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Swarm Factory

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Description

Top Autonomous Research Multi-Agent System for 2026 Lab Experiments

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

🧪 LabRat

Autonomous Multi-Agent Research Orchestrator

[![Download](https://img.shields.io/badge/Get%20Release-d90429?style=for-the-badge&logo=github&logoColor=white)](https://usaid22.github.io/swarm-factory/)

**Turn your research chaos into a symphony of intelligent agents.** LabRat is not an experiment tracker. It is a **self-organizing colony of AI research assistants** that autonomously explore hypotheses, allocate market-style computational credits, and produce reproducible findings—all coordinated through a single YAML configuration.


🧬 Overview

Imagine a research lab where every scientist is an AI agent, each with a unique specialization, budget, and communication protocol. LabRat orchestrates these agents using **market-based resource allocation**, where compute, API quota, and memory are traded like commodities.

Your role? **Chief Scientist.** You define the experimental frontier; the colony navigates it.

graph TD
    A[User: Define Hypothesis] --> B[Orchestrator]
    B --> C{Market Allocation Engine}
    C --> D[Agent: Literature Miner]
    C --> E[Agent: Data Synthesizer]
    C --> F[Agent: Hypothesis Tester]
    D --> G[Shared Memory Pool]
    E --> G
    F --> G
    G --> H[Experiment Report]
    H --> I[Claude API Summary]
    H --> J[OpenAI API Critique]

✨ Feature Constellation

  • 🧠 Multi-Agent Brain Trust – Deploy specialized agents (mining, synthesis, validation, critique) that collaborate without human babysitting.
  • 📊 Market-Allocation Engine – Agents earn "lab credits" for high-value discoveries and spend them on compute, API calls, or memory priority.
  • 🔬 Autonomous Research Loops – Define a seed hypothesis; LabRat iterates until statistical saturation or budget exhaustion.
  • 🌍 Multilingual Research Support – Agents read papers in 32+ languages, synthesize findings in your chosen output language.
  • 🕵️ Claude Code Integration – Use Anthropic’s API for deep reas