Files
Claude-Code-Workflow/README.md
catlog22 0625c66bce feat: Simplify agent architecture with test-fix workflow (v3.2.0)
Major architectural improvements:
- Simplify from 3 agents to 2 core agents
- Adopt "Tests Are the Review" philosophy
- Enhance test-gen as 4-phase orchestrator
- Simplify review.md following update-memory pattern

Agent Changes:
- NEW: @test-fix-agent - Execute tests, diagnose failures, fix code
- ENHANCED: @code-developer - Now writes implementation + tests together
- REMOVED: @code-review-agent, @code-review-test-agent

Task Type Updates:
- "test" → "test-gen" (generate tests)
- NEW: "test-fix" (execute and fix tests)

Workflow Improvements:
- test-gen.md: 4-phase orchestrator (context-gather → concept-enhanced → task-generate → execute)
- review.md: Simplified to optional specialized reviews (security, architecture, quality, action-items)
- All 16 files updated with new agent references

See CHANGELOG.md for full details.

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-02 12:26:35 +08:00

12 KiB

🚀 Claude Code Workflow (CCW)

Version License Platform MCP Tools

Languages: English | 中文


Claude Code Workflow (CCW) is a next-generation multi-agent automation framework that orchestrates complex software development tasks through intelligent workflow management and autonomous execution.

🎉 Latest: v3.1.0 - TDD Workflow Support with Red-Green-Refactor cycle enforcement. See CHANGELOG.md for details.

v3.0.0: Introduced unified CLI command structure. The /cli:* commands consolidate all tool interactions (Gemini, Qwen, Codex) using a --tool flag for selection.


Key Features

  • 🎯 Context-First Architecture: Pre-defined context gathering eliminates execution uncertainty and error accumulation.
  • 🤖 Multi-Agent System: Specialized agents (@code-developer, @test-fix-agent) with tech-stack awareness and automated test validation.
  • 🔄 End-to-End Workflow Automation: From brainstorming to deployment with multi-phase orchestration.
  • 📋 JSON-First Task Model: Structured task definitions with pre_analysis steps for deterministic execution.
  • 🧪 TDD Workflow Support: Complete Test-Driven Development with Red-Green-Refactor cycle enforcement.
  • 🧠 Multi-Model Orchestration: Leverages Gemini (analysis), Qwen (architecture), and Codex (implementation) strengths.
  • Pre-execution Verification: Validates plans with both strategic (Gemini) and technical (Codex) analysis.
  • 🔧 Unified CLI: A single, powerful /cli:* command set for interacting with various AI tools.
  • 📦 Smart Context Package: context-package.json links tasks to relevant codebase files and external examples.

⚙️ Installation

🚀 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, run the following command to ensure CCW is working:

/workflow:session:list

🚀 Getting Started

Complete Development Workflow

Phase 1: Brainstorming & Conceptual Planning

# Multi-perspective brainstorming with role-based agents
/workflow:brainstorm:auto-parallel "Build a user authentication system"

# Review and refine specific aspects (optional)
/workflow:brainstorm:ui-designer "authentication flows"
/workflow:brainstorm:synthesis  # Generate consolidated specification

Phase 2: Action Planning

# Create executable implementation plan
/workflow:plan "Implement JWT-based authentication system"

# OR for TDD approach
/workflow:tdd-plan "Implement authentication with test-first development"

Phase 3: Execution

# Execute tasks with AI agents
/workflow:execute

# Monitor progress
/workflow:status

Phase 4: Testing & Quality Assurance

# Generate comprehensive test suite (standard workflow)
/workflow:test-gen
/workflow:execute

# OR verify TDD compliance (TDD workflow)
/workflow:tdd-verify

Quick Start for Simple Tasks

Feature Development:

/workflow:session:start "Add password reset feature"
/workflow:plan "Email-based password reset with token expiry"
/workflow:execute

Bug Fixing:

# Interactive analysis with CLI tools
/cli:mode:bug-index --tool gemini "Login timeout on mobile devices"

# Execute the suggested fix
/workflow:execute

Code Analysis:

# Deep codebase analysis
/cli:mode:code-analysis --tool qwen "Analyze authentication module architecture"

🛠️ Command Reference

Unified CLI Commands (`/cli:*)

Use the --tool <gemini|qwen|codex> flag to select the desired tool. Defaults to gemini.

Command Description
/cli:analyze Deep codebase analysis.
/cli:chat Direct, interactive chat with a tool.
/cli:execute Execute a task with full permissions.
/cli:cli-init Initialize CLI tool configurations for the workspace.
/cli:mode:bug-index Analyze bugs and suggest fixes.
/cli:mode:code-analysis Perform deep code analysis and debugging.
/cli:mode:plan Project planning and architecture analysis.

Workflow Commands (`/workflow:*)

Command Description
/workflow:session:* Manage development sessions (start, pause, resume, list, switch, complete).
/workflow:brainstorm:* Use role-based agents for multi-perspective planning.
/workflow:plan Create a detailed, executable plan from a description.
/workflow:tdd-plan Create a Test-Driven Development workflow with Red-Green-Refactor cycles.
/workflow:execute Execute the current workflow plan autonomously.
/workflow:status Display the current status of the workflow.
/workflow:test-gen Automatically generate a test plan from the implementation.
/workflow:tdd-verify Verify TDD compliance and generate quality report.
/workflow:review Optional manual review (only use when explicitly needed - passing tests = approved code).

