# Feynman: The Open Source AI Research Agent This repository profile is provided by osrepos.com, an open source repository discovery platform. Source: osrepos.com Repository profile: https://osrepos.com/repo/companion-inc-feynman Generated for open source discovery and AI-assisted research. Feynman is an open-source AI research agent designed to automate and streamline complex research tasks. Built with TypeScript, it leverages multiple agents and tools to conduct in-depth investigations, literature reviews, and even experiment replications, providing source-grounded outputs. GitHub: https://github.com/companion-inc/feynman OSRepos URL: https://osrepos.com/repo/companion-inc-feynman ## Summary Feynman is an open-source AI research agent designed to automate and streamline complex research tasks. Built with TypeScript, it leverages multiple agents and tools to conduct in-depth investigations, literature reviews, and even experiment replications, providing source-grounded outputs. ## Topics - TypeScript - AI Research - AI Agent - Machine Learning - Open Source - CLI Tool - Automation - LLM ## Repository Information Last analyzed by OSRepos: Tue Jun 02 2026 17:27:34 GMT+0100 (Western European Summer Time) Detail views: 14 GitHub clicks: 15 ## Safety Notice OSRepos shares public repositories for knowledge and discovery only. Review source code, dependencies, licenses, and security implications before running or installing anything. ## Content ## Introduction Feynman is an open-source AI research agent developed by companion-inc. It's designed to automate and streamline complex research tasks, acting as a powerful assistant for anyone delving into scientific papers, web resources, and codebases. With its multi-agent architecture and a suite of integrated tools, Feynman provides source-grounded outputs for various research workflows. ## Installation Feynman offers both a standalone terminal application and a "skills-only" installation for integration with other agent systems like Codex or OpenCode. ### Standalone Application (macOS / Linux): bash curl -fsSL https://feynman.is/install | bash ### Standalone Application (Windows PowerShell): powershell irm https://feynman.is/install.ps1 | iex The installer fetches the latest tagged release and includes a standalone native bundle with its own Node.js runtime. For upgrades, simply rerun the installer. Local models like LM Studio, LiteLLM, Ollama, or vLLM are supported through the setup flow. ### Skills Only Installation (macOS / Linux): If you only need the research skills without the full terminal app, you can install them for Codex, a repo-local Claude/agent, or an OpenCode project. bash curl -fsSL https://feynman.is/install-skills | bash This installs the skill library into `~/.codex/skills/feynman` by default, or into specified targets like `--codex`, `--repo`, or `--opencode`. ## Examples Feynman simplifies complex research queries into straightforward commands, providing detailed, cited results. ### What you type ? what happens: * `$ feynman "what do we know about scaling laws"` * ? Searches papers and web, produces a cited research brief * `$ feynman deepresearch "mechanistic interpretability"` * ? Multi-agent investigation with parallel researchers, synthesis, verification * `$ feynman lit "RLHF alternatives"` * ? Literature review with consensus, disagreements, open questions * `$ feynman audit 2401.12345` * ? Compares paper claims against the public codebase * `$ feynman replicate "chain-of-thought improves math"` * ? Replicates experiments on local or cloud GPUs * `$ feynman recipe "fine-tune a small model for math reasoning"` * ? Finds ranked, implementable ML training recipes from papers, datasets, docs, and code ### Workflows: Feynman supports various workflows, accessible via natural language or slash commands: * `/deepresearch `: Source-heavy multi-agent investigation * `/lit `: Literature review from paper search and primary sources * `/review `: Simulated peer review with severity and revision plan * `/audit `: Paper vs. codebase mismatch audit * `/replicate `: Replicate experiments on local or cloud GPUs * `/recipe `: Ranked ML training recipes with dataset, method, code, and verification status * `/compare `: Source comparison matrix * `/draft `: Paper-style draft from research findings * `/autoresearch `: Autonomous experiment loop * `/watch `: Recurring research watch * `/outputs`: Browse all research artifacts ## Why use Feynman? Feynman stands out as a comprehensive AI research agent due to several key features: * **Multi-Agent System**: It dispatches specialized agents, including a Researcher, Reviewer, Writer, and Verifier, to handle different aspects of the research process, ensuring thoroughness and accuracy. * **Source-Grounded Outputs**: Every output is meticulously cited, linking directly to papers, documentation, or repositories, ensuring reliability and verifiability. * **Extensive Tool Integration**: Feynman integrates with powerful tools like AlphaXiv for paper search and analysis, Hugging Face Hub for dataset inspection, Docker for isolated experiments, and various web search APIs, providing a rich research environment. * **Local Model Support**: It offers seamless integration with local large language models (LLMs) via LM Studio, LiteLLM, Ollama, or vLLM, allowing for private and efficient research. * **Automated Workflows**: From deep research investigations to experiment replication and ML recipe generation, Feynman automates complex tasks, significantly reducing manual effort and accelerating the research cycle. ## Links * **GitHub Repository**: companion-inc/feynman * **Official Documentation**: feynman.is/docs * **License**: MIT License