catlog22 360a2b9edc docs: 完善 UI 设计工作流,添加设计更新步骤
### 主要改进

**UI 设计完整工作流** - 从探索到实现的完整流程:
- **场景 2 更新**:ui-design → **update** → plan → execute(新增 update 步骤)
- 明确说明需要使用 `/workflow:ui-design:update` 更新头脑风暴工件
- 确保实现遵循批准的设计原型

**新增步骤说明**:
```bash
# 第 2 步:审查设计后更新概念设计
/workflow:ui-design:update --session <session-id> --selected-prototypes "login-v1,login-v2"
```

**工作流逻辑**:
1. **explore-auto**: 生成多个设计变体
2. **update**: 将选定的设计原型引用集成到头脑风暴工件
3. **plan**: 基于更新后的设计引用生成实现计划
4. **execute**: 执行实现

**为什么需要 update 步骤**:
- 将 UI 设计决策正式纳入项目规格
- 确保实现代码参考正确的设计原型
- 保持设计和实现的一致性
- 为后续的代码生成提供设计上下文

**双语文档同步**:
- 英文版:完整的 4 步工作流说明
- 中文版:相同流程的中文说明和提示

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-20 14:13:01 +08:00

🚀 Claude Code Workflow (CCW)

Version License Platform MCP Tools

Languages: English | 中文


Claude Code Workflow (CCW) transforms AI development from simple prompt chaining into a robust, context-first orchestration system. It solves execution uncertainty and error accumulation through structured planning, deterministic execution, and intelligent multi-model orchestration.

🎉 Latest: v4.6.2 - Documentation Optimization & /memory:load Command Refinement. See CHANGELOG.md for details.

📚 New to CCW? Check out the Getting Started Guide for a beginner-friendly 5-minute tutorial!


Core Concepts

CCW is built on a set of core principles that differentiate it from traditional AI development approaches:

  • Context-First Architecture: Pre-defined context gathering eliminates execution uncertainty by ensuring agents have the correct information before implementation.
  • JSON-First State Management: Task states live in .task/IMPL-*.json files as the single source of truth, enabling programmatic orchestration without state drift.
  • Autonomous Multi-Phase Orchestration: Commands chain specialized sub-commands and agents to automate complex workflows with zero user intervention.
  • Multi-Model Strategy: Leverages the unique strengths of different AI models (Gemini for analysis, Codex for implementation) for superior results.
  • Hierarchical Memory System: A 4-layer documentation system provides context at the appropriate level of abstraction, preventing information overload.
  • Specialized Role-Based Agents: A suite of agents (@code-developer, @test-fix-agent, etc.) mirrors a real software team to handle diverse tasks.

⚙️ Installation

For detailed installation instructions, please refer to the INSTALL.md guide.

🚀 Quick One-Line Installation

Windows (PowerShell):

Invoke-Expression (Invoke-WebRequest -Uri "https://raw.githubusercontent.com/catlog22/Claude-Code-Workflow/main/install-remote.ps1" -UseBasicParsing).Content

Linux/macOS (Bash/Zsh):

bash <(curl -fsSL https://raw.githubusercontent.com/catlog22/Claude-Code-Workflow/main/install-remote.sh)

Verify Installation

After installation, open Claude Code and check if the workflow commands are available by running:

/workflow:session:list

If the slash commands (e.g., /workflow:*) are recognized, the installation was successful.


🛠️ Command Reference

CCW provides a rich set of commands for managing workflows, tasks, and interacting with AI tools. For a complete list and detailed descriptions of all available commands, please see the COMMAND_REFERENCE.md file.

For a detailed technical specification of every command, see the COMMAND_SPEC.md.


🚀 Getting Started

The best way to get started is to follow the 5-minute tutorial in the Getting Started Guide.

Here is a quick example of a common development workflow:

  1. Start a Session:
    /workflow:session:start "Implement user login feature"
    
  2. Create a Plan:
    /workflow:plan "Implement JWT-based user login and registration"
    
  3. Execute the Plan:
    /workflow:execute
    

🤝 Contributing & Support

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

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JSON-driven multi-agent development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution
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