- Updated COMMAND_SPEC.md to reflect new version and features including native CodexLens and CLI refactor. - Revised GETTING_STARTED.md and GETTING_STARTED_CN.md for improved onboarding experience with new features. - Enhanced INSTALL_CN.md to highlight the new CodexLens and Dashboard capabilities. - Updated README.md and README_CN.md to showcase version 6.2.0 features and breaking changes. - Introduced memory embedder scripts with comprehensive documentation and quick reference. - Added test suite for memory embedder functionality to ensure reliability and correctness. - Implemented TypeScript integration examples for memory embedder usage.
16 KiB
🚀 Claude Code Workflow (CCW) - Getting Started Guide
Welcome to Claude Code Workflow (CCW) v6.2! This guide will help you get up and running in 5 minutes and experience AI-driven automated software development with native CodexLens code intelligence and intelligent CLI orchestration.
Project Repository: catlog22/Claude-Code-Workflow
🎉 What's New in v6.2:
- 🔍 Native CodexLens: Full-Text + Semantic + Hybrid search with HNSW vector index
- 🖥️ New Dashboard Views: CLAUDE.md Manager, Skills Manager, Graph Explorer, Core Memory
- 💻 CLI Refactor:
ccw cli -pfor multi-model execution (Gemini/Qwen/Codex)- 🧠 Session Clustering: Intelligent memory management with visualization
- 📘 TypeScript Migration: Full backend modernization
⏱️ 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.
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.
/workflow:plan "Create a simple Express API that returns Hello World at the root path"
💡 Note:
/workflow:planautomatically 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:
- Context Gathering: Analyzing your project environment.
- Agent Analysis: AI agents think about the best implementation path.
- Task Generation: Creating specific task files (in
.jsonformat).
Step 3: Execute the Plan
Once the plan is created, you can command the AI agents to start working.
/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.
/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
.jsonfile 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:
# Create plan (auto-creates session)
/workflow:plan "Implement JWT-based user login and registration"
# Execute
/workflow:execute
💡 Note:
/workflow:planautomatically 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
# 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
updatecommand integrates selected design prototypes into brainstorming artifacts, ensuring implementation follows the approved designs.
Scenario 3: Complex Feature with Multi-Agent Brainstorming
Use brainstorming when you know WHAT to build, but don't know HOW to build it. The complete workflow: brainstorm → plan → execute
# 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
When to Use Brainstorming:
- You know WHAT to build, but NOT HOW - Need to explore solution approaches
- Multiple solution paths exist - Need expert analysis to choose the best approach
- Unclear technical requirements - Need to clarify architecture, data models, APIs
- Significant architectural decisions - Need multi-perspective analysis before committing
When to Skip Brainstorming (use /workflow:plan directly):
- You already know the implementation approach
- Clear technical requirements from the start
- Simple, straightforward features
- Similar to existing implementations in your codebase
Scenario 4: Quality Assurance - Action Plan Verification
After planning, validate your implementation plan for consistency and completeness:
# 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:plangenerates 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
Scenario 6: Bug Fixing
Quick bug analysis and fix workflow:
# Lightweight bug fix workflow with intelligent diagnosis
/workflow:lite-fix "Incorrect success message with wrong password"
# Claude will analyze severity, diagnose root cause, and implement the fix
🔧 Lightweight Commands
Beyond the full workflow mode, CCW provides lightweight commands suitable for quick analysis and routine tasks.
Workflow Commands for Quick Tasks
Use workflow commands for integrated planning and bug fixing:
# Lightweight planning workflow
/workflow:lite-plan "Design a scalable microservices architecture"
# Bug fix workflow with intelligent diagnosis
/workflow:lite-fix "Analyze potential causes of memory leak"
# Initialize CLI tool configurations
/cli:cli-init
Semantic Tool Invocation (Replaces Direct CLI Commands)
Important
: Direct CLI commands (
/cli:analyze,/cli:chat,/cli:execute, etc.) have been replaced by semantic invocation. Simply describe your needs in natural language, and Claude will automatically select and execute the appropriate CLI tools (Gemini/Qwen/Codex) with optimized templates.
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 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:
# 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:
# 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:
# 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:
# 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
-eor--enhanceflag in natural conversation to trigger theprompt-enhancerskill - CLI Command Enhancement: Use
--enhanceflag in CLI commands for prompt refinement (this is a CLI feature, not a skill trigger)
- Conversational Trigger: Use
Examples
Conversational Trigger (activates prompt-enhancer skill):
User: "Analyze authentication module -e"
→ AI uses prompt-enhancer skill to expand the request
Important Note: The -e flag works in natural conversation to trigger the prompt-enhancer skill.
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 design workflow that creates prototypes from local reference files (images, code) or text prompts.
Example: Generating a UI from a Prompt
You can generate multiple design options for a web page with a single command:
# 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:
- First, try using
/workflow:statusto check the current state. - Check the log files in the
.workflow/WFS-<session-name>/.chat/directory for detailed error messages. - If the task is too complex, try breaking it down into smaller tasks and then use
/workflow:planto create a new plan.
- First, try using
📚 Next Steps for Advanced Learning
Once you've mastered the basics, you can explore CCW's more powerful features:
-
Test-Driven Development (TDD): Use
/workflow:tdd-planto create a complete TDD workflow. The AI will first write failing tests, then write code to make them pass, and finally refactor. -
Multi-Agent Brainstorming: Use
/workflow:brainstorm:auto-parallelto have multiple AI agents with different roles (like System Architect, Product Manager, Security Expert) analyze a topic simultaneously and generate a comprehensive report. -
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!