Files
Claude-Code-Workflow/GETTING_STARTED.md
catlog22 02ee426af0 Refactor UI Design Commands: Replace /workflow:ui-design:update with /workflow:ui-design:design-sync
- Deleted the `list` command for design runs.
- Removed the `update` command and its associated documentation.
- Introduced `design-sync` command to synchronize finalized design system references to brainstorming artifacts.
- Updated command references in `COMMAND_REFERENCE.md`, `GETTING_STARTED.md`, and `GETTING_STARTED_CN.md` to reflect the new command structure.
- Ensured all related documentation and output styles are consistent with the new command naming and functionality.
2025-11-15 16:30:40 +08:00

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# 🚀 Claude Code Workflow (CCW) - Getting Started Guide
Welcome to Claude Code Workflow (CCW) v5.0! This guide will help you get up and running in 5 minutes and experience AI-driven automated software development with our streamlined, dependency-free workflow system.
**Project Repository**: [catlog22/Claude-Code-Workflow](https://github.com/catlog22/Claude-Code-Workflow)
> **🎉 What's New in v5.0**: Less is more! We've removed external MCP dependencies and simplified workflows. CCW now uses standard tools (ripgrep/find) for better stability and performance. The brainstorming workflow focuses on role analysis for clearer planning.
---
## ⏱️ 5-Minute Quick Start
Let's build a "Hello World" web application from scratch with a simple example.
### Step 1: Install CCW
First, make sure you have installed CCW according to the [Installation Guide](INSTALL.md).
### Step 2: Create an Execution Plan (Automatically Starts a Session)
Now, tell CCW what you want to do. CCW will analyze your request and automatically generate a detailed, executable task plan.
```bash
/workflow:plan "Create a simple Express API that returns Hello World at the root path"
```
> **💡 Note**: `/workflow:plan` automatically creates and starts a workflow session. No need to manually run `/workflow:session:start`. The session will be auto-named based on your task description, e.g., `WFS-create-a-simple-express-api`.
This command kicks off a fully automated planning process, which includes:
1. **Context Gathering**: Analyzing your project environment.
2. **Agent Analysis**: AI agents think about the best implementation path.
3. **Task Generation**: Creating specific task files (in `.json` format).
### Step 3: Execute the Plan
Once the plan is created, you can command the AI agents to start working.
```bash
/workflow:execute
```
You will see CCW's agents (like `@code-developer`) begin to execute tasks one by one. It will automatically create files, write code, and install dependencies.
### Step 4: Check the Status
Want to know the progress? You can check the status of the current workflow at any time.
```bash
/workflow:status
```
This will show the completion status of tasks, the currently executing task, and the next steps.
---
## 🧠 Core Concepts Explained
Understanding these concepts will help you use CCW more effectively:
- **Workflow Session**
> Like an independent sandbox or project space, used to isolate the context, files, and history of different tasks. All related files are stored in the `.workflow/WFS-<session-name>/` directory.
- **Task**
> An atomic unit of work, such as "create API route" or "write test case." Each task is a `.json` file that defines the goal, context, and execution steps in detail.
- **Agent**
> An AI assistant specialized in a specific domain. For example:
> - `@code-developer`: Responsible for writing and implementing code.
> - `@test-fix-agent`: Responsible for running tests and automatically fixing failures.
> - `@ui-design-agent`: Responsible for UI design and prototype creation.
> - `@cli-execution-agent`: Responsible for autonomous CLI task handling (v4.5.0+).
- **Workflow**
> A series of predefined, collaborative commands used to orchestrate different agents and tools to achieve a complex development goal (e.g., `plan`, `execute`, `test-gen`).
---
## 🛠️ Common Scenarios
### Scenario 1: Quick Feature Development
For simple, well-defined features, use the direct "plan → execute" pattern:
```bash
# Create plan (auto-creates session)
/workflow:plan "Implement JWT-based user login and registration"
# Execute
/workflow:execute
```
> **💡 Note**: `/workflow:plan` automatically creates a session. You can also manually start a session first with `/workflow:session:start "Feature Name"`.
