有规范相关性。能够从复杂事实中筛选出与规范目的有关的事实要素,判断哪些事实能够进入法律评价,哪些事实只是背景事实或情绪性事实。
  • Capability 3:论证事实涵摄的限度。能够分析案件事实是否落入规范的调整范围,判断是否存在扩大适用、限制适用或排除适用的理由,避免机械涵摄。
  • Capability 4:连接规范意义与裁判结论。能够围绕规范目的组织法律论证,使“适用该法条”或“不适用该法条”的结论具有说服力。
  • Capability 5:区别规范意义解释与规范目的解释。能够避免停留在“该条文目的是什么”的层面,而是进一步说明该目的如何在个案事实中发挥评价作用。

How to Use

Step-by-step instructions: 1.Step 1:确定待适用的法律规范。明确案件中可能适用的法条、规则或原则,并提取其构成要件、法律后果和制度位置。 2. Step 2:识别规范目的。分析该规范所保护的法益、所防止的风险、所维持的交易秩序或社会关系秩序。例如,某一规范是为了保护人格尊严、交易安全、信赖利益、弱者保护,还是为了控制行为风险。 3. Step 3:提炼规范评价对象。判断该规范真正评价的是什么。 4. Step 4:筛选案件中的规范相关事实。从案件事实中选出与规范目的直接相关的事实,排除与规范评价无关或关系较弱的事实。 5. Step 5:建立“规范目的—事实特征”的对应关系。说明案件事实为何触及该规范所关注的风险、利益或秩序问题。例如,某行为虽然形式上不完全符合典型样态,但实质上制造了规范所欲防止的风险。 6. Step 6:判断涵摄边界。分析该事实是否应当被纳入规范适用范围。如果纳入,说明理由;如果不纳入,说明为什么超出了规范目的、构成过度扩张或破坏体系协调。 7. Step 7:形成规范意义解释结论。输出一个清晰结论:在本案中,该规范应当如何理解、如何评价事实、是否支持最终法律结论。

Input Format

Describe expected input:

  • Format 1:法律条文 + 案件事实:适用于对某一具体案件进行法律论证。 示例:“请根据《民法典》第1032条,分析某人偷拍他人住宅内部是否构成隐私权侵权。”
  • Format 2:争议焦点 + 相关法条:适用于围绕某一争议问题展开规范评价。 示例: “争议焦点是:公开他人身份证号是否属于侵害隐私权?相关法条为《民法典》第1032条、第1034条。”
  • Format 3:裁判观点 + 需要检验的论证:适用于评估法院裁判理由是否充分。 示例:“法院认为该行为不构成隐私侵权,请从规范意义解释角度检验其说理是否充分。”
  • Format 4:论文观点 + 规范依据:适用于学术论文中的规范论证。 示例:“我想论证个人数据访问权具有人格权属性,请从规范意义解释角度展开。”

Output Format

Describe what will be produced:

  • Output 1:规范目的分析:说明相关规范的制度功能、保护利益、风险控制目标和价值导向。
  • Output 2:规范评价对象:说明该规范真正评价的是何种行为、状态、风险、利益冲突或法律关系。
  • Output 3:事实筛选与规范相关性判断:区分案件中的核心事实、辅助事实和无关事实,说明哪些事实能够进入规范评价。
  • Output 4:规范目的与案件事实的对应关系:论证案件事实如何触及或未触及该规范所关注的法益、风险或秩序。
  • Output 5:涵摄限度判断:判断该事实是否应纳入规范适用范围,并说明扩大适用、限制适用或排除适用的理由。
  • Output 6:规范意义解释结论:形成简明的法律论证结论,为后续利益衡量、类比论证、体系一致性论证或裁判结论提供基础。

Example Usage

Provide concrete examples: “分析《民法典》第1032条隐私权保护规范在‘公开他人身份证号’案件中的适用。”

