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/pdlc-code-gen

在已有服务 / 应用里按设计文档生成模块代码骨架(分层、接口、模型);加新服务用 /pdlc-add-service

From plugin
pdlc
1838 skills2 hooks

Claude Code

$ npx -y skills add kanfu-panda/pdlc-skills --skill pdlc-code-gen --agent claude-code

SKILL.md

pdlc-code-gen.SKILL.md
name: pdlc-code-gen
description: 在已有服务 / 应用里按设计文档生成模块代码骨架(分层、接口、模型);加新服务用 /pdlc-add-service
argument-hint: "<模板类型 | 目标目录>"
allowed-tools: Read, Write, Edit, Glob, Grep, Bash
layer: 3
stage: engineering
produces: []
requires: []
next_step: null
terminal_state: null

代码脚手架生成

<!-- @include templates/prompts/iron-law-tool.md(已内联于下方,无需另读) --> ⛔ **IRON LAW · 不可违反的硬门禁(工具型命令)**

本命令不是主链路上的阶段:**不追加 `history`,不改 `current_stage` / `next_step` / `last_phase_result`**,也不为此分配功能ID。以下规则不可协商:

1. **文件必须落盘**:正文要求创建的文件必须作为实际文件写入磁盘,不可仅在对话中输出(只要求在对话里输出的,照正文办)。 2. **自检必须执行**:产出后按本命令的自检项逐项核对,不得以"已经很好了"为由跳过。 3. **防循环**:修复只做一次,不递归。修不了的问题记进报告,继续往下走。

**违反任一条 = 立即中止当前命令,输出违规详情,等待人工介入。** <!-- @include-end templates/prompts/iron-law-tool.md -->

根据设计文档快速生成模块代码脚手架(骨架代码)。

工作流程

1. **阅读设计文档**: 阅读 `docs/02_design/api/` 和 `docs/02_design/database/` 下的设计文档 2. **确定目标服务**: 确认代码生成到哪个服务或应用 3. **生成代码骨架**: 按技术栈生成对应的代码文件

后端生成内容(按分层架构)

Java/Spring Boot

  • Controller(控制器层): 路由、参数校验、响应封装
  • Service(服务层): 业务逻辑接口和实现
  • Repository(数据层): 数据访问接口
  • DTO/VO/Entity: 数据传输对象、视图对象、实体类
  • 单元测试骨架

Go

  • Handler(处理器层): HTTP 路由处理
  • Service(服务层): 业务逻辑
  • Repository(仓储层): 数据访问
  • Model(模型层): 数据结构定义
  • 单元测试骨架

Python/FastAPI

  • Router(路由层): API 路由定义
  • Service(服务层): 业务逻辑
  • Repository(仓储层): 数据访问
  • Schema/Model: Pydantic 模型、ORM 模型
  • 单元测试骨架

Node.js

  • Controller(控制器层): 路由处理
  • Service(服务层): 业务逻辑
  • Model(模型层): 数据模型
  • Middleware(中间件): 通用中间件
  • 单元测试骨架

前端生成内容

  • 页面组件骨架
  • API 请求服务层
  • 类型定义(TypeScript)
  • 状态管理模块
  • 单元测试骨架

要求

<!-- @include templates/prompts/output-language.md(已内联于下方,无需另读) --> 🌐 **Output language for generated artifacts**

All generated artifacts (PRDs, design docs, code comments, review reports, test plans, deployment manuals, changelog entries, etc.) follow this policy:

1. **Default — match the conversation language exactly**:

  • 用户用中文与 Claude 对话 → 产中文文档、中文代码注释、中文报告
  • User talks to Claude in English → produce English artifacts
  • User talks in another language → produce artifacts in that language
  • **Never silently default to a fixed language regardless of the user's input.**

2. **Explicit override always wins**: when the user specifies a language for an artifact (e.g. "write the PRD in English", "用英文写 API 设计文档", "output the deploy doc in Japanese"), use that language for that artifact, regardless of conversation language.

3. **Mixed-language requirements**: if the user wants some artifacts in one language and others in a different language (common: Chinese PRD + English API docs for partners), honour each per-artifact instruction.

4. **Uncertain**: if you cannot reliably detect the conversation language, ask once before producing the first artifact.

This policy applies to **content** (prose, comments, headings). It does **not** override technical conventions like English variable names, English git commit subjects, or English error codes when the project's conventions require them. <!-- @include-end templates/prompts/output-language.md -->

  • 生成的代码要遵循 `docs/00_standards/coding/` 下的规范(未命中 → 提示 `consider /pdlc-standard add coding/<topic>`)
  • 方法体用 `// TODO: 待实现` 占位
  • 测试用例用 `// TODO: 补充测试逻辑` 占位
  • 生成后提示用户先运行 `/pdlc-tdd` 补充测试

生成目标: $ARGUMENTS

<!-- @include templates/prompts/handoff.md(已内联于下方,无需另读) -->

段四:交接(Handoff)

命令完成后必须输出以下格式的最终消息:

✅ <阶段名> 完成:<主要产出物路径>
📊 自检:<通过数>/<总数> 通过(若有未通过,附要点)
📦 状态快照:docs/.pdlc-state/<feature-id>.json
👉 下一步:/pdlc-<next_step>
   (如果有分叉)或 /pdlc-<alt>(条件:<选择依据>)

**规则:**

  • 主流程命令(写状态机的命令;下一跳见正文里「本命令的状态机取值」)必须显式输出"下一步",不可省略
  • 工具型命令(Layer 3)可以没有 `next_step`,此时输出 `👉 下一步:(本次流程结束,无后续)`
  • 分叉场景必须说明**选择条件**,例如"若需补充测试用例 → `/pdlc-tdd`;若测试已齐 → `/pdlc-review`"

<!-- @include-end templates/prompts/handoff.md -->

**本命令的 handoff 输出:**

✅ 代码脚手架 完成
📦 产出:(生成到目标服务/应用目录)
👉 下一步:(本次流程结束,无后续)
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Author: kanfu-panda Repo: github.com/kanfu-panda/pdlc-skills License: MIT pdlc-skills is built on one rule: an AI saying "done" doesn't count — exit codes do.

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Questions about pdlc-code-gen.

Which coding agents can use pdlc-code-gen?
pdlc-code-gen installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.