three-tomato

name	three-tomato
description	将需求文档转换为多端原生开发代码，支持 Android、iOS、鸿蒙、小程序、快应用、H5、Web、macOS、Windows 等 17 个平台。原生优先，AI 友好技术栈。
license	MIT

Three-Tomato

将需求文档转换为多端原生开发代码，支持 Android、iOS、鸿蒙、小程序、快应用、H5、Web、macOS、Windows 等 17 个平台。

核心原则：原生优先，AI 友好技术栈（数据集大、文档丰富）

Overview

This skill enables AI Agents to analyze requirement documents and generate native platform-specific code using AI-friendly tech stacks with large training datasets.

Supported Platforms

Platform	Code	Language/Framework	AI-Friendly Reason
原生移动端
Android	android	Kotlin + Jetpack Compose	Kotlin 数据集大，Compose 声明式 UI
iOS	ios	Swift + SwiftUI	Swift 现代语法，SwiftUI 声明式
HarmonyOS	harmony	ArkTS + ArkUI	TypeScript 超集，AI 熟悉
小程序
WeChat Mini Program	wechat-mp	TypeScript + 原生 WXML	TS 类型安全，文档丰富
Alipay Mini Program	alipay-mp	TypeScript + 原生 AXML	同上
Baidu Mini Program	baidu-mp	TypeScript + 原生 Swan	同上
Quick App	quick-app	TypeScript	类 Vue 语法
Web
H5 Mobile	h5	TypeScript + React	React 优先，数据集最大
Web Desktop	web	TypeScript + React + Next.js	SSR/SSG，企业级首选
桌面原生
macOS	macos	Swift + SwiftUI	原生 Apple 生态
Windows	windows	C# + WinUI 3	.NET 生态成熟，AI 友好
跨端移动
Flutter	flutter	Dart + Riverpod	高性能，声明式 UI
React Native	react-native	TypeScript + Zustand	React 生态，AI 友好
Uni-app	uni-app	Vue 3 + TypeScript	一套代码多端运行
Taro	taro	React + TypeScript	京东出品，React 生态
跨端桌面
Electron	electron	React + TypeScript	Web 技术栈，成熟稳定
Tauri	tauri	Rust + React	高性能，体积小

Trigger Commands

Code Generation

🤖 "transform to [platform]"
🤖 "generate [platform] code"
🤖 "convert requirement to multi-platform"
🤖 "create platform specs"
🤖 "转换为[平台]代码"
🤖 "生成多端代码"

Self-Evolution

🧬 "3T evolve" / "3T 总结归纳进化"
🧬 "3T log issue [description]" / "3T 记录问题 [描述]"
🧬 "3T show evolution log" / "3T 查看进化日志"

Workflow

Evolution Workflow (3T evolve / 3T 总结归纳进化)

When 3T evolve command is triggered, AI Agent executes:

Step 1: Collect Feedback

1. Scan .three-tomato/feedback/issues/ for issue records
2. Analyze compile/runtime errors in .three-tomato/output/
3. Identify patterns from user's manual code fixes

Step 2: Categorize Issues

1. Group by platform (Android/iOS/Mini Programs, etc.)
2. Group by type (syntax error/API changes/best practices/architecture)
3. Calculate issue frequency

Step 3: Update Knowledge

1. Update references/patterns/known-issues.yaml - known issues database
2. Update references/patterns/best-practices.yaml - best practices
3. Update platform-specific plugins/[platform]-generator/PLUGIN.md
4. Log changes to .three-tomato/evolution/changelog.md

Step 4: Validate Improvements

1. Generate test cases for high-frequency issues
2. Verify improved templates resolve the issues
3. Output evolution report to .three-tomato/evolution/reports/

---

Phase 1: Requirement Analysis

1. Read requirement document from .three-tomato/requirements/ or specified path
2. Parse and extract:
   • Feature specifications
   • UI/UX requirements
   • Data models
   • API interfaces
   • Business logic flows

Phase 2: Platform Selection

1. Read .three-tomato/config.yaml for target platforms
2. Check enabled plugins in plugins/_registry.yaml
3. Determine output platforms based on user command or config

Phase 3: Code Generation

For each target platform:

1. Load platform-specific templates from references/templates/[platform]/
2. Apply tech stack configurations
3. Generate:
   • Project structure
   • UI components
   • Data models
   • API clients
   • Business logic
   • Platform-specific configurations

Phase 4: Output & Validation

1. Write generated code to .three-tomato/output/[platform]/
2. Generate comparison matrix
3. Create migration guides between platforms

Configuration

Read configuration from .three-tomato/config.yaml:

# Target platforms to generate
platforms:
  - android
  - ios
  - wechat-mp
  - h5

# AI-Friendly Tech Stack (原生优先，数据集大)
tech_stack:
  android:
    language: kotlin              # AI 数据集大
    ui: compose                   # 声明式，AI 友好
    architecture: mvvm
    di: hilt
    network: retrofit + okhttp
    async: coroutines
    
  ios:
    language: swift               # 现代语法，AI 熟悉
    ui: swiftui                   # 声明式 UI
    architecture: mvvm
    network: urlsession           # 原生优先
    async: async-await
    
  harmony:
    language: arkts               # TypeScript 超集
    ui: arkui
    architecture: mvvm
    
  wechat-mp:
    language: typescript          
                  
    
  