Task & Memory Commands

Command Description
/task:* Manage individual tasks (create, breakdown, execute, replan).
/update-memory-full Re-index the entire project documentation.
/update-memory-related Update documentation related to recent changes.

⚙️ Configuration

Essential: Gemini CLI Setup

Configure Gemini CLI for optimal integration:

// ~/.gemini/settings.json
{
  "contextFileName": "CLAUDE.md"
}

Optimize performance by excluding unnecessary files:

# .geminiignore (in project root)
/dist/
/build/
/node_modules/
/.next/
*.tmp
*.log
/temp/

# Include important docs
!README.md
!**/CLAUDE.md

Optional: MCP Tools (Enhanced Analysis)

MCP (Model Context Protocol) tools provide advanced codebase analysis. Completely optional - CCW works perfectly without them.

Available MCP Servers

MCP Server Purpose Installation Guide
Exa MCP External API patterns & best practices Install Guide
Code Index MCP Advanced internal code search Install Guide

Benefits When Enabled

  • 📊 Faster Analysis: Direct codebase indexing vs manual searching
  • 🌐 External Context: Real-world API patterns and examples
  • 🔍 Advanced Search: Pattern matching and similarity detection
  • Automatic Fallback: Uses traditional tools when MCP unavailable

🧩 How It Works: Design Philosophy

The Core Problem

Traditional AI coding workflows face a fundamental challenge: execution uncertainty leads to error accumulation.

Example:

# Prompt 1: "Develop XX feature"
# Prompt 2: "Review XX architecture in file Y, then develop XX feature"

While Prompt 1 might succeed for simple tasks, in complex workflows:

  • The AI may examine different files each time
  • Small deviations compound across multiple steps
  • Final output drifts from the intended goal

CCW's Mission: Solve the "1-to-N" problem — building upon existing codebases with precision, not just "0-to-1" greenfield development.


The CCW Solution: Context-First Architecture

1. Pre-defined Context Gathering

Instead of letting agents randomly explore, CCW uses structured context packages:

context-package.json created during planning:

{
  "metadata": {
    "task_description": "...",
    "tech_stack": {"frontend": [...], "backend": [...]},
    "complexity": "high"
  },
  "assets": [
    {
      "path": "synthesis-specification.md",
      "priority": "critical",
      "sections": ["Backend Module Structure"]
    }
  ],
  "implementation_guidance": {
    "start_with": ["Step 1", "Step 2"],
    "critical_security_items": [...]
  }
}

2. JSON-First Task Model

Each task includes a flow_control.pre_analysis section:

{
  "id": "IMPL-1",
  "flow_control": {
    "pre_analysis": [
      {
        "step": "load_architecture",
        "commands": ["Read(architecture.md)", "grep 'auth' src/"],
        "output_to": "arch_context",
        "on_error": "fail"
      }
    ],
    "implementation_approach": {
      "modification_points": ["..."],
      "logic_flow": ["..."]
    },
    "target_files": ["src/auth/index.ts"]
  }
}

Key Innovation: The pre_analysis steps are executed before implementation, ensuring agents always have the correct context.

3. Multi-Phase Orchestration

CCW workflows are orchestrators that coordinate slash commands:

Planning Phase (/workflow:plan):

Phase 1: session:start       → Create session
Phase 2: context-gather      → Build context-package.json
Phase 3: concept-enhanced    → CLI analysis (Gemini/Qwen)
Phase 4: task-generate       → Generate task JSONs with pre_analysis

Execution Phase (/workflow:execute):

For each task:
  1. Execute pre_analysis steps → Load context
  2. Apply implementation_approach → Make changes
  3. Validate acceptance criteria → Verify success
  4. Generate summary → Track progress

4. Multi-Model Orchestration

Each AI model serves its strength:

Model Role Use Cases
Gemini Analysis & Understanding Long-context analysis, architecture review, bug investigation
Qwen Architecture & Design System design, code generation, architectural planning
Codex Implementation Feature development, testing, autonomous execution

Example:

# Gemini analyzes the problem space
/cli:mode:code-analysis --tool gemini "Analyze auth module"

# Qwen designs the solution
/cli:analyze --tool qwen "Design scalable auth architecture"

# Codex implements the code
/workflow:execute  # Uses @code-developer with Codex

From 0-to-1 vs 1-to-N Development

Scenario Traditional Workflow CCW Approach
Greenfield (0→1) Works well Adds structured planning
Feature Addition (1→2) ⚠️ Context uncertainty Context-package links to existing code
Bug Fixing (N→N+1) ⚠️ May miss related code Pre-analysis finds dependencies
Refactoring ⚠️ Unpredictable scope CLI analysis + structured tasks

Key Workflows

Complete Development (Brainstorm → Deploy)

Brainstorm (8 roles) → Synthesis → Plan (4 phases) → Execute → Test → Review

Quick Feature Development

session:start → plan → execute → test-gen → execute

TDD Workflow

tdd-plan (TEST→IMPL→REFACTOR chains) → execute → tdd-verify

Bug Fixing

cli:mode:bug-index (analyze) → execute (fix) → test-gen (verify)

🤝 Contributing & Support

📄 License

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