### Scenario 2: UI Design Exploration
For UI-focused projects, start with design exploration before implementation: **ui-design → update → plan → execute**
```bash
# Step 1: Generate UI design variations (auto-creates session)
/workflow:ui-design:explore-auto --prompt "A modern, clean admin dashboard login page"
# Step 2: Review designs in compare.html, then sync design system to brainstorming artifacts
/workflow:ui-design:design-sync --session <session-id> --selected-prototypes "login-v1,login-v2"
# Step 3: Generate implementation plan with design references
/workflow:plan
# Step 4: Execute the implementation
/workflow:execute
```
> **💡 Tip**: The `update` command integrates selected design prototypes into brainstorming artifacts, ensuring implementation follows the approved designs.
### Scenario 3: Complex Feature with Multi-Agent Brainstorming
For complex features requiring thorough analysis, use the complete workflow: **brainstorm → plan → execute**
```bash
# Step 1: Multi-agent brainstorming (auto-creates session)
/workflow:brainstorm:auto-parallel "Design a real-time collaborative document editing system with conflict resolution"
# Optional: Specify number of expert roles (default: 3, max: 9)
/workflow:brainstorm:auto-parallel "Build scalable microservices platform" --count 5
# Step 2: Generate implementation plan from brainstorming results
/workflow:plan
# Step 3: Execute the plan
/workflow:execute
```
**Brainstorming Benefits**:
- **Auto role selection**: Analyzes your topic and selects 3-9 relevant expert roles (system-architect, ui-designer, product-manager, etc.)
- **Parallel execution**: Multiple AI agents analyze simultaneously from different perspectives
- **Comprehensive specification**: Generates integrated requirements and design document
**When to Use Brainstorming**:
- Complex features requiring multiple perspectives
- Architectural decisions with significant impact
- When you need thorough requirements before implementation
### Scenario 4: Quality Assurance - Action Plan Verification
After planning, validate your implementation plan for consistency and completeness:
```bash
# After /workflow:plan completes, verify task quality
/workflow:action-plan-verify
# The command will:
# 1. Check requirements coverage (all requirements have tasks)
# 2. Validate task dependencies (no circular or broken dependencies)
# 3. Ensure synthesis alignment (tasks match architectural decisions)
# 4. Assess task specification quality
# 5. Generate detailed verification report with remediation todos
```
**The verification report includes**:
- Requirements coverage analysis
- Dependency graph validation
- Synthesis alignment checks
- Task specification quality assessment
- Prioritized remediation recommendations
**When to Use**:
- After `/workflow:plan` generates IMPL_PLAN.md and task files
- Before starting `/workflow:execute`
- When working on complex projects with many dependencies
- When you want to ensure high-quality task specifications
**Benefits**:
- Catches planning errors before execution
- Ensures complete requirements coverage
- Validates architectural consistency
- Identifies resource conflicts and skill gaps
- Provides actionable remediation plan with TodoWrite integration
### Scenario 6: Bug Fixing
Quick bug analysis and fix workflow:
```bash
# Analyze the bug
/cli:mode:bug-index "Incorrect success message with wrong password"
# Claude will analyze and then directly implement the fix based on the analysis
```
---
## 🔧 Workflow-Free Usage: Standalone Tools
Beyond the full workflow mode, CCW provides standalone CLI tools and commands suitable for quick analysis, ad-hoc queries, and routine maintenance tasks.
### Direct CLI Tool Invocation
CCW supports direct invocation of external AI tools (Gemini, Qwen, Codex) through a unified CLI interface without creating workflow sessions.