Example output 1

  1. 规范目的:《民法典》第1032条旨在保护自然人的私人生活安宁和不愿为他人知晓的私密空间、私密活动、私密信息。其规范目的并非保护一切个人信息,而是保护与人格尊严、私人生活边界和个体不受干扰状态密切相关的信息利益。
  2. 规范评价对象:该规范评价的不是“信息是否被公开”这一事实本身,而是公开行为是否侵入个人私生活领域,是否破坏个人对私密信息的控制,是否足以造成私人生活安宁受损。
  3. 事实相关性:身份证号是否属于隐私,需要结合公开场景、公开范围、信息用途、是否与其他身份信息结合、是否可能导致现实侵扰等因素判断。单纯存在身份证号公开事实,并不当然等同于隐私侵权。
  4. 涵摄限度:如果身份证号公开足以使个人身份被识别,并进一步带来骚扰、冒用、歧视或其他私人生活风险,则该事实可以进入隐私权规范评价范围。反之,如果公开范围极小、信息已依法公开、且不存在私人生活侵扰风险,则不宜机械适用隐私权保护规范。
  5. 结论:对公开身份证号行为的评价,应以该行为是否触及隐私权规范所保护的私人生活边界为核心,而不能仅以“个人信息被公开”为由直接认定隐私权侵权。

Example request 2

“分析数据提供合同中数据质量瑕疵能否适用买卖合同中的物的瑕疵规则。”

Example output 2

  1. 规范目的:买卖合同中的物的瑕疵担保规则主要用于保障买受人取得符合约定或通常用途的标的物,其制度背景是有体物交付与所有权移转。该规范关注的是交付物在交付时是否具备约定品质、通常效用和交易安全。

  2. 规范评价对象:传统瑕疵担保规则评价的是有体物的质量状态,而数据提供合同中的核心问题往往不是物理质量缺陷,而是数据是否适合合同目的,包括合法性、准确性、完整性、时效性和可用性。

  3. 事实相关性:在数据交易中,数据可能持续更新、动态接入、反复加工,并依赖接口、格式、算法环境和使用场景。因此,与规范评价相关的事实不只是交付时的数据内容,还包括数据来源、处理过程、更新机制、接口稳定性和使用目的。

  4. 涵摄限度:规范意义解释要求将“质量不符合”理解为“履行不符合合同目的”,从而将评价中心从静态物的缺陷转向适约性障碍。

  5. 结论:数据质量瑕疵责任可以借鉴买卖合同瑕疵担保规则,但不能简单等同于物的瑕疵责任。其规范评价应围绕数据是否满足合同目的、使用场景和持续供给义务展开。

Best Practices

  1. 不要只解释法条含义,要说明法条如何评价案件事实。规范意义解释的关键不是“条文是什么意思”,而是“该条文为什么能够评价本案事实,以及评价到什么程度”。

2.结合体系位置进行解释。分析某一规范时,应注意其与相邻规范、上位原则和制度结构之间的关系,避免孤立解释。

Limitations

  • Limitation 1:不能替代完整的法律解释。该 skill 主要服务于个案论证,不能完全替代文义解释、体系解释、历史解释和目的解释等完整法律解释方法。

  • Limitation 2:不能单独决定案件结论。规范意义解释只能说明事实是否能够进入规范评价,最终结论还需要结合利益衡量、证明责任、法律后果、抗辩事由和体系协调等因素。

  • Limitation 3:容易被误用为价值判断。如果缺乏法条依据和制度背景,规范意义解释可能滑向抽象价值宣示。因此必须始终围绕具体规范展开。

Frequently asked questions

What does the Normative Meaning Argumentation AI skill do?

分析法律规范的目的、价值导向,以及事实应如何进入规范评价,判断涵摄的限度,需要适当区别于法律解释中的规范目的解释。

Why use Normative Meaning Argumentation on TypingMind?

Because you install it once and use it with any model. Normative Meaning Argumentation 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 Normative Meaning Argumentation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/THUYRan/Legal-Skills-Chinese/tree/main/skills/Normative-Meaning-Argumentation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Normative Meaning Argumentation?

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 Normative Meaning Argumentation?

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

Is the Normative Meaning Argumentation AI skill free?

It is published on GitHub by THUYRan. Check the repository for licensing terms. 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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