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Dev Workflow

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xstongxue
dev-workflow

开发流程五步法。支持需求理解、方案设计、代码实现、代码审查、Bug 修复。当用户提到「需求分析」「方案设计」「代码实现」「代码审查」「理解需求」「技术设计」「开始写代码」「Review」「检查代码」「bug」「报错」「崩溃」「异常」「出错了」时使用。

Overview

Publisherxstongxue
Repositorybest-skills
Skill namedev-workflow
Stars
2.9K
Forks
201
Bundled files
22
LicenseApache-2.0
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.

  • 22 bundled files

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

  • Open source

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

Installation

Install the Dev Workflow 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.
  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/xstongxue/best-skills.git /tmp/best-skills
mkdir -p .claude/skills
cp -r /tmp/best-skills/skills/dev-workflow .claude/skills/dev-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dev Workflow 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 Dev Workflow 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 Dev Workflow 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.

开发流程五步法

需求理解 → 方案设计 → 代码实现 → 代码审查 → Bug 修复

Step 1:识别当前步骤

根据用户需求选择对应 reference 文件执行:

步骤文件触发关键词
需求理解requirement.md需求分析、理解需求、整理需求、帮我梳理
方案设计design.md方案设计、技术设计、架构设计、怎么实现
代码实现implementation.md代码实现、开始写代码、帮我实现、写一下
代码审查review.md代码审查、Review、检查代码、看看有没有问题
Bug 修复bug-fix.mdbug、报错、崩溃、异常、不工作、出错了、测试失败

Step 2:执行、输出与落盘

读取对应 reference 中的完整流程,按步骤执行,输出符合该阶段要求的交付物。

自动落盘(默认必须写入):

  • 需求理解docs/<feature>/01-需求理解.md
  • 方案设计docs/<feature>/02-方案设计.md

可选落盘(默认不写,仅当用户明确要求时才写入):

  • 代码审查docs/<feature>/03-代码审查.md
  • Bug 修复docs/<feature>/04-bug修复.md

落盘规则:

  • 目录为当前工作目录 docs/ 下,不存在则创建
  • 按功能划分子目录:能识别出功能(如登录、测试、部署等)就必须写入 docs/<feature>/,即使只有一个功能也不写入根目录;涉及多个功能时各建子目录,同一功能的全部文档归入同一子目录
  • 无法识别功能或跨功能全局性内容(如整体架构设计):写入 docs/通用/
  • <feature> 使用稳定标识(建议用功能英文名或代码目录名/包名,如 logindeploy,避免同义词混用)
  • 演进式更新(不追加):主文件永远是最新完整版,结构为 # 文档标题## 修订记录(表格:版本 | 日期 | 摘要)→ 本次完整正文
  • 首次写入:创建文件,修订记录写入 v1 | YYYY-MM-DD HH:mm | 初版
  • 再次写入:先将旧文件整体移入 docs/<feature>/archive/<原文件名>-v<N>-<YYYYMMDD>.md(同日多次归档加时分后缀),再重写主文件,修订记录表新增一行(版本号递增,摘要为一句话变更概括)
  • 若用户明确指定了其他文件路径,优先按用户指定路径写入
  • 可选维护 docs/功能索引.md 记录功能名与文档路径映射

注意事项

  • 每步完成后提示用户进入下一阶段
  • 上游缺失时:提示用户先完成前置步骤,或简要收集关键信息后继续

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 Dev Workflow AI skill do?

开发流程五步法。支持需求理解、方案设计、代码实现、代码审查、Bug 修复。当用户提到「需求分析」「方案设计」「代码实现」「代码审查」「理解需求」「技术设计」「开始写代码」「Review」「检查代码」「bug」「报错」「崩溃」「异常」「出错了」时使用。

Why use Dev Workflow on TypingMind?

Because you install it once and use it with any model. Dev Workflow 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 Dev Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xstongxue/best-skills/tree/main/skills/dev-workflow. 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 Dev Workflow?

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 Dev Workflow?

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

Is the Dev Workflow AI skill free?

Yes. It is published on GitHub by xstongxue under the Apache-2.0 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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