#### Code Analysis
Quickly analyze project code structure and architectural patterns:
```bash
# Code analysis with Gemini
/cli:analyze --tool gemini "Analyze authentication module architecture"
# Code quality analysis with Qwen
/cli:analyze --tool qwen "Review database model design for best practices"
```
#### Interactive Chat
Direct interactive dialogue with AI tools:
```bash
# Chat with Gemini
/cli:chat --tool gemini "Explain React Hook use cases"
# Discuss implementation with Codex
/cli:chat --tool codex "How to optimize this query performance"
```
#### Specialized Analysis Modes
Use specific analysis modes for in-depth exploration:
```bash
# Architecture planning mode
/cli:mode:plan --tool gemini "Design a scalable microservices architecture"
# Deep code analysis
/cli:mode:code-analysis --tool qwen "Analyze utility functions in src/utils/"
# Bug analysis mode
/cli:mode:bug-index --tool gemini "Analyze potential causes of memory leak"
```
### Semantic Tool Invocation
Users can tell Claude to use specific tools through natural language, and Claude will understand the intent and automatically execute the appropriate commands.
#### Semantic Invocation Examples
Describe needs directly in conversation using natural language:
**Example 1: Code Analysis**
```
User: "Use gemini to analyze the modular architecture of this project"
→ Claude will automatically execute gemini-wrapper for analysis
```
**Example 2: Document Generation**
```
User: "Use gemini to generate API documentation with all endpoint descriptions"
→ Claude will understand the need and automatically invoke gemini's write mode
```
**Example 3: Code Implementation**
```
User: "Use codex to implement user login functionality"
→ Claude will invoke the codex tool for autonomous development
```
#### Advantages of Semantic Invocation
- **Natural Interaction**: No need to memorize complex command syntax
- **Intelligent Understanding**: Claude selects appropriate tools and parameters based on context
- **Automatic Optimization**: Claude automatically adds necessary context and configuration
### Memory Management: CLAUDE.md Updates
CCW uses a hierarchical CLAUDE.md documentation system to maintain project context. Regular updates to these documents are critical for ensuring high-quality AI outputs.
#### Full Project Index Rebuild
Suitable for large-scale refactoring, architectural changes, or first-time CCW usage:
```bash
# Rebuild entire project documentation index
/memory:update-full
# Use specific tool for indexing
/memory:update-full --tool gemini # Comprehensive analysis (recommended)
/memory:update-full --tool qwen # Architecture focus
/memory:update-full --tool codex # Implementation details
```
**When to Execute**:
- During project initialization
- After major architectural changes
- Weekly routine maintenance
- When AI output drift is detected
#### Quick Context Loading for Specific Tasks
When you need immediate, task-specific context without updating documentation:
```bash
# Load context for a specific task into memory
/memory:load "在当前前端基础上开发用户认证功能"
# Use alternative CLI tool for analysis
/memory:load --tool qwen "重构支付模块API"
```
**How It Works**:
- Delegates to an AI agent for autonomous project analysis
- Discovers relevant files and extracts task-specific keywords
- Uses CLI tools (Gemini/Qwen) for deep analysis to save tokens
- Returns a structured "Core Content Pack" loaded into memory
- Provides context for subsequent agent operations
**When to Use**:
- Before starting a new feature or task
- When you need quick context without full documentation rebuild
- For task-specific architectural or pattern discovery
- As preparation for agent-based development workflows
#### Incremental Related Module Updates
Suitable for daily development, updating only modules affected by changes:
```bash
# Update recently modified related documentation
/memory:update-related
# Specify tool for update
/memory:update-related --tool gemini
```
**When to Execute**:
- After feature development completion
- After module refactoring
- After API interface updates
- After data model modifications
#### Memory Quality Impact
| Update Frequency | Result |
|-----------------|--------|
| ❌ Never update | Outdated API references, incorrect architectural assumptions, low-quality output |
| ⚠️ Occasional updates | Partial context accuracy, potential inconsistencies |
| ✅ Timely updates | High-quality output, precise context, correct pattern references |
### CLI Tool Initialization
When using external CLI tools for the first time, initialization commands provide quick configuration:
```bash
# Auto-configure all tools
/cli:cli-init
# Configure specific tools only
/cli:cli-init --tool gemini
/cli:cli-init --tool qwen
```
This command will:
- Analyze project structure
- Generate tool configuration files
- Set up `.geminiignore` / `.qwenignore`
- Create context file references
---
## Advanced Usage: Agent Skills
Agent Skills are modular, reusable capabilities that extend the AI's functionality. They are stored in the `.claude/skills/` directory and are invoked through specific trigger mechanisms.
