核心域、支撑域、通用域 logo

核心域、支撑域、通用域

Organization
microwind
核心域、支撑域、通用域

按业务价值和差异化程度将子域分为核心域、支撑域和通用域,指导资源分配和技术决策。

Overview

Publishermicrowind
Repositoryai-skills
Skill name核心域、支撑域、通用域
Stars
93
Forks
25
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 microwind on GitHub. Read the source before you install it.

Installation

Install the 核心域、支撑域、通用域 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/microwind/ai-skills/tree/main/domain-driven-design/domain-types
  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/microwind/ai-skills.git /tmp/ai-skills
mkdir -p .claude/skills
cp -r /tmp/ai-skills/domain-driven-design/domain-types .claude/skills/microwind-66
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 核心域、支撑域、通用域 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 核心域、支撑域、通用域 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 核心域、支撑域、通用域 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.

核心域、支撑域、通用域 (Domain Types)

概述

DDD将子域按业务价值和差异化程度分为三类,指导技术投资和人力分配。

三种域的对比

维度核心域支撑域通用域
业务价值最高,竞争优势必要,但非差异化基础设施
复杂度通常最复杂中等可简可繁
投资策略最优人才,持续投入适度投入购买/外包
技术方案自研,DDD深度建模自研或轻度定制用现成方案
变更频率高(业务创新驱动)中低
代码质量最高标准良好标准够用即可

示例:在线教育平台

核心域(竞争优势):
├── 自适应学习引擎    → 根据学生表现调整教学路径
├── 课程推荐系统      → 个性化推荐
└── 学习效果评估      → 独特的评估算法

支撑域(必须有但不是差异化因素):
├── 课程管理          → 课程CRUD、章节管理
├── 学生管理          → 注册、信息维护
└── 订单管理          → 购买课程流程

通用域(所有同类平台都需要):
├── 用户认证          → 登录注册(用Auth0)
├── 支付处理          → 支付网关(用Stripe)
├── 文件存储          → 视频/文档(用AWS S3)
└── 邮件通知          → 发送邮件(用SendGrid)

示例:RabbitAdvisors 知识付费平台

来自 RabbitAdvisors 案例研究,展示一个真实 B 端业务的域分类:

核心域(决定平台竞争力):
├── 订单域 (Order)          → 交易转化率、金额准确性
└── 订阅域 (Subscription)    → 核心交付能力,订阅状态管理

支撑域(业务必需但非差异化):
├── 专栏域 (Column)          → 内容组织
├── 专栏报价域 (ColumnQuote)  → 定价管理
├── 金融域 (Payment)          → 支付对接
├── 签约域 (Contract)         → 作者签约流程
├── 佣金域 (Commission)       → 分成计算
├── 评论域 (Comment)         
└── 公告域 (Announcement)    

通用域(同类产品普遍需要):
├── 读者域 (Reader)          
├── 编辑域 (Editor)          
├── 作者域 (Author)          
├── 消息通知域 (Notification) 
└── 登录鉴权域 (Auth)         

设计洞察:

  • "用户"看起来是通用概念,但读者 / 编辑 / 作者在业务行为上差异巨大,更适合划分为 3 个独立领域模型,只在登录、个人信息等场景共享基础能力
  • 订阅域是核心域:订阅状态决定用户能否阅读内容,是产品交付的核心
  • 订单域是核心域:交易规则、支付失败补偿、优惠券等都是竞争力

子域到微服务的路径

业务价值分类        →   限界上下文划分      →    微服务拆分
(子域类型)              (一组相关子域)          (物理服务)

核心域 订阅           │                         │
核心域 订单           │─ 专栏订阅上下文  ──────▶ smart-classroom-subscription
通用域 读者           │

支撑域 专栏           │
支撑域 专栏报价       │─ 专栏信息上下文  ──────▶ smart-classroom-column
支撑域 评论/公告      │
通用域 编辑           │

支撑域 签约           │
支撑域 佣金           │─ 签约分佣上下文  ──────▶ smart-classroom-contract
通用域 作者           │

支撑域 金融           │─ 金融上下文      ──────▶ smart-classroom-finance

通用域 认证/通知      │─ 用户信息上下文  ──────▶ smart-classroom-user

技术决策指南

java
// 核心域:深度DDD建模,充血模型
public class LearningPath {
    private List<Module> modules;
    private StudentProfile profile;

    public Module recommendNext() {
        // 复杂的自适应算法 — 这是竞争优势
        return adaptiveEngine.selectOptimal(profile, modules);
    }
}

// 支撑域:简洁实现,不过度设计
public class CourseService {
    public Course create(CreateCourseRequest req) {
        Course course = new Course(req.getTitle(), req.getInstructor());
        return courseRepo.save(course);
    }
}

// 通用域:直接用第三方
// 不自己写认证系统,用 Auth0 SDK
Auth0Client auth = new Auth0Client(domain, clientId);

域类型可能变化

注意:域的分类不是永久的

示例演变:
- 支付处理原是通用域 → 公司决定做自己的钱包功能 → 变成核心域
- 推荐引擎原是核心域 → 行业都有了 → 变成通用域
- 客服系统原是支撑域 → 发现是留存关键 → 升级为核心域

→ 定期重新评估域分类

与其他DDD概念的关系

概念关系
领域划分域类型是划分后的分类标签
限界上下文核心域需要最精确的上下文边界
通用语言核心域需要最精确的通用语言

总结

核心:识别并保护核心域,这是你的竞争优势所在。

实践:核心域深度投入,支撑域适度投入,通用域买现成的。

Frequently asked questions

What does the 核心域、支撑域、通用域 AI skill do?

按业务价值和差异化程度将子域分为核心域、支撑域和通用域,指导资源分配和技术决策。

Why use 核心域、支撑域、通用域 on TypingMind?

Because you install it once and use it with any model. 核心域、支撑域、通用域 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 核心域、支撑域、通用域 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microwind/ai-skills/tree/main/domain-driven-design/domain-types. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use 核心域、支撑域、通用域?

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 核心域、支撑域、通用域?

As many as you like. As long as a model supports skills, you can use 核心域、支撑域、通用域 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 核心域、支撑域、通用域 AI skill free?

It is published on GitHub by microwind. 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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