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Proj Analyze Design

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zhangloveyan
proj-analyze-design

技术方案设计与确认(阶段二)。基于已确认的需求,设计数据库、接口、代码结构,生成技术方案文档。

Overview

Publisherzhangloveyan
Repositorybackend-skill
Skill nameproj-analyze-design
Stars
102
Forks
31
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Proj Analyze Design 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/zhangloveyan/backend-skill/tree/main/.claude/skills/proj-analyze-design
  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/zhangloveyan/backend-skill.git /tmp/backend-skill
mkdir -p .claude/skills
cp -r /tmp/backend-skill/.claude/skills/proj-analyze-design .claude/skills/proj-analyze-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Proj Analyze Design 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 Proj Analyze Design 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 Proj Analyze Design 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.

技术方案设计(阶段二)

前置条件:用户已确认阶段一(/proj-analyze-req)的需求分析文档,且全流程任务文档已创建 目标:设计技术实现方案,明确数据库、接口、代码结构 产出:技术方案文档(用户确认后进入开发阶段)


执行流程

Step 0: 校验任务文档 → Step 1: 探索现有代码 → Step 2: 设计技术方案 → Step 3: 输出方案文档 → Step 4: 用户确认 → Step 5: 生成任务

Step 0: 校验任务文档

  • 确认全流程任务文档存在
  • 若缺失,先创建任务文档骨架并补齐流程状态与上下文快照

Step 1: 探索现有代码

在设计方案前,先了解项目现状:

探索内容目的
相关模块代码了解现有实现方式
类似功能实现参考已有模式
公共类和工具复用现有组件
数据库表结构了解关联关系

Step 2: 设计技术方案

2.1 数据库设计

表命名规范:

  • 表名:小写下划线,单数(如 sys_user, order_item)
  • 字段名:小写下划线(如 user_id, create_time)
  • 主键:id BIGINT AUTO_INCREMENT
  • 外键:{关联表}_id
  • 索引:idx_{表名}_{字段}

关键字检查(必须做):新增或重命名的表、字段禁止与目标 MySQL 版本的关键字完全同名(大小写不敏感,包含保留字和非保留关键字),不得用反引号规避。按 SQL 命名规范与校验方法 检查,并在技术方案中记录目标版本、校验来源、结果及改名映射。已有数据库的冲突名称先提交迁移方案,未经确认不得直接改名。

通用字段(每张业务表必须包含):

sql
id BIGINT AUTO_INCREMENT PRIMARY KEY,
del_flag TINYINT(1) DEFAULT 0 COMMENT '删除标记',
create_by VARCHAR(64) COMMENT '创建人',
create_time DATETIME DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
update_by VARCHAR(64) COMMENT '更新人',
update_time DATETIME COMMENT '更新时间'

2.2 接口设计规范

接口文档要求:

  • 完整参数:必须包含所有请求参数的类型、是否必填、示例值
  • 响应格式:提供完整的JSON响应示例,包含所有字段
  • 错误码:列出所有可能的错误码和说明
  • 业务场景:说明接口的使用场景和业务含义

2.3 枚举类设计规范

标准枚举格式:参考模板中的枚举类设计,必须包含getByCode和getMessageByCode方法

2.4 技术架构澄清

按需澄清原则:只在涉及相关技术时才需要澄清

常见澄清场景:

  • 消息/通知功能 → 澄清:推送服务 vs 前端轮询?
  • 实时数据展示 → 澄清:Redis vs 数据库?
  • 历史数据管理 → 澄清:永久保存 vs 定期清理?
  • 在线状态功能 → 澄清:实时更新机制?存储位置?

Step 3: 输出方案文档

在充分澄清后,使用模板输出技术方案文档。

模板文件:技术方案模板

保存位置:docs/design/{YYYYMMDD}_{中文模块名}_技术.md

注意:技术方案设计时如发现需求遗漏或变更,需同步更新需求文档。

同步更新任务文档:

  • 将“技术方案”状态标记为进行中/已完成
  • 在产物清单中记录技术方案文档路径
  • 更新上下文快照与下一步指令

Step 4: 用户确认

4.1 确认话术

输出技术方案后,必须使用以下话术请求确认:

以上是技术实现方案,请确认:
1. 数据库表结构和字段是否符合预期?
2. 接口设计是否满足需求?
3. 是否需要调整?

确认后我将开始编码开发。

4.2 用户反馈处理

用户反馈处理方式
"确认"/"没问题"/"可以"调用 /proj-task 拆分任务,开始开发
"字段需要调整xxx"修改表结构设计,再次确认
"接口需要增加xxx"补充接口设计,再次确认
"取消"/"不做了"结束流程

注意事项

  1. 前置检查 - 确保阶段一需求已确认,否则不能开始
  2. 参考现有 - 设计前先看项目已有实现,保持风格一致
  3. 命名规范 - 严格遵循 CLAUDE.md 命名规范
  4. 不要过度设计 - 按需求来,不主动加功能
  5. 确认再开发 - 方案确认前禁止创建/修改任何代码文件

Step 5: 生成任务(用户确认后)

用户确认技术方案后:

  1. 保存方案文档(中等/复杂需求):docs/design/{YYYYMMDD}_{中文模块名}_技术.md
  2. 生成任务清单:调用 /proj-task 创建任务
  3. 开始开发:按顺序 SQL → Entity → Mapper → DTO → Service → Controller
  4. 开发完成:调用 /proj-review 自检

同步更新任务文档:

  • 标记“方案确认”状态为已完成
  • 更新“下一步指令”为进入任务拆分

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 Proj Analyze Design AI skill do?

技术方案设计与确认(阶段二)。基于已确认的需求,设计数据库、接口、代码结构,生成技术方案文档。

Why use Proj Analyze Design on TypingMind?

Because you install it once and use it with any model. Proj Analyze Design 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 Proj Analyze Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhangloveyan/backend-skill/tree/main/.claude/skills/proj-analyze-design. 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 Proj Analyze Design?

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 Proj Analyze Design?

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

Is the Proj Analyze Design AI skill free?

Yes. It is published on GitHub by zhangloveyan 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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