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Domain Modeling

Community
FeatherHunter
domain-modeling

构建并打磨项目的领域模型。当讨论代码库术语、编写或修改 GLOSSARY.md、记录或修改 ADR 时使用。

Overview

PublisherFeatherHunter
Repositorydsh-mattpocock-skills-deck
Skill namedomain-modeling
Stars
263
Forks
22
Bundled files
2
LicenseMIT
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Domain Modeling 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/FeatherHunter/dsh-mattpocock-skills-deck/tree/main/package/bundled-skills-zh/domain-modeling
  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/FeatherHunter/dsh-mattpocock-skills-deck.git /tmp/dsh-mattpocock-skills-deck
mkdir -p .claude/skills
cp -r /tmp/dsh-mattpocock-skills-deck/package/bundled-skills-zh/domain-modeling .claude/skills/domain-modeling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Domain Modeling 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 Domain Modeling 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 Domain Modeling 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.

领域建模

在设计的过程中主动构建并打磨项目的领域模型。这是一项主动的实践:质疑术语、构想边界场景,并在术语与决策一旦成形的当下就把词汇表和决策写下来。(仅仅为了查词而阅读 GLOSSARY.md 不算这项技能:那只是一句话就能带过的习惯,任何技能都做得到。这项技能用在你要改变模型的时候,而不只是使用模型的时候。)

文件结构

大多数仓库只有一个上下文:

/
├── GLOSSARY.md
├── docs/
│   └── adr/
│       ├── 0001-event-sourced-orders.md
│       └── 0002-postgres-for-write-model.md
└── src/

如果根目录下存在 GLOSSARY-MAP.md,这个仓库就有多个上下文。这张地图指出每个上下文各自放在哪里:

/
├── GLOSSARY-MAP.md
├── docs/
│   └── adr/                          ← system-wide decisions
├── src/
│   ├── ordering/
│   │   ├── GLOSSARY.md
│   │   └── docs/adr/                 ← context-specific decisions
│   └── billing/
│       ├── GLOSSARY.md
│       └── docs/adr/

按需创建文件:只在确实有东西要写的时候才建。如果还没有 GLOSSARY.md,就在第一个术语定下来时创建一个。如果还没有 docs/adr/,就在需要第一条 ADR 时创建它。

会话期间

对照词汇表提出质疑

当用户使用的术语与 GLOSSARY.md 里既有的说法冲突时,立刻指出来。「你的词汇表把“cancellation”定义为 X,但你似乎想说的是 Y。到底是哪一个?」

打磨含糊的说法

当用户使用含糊或一词多义的词时,提出一个精确的规范术语。「你在说“account”:你指的是 Customer 还是 User?这是两回事。」

讨论具体场景

当讨论到领域关系时,用具体的场景给它们做压力测试。构想一些触及边界情况的场景,逼用户把概念之间的界线说清楚。

与代码交叉核对

当用户说明某件事是怎么运作的,去核对代码是否与之相符。如果你发现矛盾,就把它摆出来:「你的代码会取消整张 Order,但你刚说部分取消是可能的。哪个才是对的?」

就地更新 GLOSSARY.md

当一个术语定下来时,就当场更新 GLOSSARY.md。不要攒着一起改:事情发生的时候就记下来。使用 GLOSSARY-FORMAT.md 里的格式。

GLOSSARY.md 里应当完全没有实现细节。不要把 GLOSSARY.md 当成规格说明、草稿纸,或实现决策的存放处。它是词汇表,仅此而已。

谨慎地提议写 ADR

只有当以下三条同时成立时,才提议创建 ADR:

  1. 难以逆转:日后改变主意的代价不小
  2. 没有上下文会让人意外:未来的读者会琢磨「他们当初为什么这么做?」
  3. 真正权衡后的结果:当时确实有别的选择,而你出于具体理由选了其中一个

三条里缺任何一条,就跳过 ADR。使用 ADR-FORMAT.md 里的格式。

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 Domain Modeling AI skill do?

构建并打磨项目的领域模型。当讨论代码库术语、编写或修改 GLOSSARY.md、记录或修改 ADR 时使用。

Why use Domain Modeling on TypingMind?

Because you install it once and use it with any model. Domain Modeling 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 Domain Modeling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FeatherHunter/dsh-mattpocock-skills-deck/tree/main/package/bundled-skills-zh/domain-modeling. 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 Domain Modeling?

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 Domain Modeling?

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

Is the Domain Modeling AI skill free?

Yes. It is published on GitHub by FeatherHunter under the MIT 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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