multi-agent Tools

Agents is a multi-harness plugin marketplace for AI coding tools like Claude Code, Cursor, and GitHub Copilot. It solves the problem of fragmented, tool-specific agent ecosystems by providing a central hub for discovering and using skills across different platforms. This project is for developers and teams who use multiple AI coding assistants and want a consistent, extensible set of capabilities available everywhere they work.

OpenRig is a multi-agent harness that orchestrates Claude Code, Codex, and Pi to work together as a coordinated team. It solves the problem of managing complex, long-term coding projects by delegating specialized tasks to different AI agents, tracking their work, and consolidating results. It's designed for developers and teams who need to tackle large-scale software projects that require sustained, collaborative effort over weeks or months.

Starnet is a local-first desktop application that lets you run and manage real AI agents that perform actual work. It solves the problem of opaque, cloud-dependent AI tools by giving you full control—you bring your own API keys and watch your crew execute tasks directly on your machine. It's built for developers and tinkerers who want a transparent, customizable, and visually engaging interface for their autonomous AI workflows.

Ruflo is an agent meta-harness for building and orchestrating intelligent multi-agent systems. It solves the complexity of coordinating autonomous AI workflows by providing adaptive memory, RAG integration, and self-learning intelligence. It's designed for developers and teams building advanced conversational AI, autonomous swarms, and complex, coordinated AI applications.

This is an open-source book titled 'Deep Understanding of AI Agent: Design Principles and Engineering Practice' by Li Bojie. It provides a systematic guide to the core concepts, design principles, and practical engineering techniques for creating effective AI agents. The repository contains the full book text, compiled PDFs, and chapter-by-chapter example code. It is designed for developers, engineers, and researchers who want to move beyond simple AI models and learn how to architect and implement sophisticated, autonomous agent systems.

DeerFlow is an open-source, long-horizon SuperAgent harness that automates complex tasks like deep research, coding, and content generation. It solves the problem of executing multi-step, time-intensive projects by leveraging sandboxes, memory, tools, and subagents in a secure environment. It's designed for developers, researchers, and creators who need an autonomous agent to handle workflows that can take from minutes to hours.

AI code review that actually thinks. 30+ agents, zero noise.