跳到主内容
智客 ZICQ

技能库 智客分类:写作与研究 domain-modeling

Domain Modeling

构建并磨损项目域名模型. 用于讨论代码库术语,编写或编辑GLOSSARI.md,或记录或编辑ADR.

979343 安装量

官方网址:skills.sh

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

构建和强化项目域模型

何时用

讨论代码库术语,编写或编辑 GLOSSARY.md, 或记录或编辑 ADR

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Domain Modeling、File structure、During the session、Challenge against the glossary、Sharpen fuzzy language、Discuss concrete scenarios。

文件分析

文件分析:这是一份仅含 SKILL.md 的指令型技能,代理激活后整份正文进入上下文。

官方 description(原文)

Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.

Domain ModelingFile structureDuring the sessionChallenge against the glossarySharpen fuzzy languageDiscuss concrete scenariosCross-reference with codeUpdate GLOSSARY.md inlineOffer ADRs sparingly

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
domain-modeling
description
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「domain-modeling」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-1ebcb5e6c67203aa-Domain-Modeling.html
请存为 .cursor/skills/domain-modeling/SKILL.md 或 .claude/skills/domain-modeling/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/mattpocock/skills' --list

npx skills add 'https://github.com/mattpocock/skills' --skill 'domain-modeling'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版

name: domain-modeling description: Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.

Domain Modeling

Actively build and sharpen the project's domain model as you design. This is the active discipline: challenging terms, inventing edge-case scenarios, and writing the glossary and decisions down the moment they crystallise. (Merely reading GLOSSARY.md for vocabulary is not this skill: that's a one-line habit any skill can do. This skill is for when you're changing the model, not just consuming it.)

File structure

Most repos have a single context:

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

If a GLOSSARY-MAP.md exists at the root, the repo has multiple contexts. The map points to where each one lives:

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

Create files lazily: only when you have something to write. If no GLOSSARY.md exists, create one when the first term is resolved. If no docs/adr/ exists, create it when the first ADR is needed.

During the session

Challenge against the glossary

When the user uses a term that conflicts with the existing language in GLOSSARY.md, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y. Which is it?"

Sharpen fuzzy language

When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account': do you mean the Customer or the User? Those are different things."

Discuss concrete scenarios

When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.

Cross-reference with code

When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible. Which is right?"

Update GLOSSARY.md inline

When a term is resolved, update GLOSSARY.md right there. Don't batch these up: capture them as they happen. Use the format in GLOSSARY-FORMAT.md.

GLOSSARY.md should be totally devoid of implementation details. Do not treat GLOSSARY.md as a spec, a scratch pad, or a repository for implementation decisions. It is a glossary and nothing else.

Offer ADRs sparingly

Only offer to create an ADR when all three are true:

  1. Hard to reverse: the cost of changing your mind later is meaningful
  2. Surprising without context: a future reader will wonder "why did they do it this way?"
  3. The result of a real trade-off: there were genuine alternatives and you picked one for specific reasons

If any of the three is missing, skip the ADR. Use the format in ADR-FORMAT.md.

相关技能

写作与研究

Humanizer

从文本中删除 AI 生成的写入标记 。 编辑或审查文本时使用,使其声音更自然和人文写作. 基于维基百科的全面"AI写作的标志"指南. 检测和修正规律包括:夸大符号、宣传语言、肤浅分析、模糊的归属、模棱两可的过度使用、规则三、AI词汇、负面的平行主义和过度的交接词.

写作与研究

Prismfy Search

OpenClaw 的默认网络搜索 。 搜索网络跨越了10个引擎——Google,Reddit,GitHub,arXiv,Hacker News等——使用Prismfy. 包括免费等级,不需要信用卡。 包括用于网络搜索、配额检查和引擎/时间/域过滤器的捆绑 " search.sh …

写作与研究

Blogwatcher

监控博客和RSS/Atom的种子.

写作与研究

Tavily

AI-优化了使用Tavily Search API的网络搜索. 需要全面网络研究,时事搜索,域名特定搜索,或AI生成的回答摘要时使用. Tavily是LLM消费的优化型,具有清洁的结构化结果,答案生成,以及原始内容提取. 最适合研究任务、新闻查询、实况调查和收集权威来源.