This project provides a framework for building structured, transparent, and well-documented AI teams, targeting developers and researchers who need to manage complex AI workflows. It aims to improve AI system development by enabling task decomposition, delegation, and consistent documentation through specialized AI modes and a structured prompting methodology.

How It Works

The core of the framework is the "Roo Code" system, which utilizes a "System Prompt" incorporating the SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology. This system prompt guides an "Orchestrator" agent to decompose tasks, delegate them to specialized modes (e.g., Code, Architect, Debug), and track their execution using the "Agentic Boomerang" pattern. The framework emphasizes structured prompts for subtasks and leverages a memory mode for knowledge storage and retrieval, aiming for efficient token usage.

Quick Start & Requirements

• Installation: Manual setup involves cloning the repository, copying .roomodes to the project root, configuring AI assistant custom modes, setting custom instructions, and creating the .roo directory structure with subdirectories for modes and logs. An NPM installation is noted as "Coming Soon."
• Prerequisites: A compatible AI assistant supporting custom modes (e.g., Roo, Claude, ChatGPT) is required.
• Setup: Detailed instructions are provided for manual setup and direct setup via AI assistant prompts. Links to custom instructions and prompt enhancement templates are available within the README.

Highlighted Details

• Multi-Agent Framework: Features specialized modes like Orchestrator, Code, Architect, Ask, Debug, Memory, and Deep Research.
• SPARC Framework: Implements a structured approach to problem-solving, covering specification, pseudocode, architecture, refinement, and completion.
• Agentic Boomerang: Enables reliable task delegation and tracking within the AI team.
• Structured Documentation: Promotes consistent and traceable documentation through standardized prompt formats and memory archival.

Maintenance & Community

The project welcomes contributions via Pull Requests. The README mentions the SPARC framework developers and the broader AI research community.

Licensing & Compatibility

• License: MIT License.
• Compatibility: The MIT license generally permits commercial use and linking with closed-source projects.

Limitations & Caveats

An NPM installation is listed as "Coming Soon," suggesting the primary setup method is manual. The framework relies on external AI assistants, and its effectiveness may depend on the capabilities and API of the chosen assistant.