     
     
    
  
     
     
    
  
     
    
  
     
                   
     
     
    
  
     
                   
             
       
     
    
  
     
     
     
    
  
                   
                         
     



   
   
   
   

Plugin System

Hook Points

Plugins can extend functionality at these hooks:

• before_analyze - Pre-process requirement documents
• after_analyze - Post-process extracted requirements
• before_generate - Modify generation parameters
• on_generate - Custom code generation logic
• after_generate - Post-process generated code
• on_export - Custom export formats

Plugin Commands

📋 "list platform plugins"
📦 "install plugin <source>"
✅ "enable plugin <name>"
❌ "disable plugin <name>"

Built-in Plugins

Plugin	Description
原生平台
android-generator	Android 原生 (Kotlin + Compose)
ios-generator	iOS 原生 (Swift + SwiftUI)
harmony-generator	HarmonyOS (ArkTS + ArkUI)
wechat-mp-generator	微信小程序 (TypeScript)
alipay-mp-generator	支付宝小程序 (TypeScript)
baidu-mp-generator	百度智能小程序 (TypeScript)
quick-app-generator	快应用 (TypeScript)
h5-generator	H5 移动端 (React + TypeScript)
web-generator	Web 桌面端 (Next.js + React)
macos-generator	macOS 原生 (Swift + SwiftUI)
windows-generator	Windows 原生 (C# + WinUI 3)
跨端框架
flutter-generator	Flutter (Dart + Riverpod)
rn-generator	React Native (TypeScript + Zustand)
uni-app-generator	Uni-app (Vue 3 + TypeScript)
taro-generator	Taro (React + TypeScript)
electron-generator	Electron (React + TypeScript)
tauri-generator	Tauri (Rust + React)
工具类
api-sync	跨平台 API 定义同步
ui-converter	UI 组件跨平台转换
i18n-sync	国际化资源同步
diff-report	平台差异报告生成

Output Structure

.three-tomato/
├── config.yaml              # Main configuration
├── requirements/            # Input requirement documents
│   ├── PRD.md              # Product requirement document
│   ├── api.yaml            # API specifications
│   └── ui-specs/           # UI design specs
├── cache/                   # Incremental cache
├── output/                  # Generated code
│   ├── android/            # Kotlin + Compose
│   ├── ios/                # Swift + SwiftUI
│   ├── harmony/            # ArkTS + ArkUI
│   ├── wechat-mp/          # TypeScript 原生
│   ├── alipay-mp/          # TypeScript 原生
│   ├── baidu-mp/           # TypeScript 原生
│   ├── quick-app/          # TypeScript
│   ├── h5/                 # React + TypeScript
│   ├── web/                # Next.js + React
│   ├── macos/              # Swift + SwiftUI
│   ├── windows/            # C# + WinUI 3
│   └── _shared/            # 共享资源
│       ├── models/         # 数据模型定义
│       ├── api/            # API 接口定义
│       └── assets/         # 共享资源文件
├── reports/                 # Analysis reports
│   ├── comparison.md       # Platform comparison
│   ├── migration.md        # Migration guide
│   └── compatibility.md    # Compatibility matrix
└── i18n/                    # Multi-language docs
    ├── en/
    └── zh/

Important Instructions

For AI Agent:

1. Always read config first: Check .three-tomato/config.yaml before generation
2. Respect tech stack: Use configured frameworks and libraries
3. Maintain consistency: Ensure data models and API calls are consistent across platforms
4. Platform idioms: Follow each platform's best practices and conventions
5. Protocol Retention:
   • If requirement/legacy uses gRPC:
     • Supported Platforms (iOS, Android, Windows, macOS, Flutter): MUST use gRPC to maintain high performance and type safety.
     • Restricted Platforms (Mini Programs, H5): Fallback to HTTP/JSON (via Envoy/Gateway).
   • If requirement uses REST/GraphQL: Use standard HTTP clients.
6. Incremental updates: Only regenerate changed parts using cache
7. Preserve user content: Content marked with <!-- user-content --> must not be overwritten

Code Quality Standards:

• Follow platform-specific coding guidelines
• Include proper error handling
• Add necessary comments (in configured language)
• Generate unit tests when include_tests: true
• Create platform-specific README with setup instructions

Cross-Platform Consistency:

• Unified data model definitions
• Consistent API interface naming
• Shared business logic documentation
• Synchronized i18n resources

References

• Templates: references/templates/
• Prompts: references/prompts/
• Examples: references/examples/
• Platform Guides: docs/platforms/

Version

• Skill Version: 1.0.1
• Last Updated: 2026-01-30
• Author: three-tomato