### How Skills Work
- **Model-Invoked**: Unlike slash commands, you don't call Skills directly. The AI decides when to use a Skill based on its understanding of your goal.
- **Contextual**: Skills provide specific instructions, scripts, and templates to the AI for specialized tasks.
- **Trigger Mechanisms**:
- **Conversational Trigger**: Use `-e` or `--enhance` flag in **natural conversation** to trigger the `prompt-enhancer` skill
- **CLI Command Enhancement**: Use `--enhance` flag in **CLI commands** for prompt refinement (this is a CLI feature, not a skill trigger)
### Examples
**Conversational Trigger** (activates prompt-enhancer skill):
```
User: "Analyze authentication module -e"
→ AI uses prompt-enhancer skill to expand the request
```
**CLI Command Enhancement** (built-in CLI feature):
```bash
# The --enhance flag here is a CLI parameter, not a skill trigger
/cli:analyze --enhance "check for security issues"
```
**Important Note**: The `-e` flag works in natural conversation, but `--enhance` in CLI commands is a separate enhancement mechanism, not the skill system.
---
## Advanced Usage: UI Design Workflow
CCW includes a powerful, multi-phase workflow for UI design and prototyping, capable of generating complete design systems and interactive prototypes from simple descriptions or reference images.
### Key Commands
- `/workflow:ui-design:explore-auto`: An exploratory workflow that generates multiple, distinct design variations based on a prompt.
- `/workflow:ui-design:imitate-auto`: A replication workflow that creates high-fidelity prototypes from reference URLs.
### Example: Generating a UI from a Prompt
You can generate multiple design options for a web page with a single command:
```bash
# This command will generate 3 different style and layout variations for a login page.
/workflow:ui-design:explore-auto --prompt "A modern, clean login page for a SaaS application" --targets "login" --style-variants 3 --layout-variants 3
```
After the workflow completes, it provides a `compare.html` file, allowing you to visually review and select the best design combination.
---
## ❓ Troubleshooting
- **Problem: Prompt shows "No active session found"**
> **Reason**: You haven't started a workflow session, or the current session is complete.
> **Solution**: Use `/workflow:session:start "Your task description"` to start a new session.
- **Problem: Command execution fails or gets stuck**
> **Reason**: It could be a network issue, AI model limitation, or the task is too complex.
> **Solution**:
> 1. First, try using `/workflow:status` to check the current state.
> 2. Check the log files in the `.workflow/WFS-<session-name>/.chat/` directory for detailed error messages.
> 3. If the task is too complex, try breaking it down into smaller tasks and then use `/workflow:plan` to create a new plan.
---
## 📚 Next Steps for Advanced Learning
Once you've mastered the basics, you can explore CCW's more powerful features:
1. **Test-Driven Development (TDD)**: Use `/workflow:tdd-plan` to create a complete TDD workflow. The AI will first write failing tests, then write code to make them pass, and finally refactor.
2. **Multi-Agent Brainstorming**: Use `/workflow:brainstorm:auto-parallel` to have multiple AI agents with different roles (like System Architect, Product Manager, Security Expert) analyze a topic simultaneously and generate a comprehensive report.
3. **Custom Agents and Commands**: You can modify the files in the `.claude/agents/` and `.claude/commands/` directories to customize agent behavior and workflows to fit your team's specific needs.
Hope this guide helps you get started smoothly with CCW!