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Transform load-skill-memory from manual specification to automatic discovery: **Core Change**: - From: User specifies SKILL name manually - To: System automatically discovers and matches SKILL based on task context **New Capabilities**: 1. **Three-Step Execution**: - Step 1: Discover all available SKILLs (.claude/skills/) - Step 2: Match most relevant SKILL using scoring algorithm - Step 3: Activate matched SKILL via Skill() tool 2. **Intelligent Matching Algorithm**: - **Path-Based** (Highest Priority): Direct path match from file paths - **Keyword Matching** (Secondary): Score by keyword overlap - **Action Matching** (Tertiary): Detect action verbs (分析/修改/学习) 3. **Updated Parameters**: - From: `<skill_name> [--level] [task description]` - To: `"task description or file path"` - More intuitive user experience 4. **New Examples**: ```bash /memory:load-skill-memory "分析热模型builder pattern实现" /memory:load-skill-memory "D:\dongdiankaifa9\hydro_generator_module\builders\base.py" /memory:load-skill-memory "修改workflow文档生成逻辑" ``` **Matching Examples**: Task: "分析热模型builder pattern实现" - hydro_generator_module: 4 points (thermal+builder+analyzing) ✅ - Claude_dms3: 1 point (analyzing only) Task: "D:\dongdiankaifa9\hydro_generator_module\builders\base.py" - Path match: hydro_generator_module ✅ (exact path) **Benefits**: - No manual SKILL name required - Automatic best match selection - Path-based intelligent routing - Keyword scoring for relevance - Action verb detection for context **User Experience**: Before: "/memory:load-skill-memory hydro_generator_module '分析热模型'" After: "/memory:load-skill-memory '分析热模型实现'" System automatically discovers and activates hydro_generator_module SKILL. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
🚀 Claude Code Workflow (CCW)
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.
🎉 Version 5.2: Memory Commands Enhancement
Core Improvements:
- ✅ Batch Processing - Single Level 1 task handles all module trees (67% fewer tasks)
- ✅ Dual Execution Modes - Agent Mode and CLI Mode (--cli-execute) support
- ✅ Pre-computed Analysis - Unified analysis eliminates redundant CLI calls (67% reduction)
- ✅ Performance Boost - 67% fewer file reads, 33% fewer total tasks
See CHANGELOG.md for full 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-*.jsonfiles 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:
- Create a Plan (automatically starts a session):
/workflow:plan "Implement JWT-based user login and registration" - Execute the Plan:
/workflow:execute - Check Status (optional):
/workflow:status
🤝 Contributing & Support
- Repository: GitHub - Claude-Code-Workflow
- Issues: Report bugs or request features on GitHub Issues.
- Discussions: Join the Community Forum.
📄 License
This project is licensed under the MIT License. See the LICENSE file for details.