AI Agent System - Creator of the /do router

The claude-code-toolkit provides an AI agent system designed to enhance large language models like Claude Code, transforming them into specialized teams. It introduces a /do router that directs tasks to domain-specific agents, applying structured workflows and methodologies for tasks like debugging, thereby offering domain expertise and managed workflows without manual overhead. This system aims to provide domain expertise and structured workflows automatically, built over a year of daily use.

How It Works

The core innovation is the /do router, which acts as an intelligent dispatcher. When a user issues a command (e.g., /do debug this Go test), the router identifies the domain (Go testing) and selects a specialized agent. This agent then applies a predefined debugging methodology and enforces gated phases, ensuring structured and expert-level task execution. This approach aims to deliver domain expertise and consistent workflows automatically, without requiring the user to manage the underlying complexity.

Quick Start & Requirements

• Installation: Clone the repository and run the install.sh script.

  git clone https://github.com/notque/claude-code-toolkit.git ~/claude-code-toolkit
  cd ~/claude-code-toolkit
  ./install.sh --symlink
  

• Prerequisites: No specific non-default prerequisites are mentioned in the README. The installation script likely handles dependencies.
• Resources: Setup is described as taking "2 minutes."
• Documentation: Further details are available in start-here.md.

Highlighted Details

• Features a /do router for task delegation to specialized AI agents.
• Enforces gated phases and structured workflows for consistent execution.
• Demonstrates capability by mentioning a game built entirely by Claude Code using the toolkit.
• Developed over a year of daily use, suggesting practical, real-world application.

Maintenance & Community

No specific details on contributors, sponsorships, community channels (like Discord/Slack), or roadmaps are provided in the README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: The MIT license is permissive and generally compatible with commercial and closed-source applications.

Limitations & Caveats

The README does not explicitly list limitations. However, its reliance on "Claude Code" suggests it might be tailored for a specific LLM or environment, and the "built over a year of daily use" implies a mature but potentially opinionated system. Further investigation into start-here.md and the codebase would be needed to uncover specific constraints or unsupported scenarios.