feynman is a free, open source ai development platforms project written in TypeScript and released under MIT. It has 9,781 GitHub stars, 1,087 forks and 1 open issues, and was last pushed 4 hours ago. On this registry it ranks #63 of 144 tracked projects in AI Development Platforms, with 5 head-to-head comparisons available.

What is feynman?

Feynman is the open source AI research agent: an MIT-licensed TypeScript command-line tool that searches papers and the web and answers with cited sources, aimed at researchers, engineers, and research groups.

What it is

Feynman is a terminal application written in TypeScript and released under the MIT licence, catalogued under AI & Machine Learning / AI Development Platforms, with 9781 stars, 1087 forks, and a single open issue. Its topics — ai-agent, arxiv, cli, literature-review, pi-coding-agent, and research — show the ground it covers: a natural-language question or a slash command returns answers with citations, literature reviews, replication plans, paper-versus-code audits, or ranked training recipes. It can also be reached from an ACP editor such as Zed by running it through pi-acp, and its skill library installs separately for Codex, a repository, or OpenCode.

The problem it solves is the manual, scattered effort of research: finding papers, reading them, checking whether a paper's claims match its published code, and locating a training recipe that spans papers, datasets, documentation, and repositories. Feynman replaces that ad-hoc process with named, repeatable commands. feynman audit 2401.12345 compares paper claims against the public codebase, feynman replicate plans replication checks and runs them only after an explicit environment choice, and feynman lit "RLHF alternatives" returns consensus, disagreements, and open questions. A /summarize command condenses a paper, report, repository, or PDF without loading it raw into context.

Key capabilities

  • Prompt-driven research: feynman "what do we know about scaling laws" searches papers and the web and answers with cited sources, while feynman deepresearch runs a plan-first investigation with parallel researchers, synthesis, and citation verification.
  • A slash-command set alongside natural language: /deepresearch, /lit, /review, /audit, /replicate, /recipe, /compare, /draft, /autoresearch, /summarize, and /btw.
  • Paper-versus-code auditing with feynman audit, comparing a paper's claims against its public codebase.
  • Replication planning with feynman replicate, which executes checks only after an explicit environment choice.
  • Ranked ML training recipes from feynman recipe, carrying dataset, method, code, and verification status.
  • A skills-only installer placing the library at ~/.codex/skills/feynman, .agents/skills/feynman, or .opencode/skills/feynman, without the terminal, bundled Node runtime, auth storage, or Pi packages.

Who uses it and how

  • Researchers and research groups running feynman lit for consensus, disagreements, and open questions, or naming a lab or PI to get corpus mode with publication trajectories and originality-ranked papers.
  • ML engineers using feynman recipe "fine-tune a small model for math reasoning" to find ranked, implementable training recipes rather than a reading list.
  • Review and reproducibility work: feynman audit for paper-versus-code mismatch, feynman review for a severity-ranked review with a revision plan, and feynman replicate for planned replication checks.
  • Developers already inside agent editors, running Feynman through pi-acp in Zed or installing only the skills for Codex or OpenCode.
  • Users choosing their own inference: feynman setup signs in to a model provider, with local models supported through LM Studio, LiteLLM, Ollama, and vLLM, plus Amazon Bedrock.

Getting started

On macOS and Linux, run curl -fsSL https://feynman.is/install | bash; on Windows PowerShell, run irm https://feynman.is/install.ps1 | iex. The installer fetches the latest tagged release as a standalone bundle with its own Node.js runtime and verifies its SHA-256 before installing, while the npm alternative npm install -g @companion-ai/feynman uses a local Node.js >= 22.22.0; either route is followed by feynman setup.

How it compares

The material does not position Feynman against paid research products. It is built to sit alongside agent tooling that already exists, running through pi-acp inside an ACP editor such as Zed and installing its skills for Codex and OpenCode. Model access is provider-neutral, with feynman setup sign-in sitting alongside LM Studio, LiteLLM, Ollama, vLLM, and Amazon Bedrock.

When to use it — and when not to

Choosing Feynman means running a local terminal application: the one-line installer manages its own bundled runtime, but the npm route requires Node.js >= 22.22.0, and any route needs a model provider signed in before research commands work. Upgrades come from rerunning the installer, since feynman update only refreshes optional Pi packages, and anyone who installed the earlier @advaitpaliwal/feynman package must migrate once to @companion-ai/feynman. It is a poor fit for people who want a hosted, browser-based research service, and those who only need the research skills should use the smaller install-skills path that deliberately omits the terminal, Node runtime, auth storage, and Pi packages.

project readme (upstream, from github) — read inline

The open source AI research agent.

Docs License Ask DeepWiki


Installation

macOS / Linux:

curl -fsSL https://feynman.is/install | bash

Windows (PowerShell):

irm https://feynman.is/install.ps1 | iex

The one-line installer fetches the latest tagged release as a standalone bundle with its own Node.js runtime and verifies its SHA-256 before installing. To pin a version, pass it explicitly, for example curl -fsSL https://feynman.is/install | bash -s -- 0.5.3. Rerun the installer to upgrade; feynman update only updates optional Pi packages you installed.

npm alternative (uses your local Node.js >=22.22.0):

npm install -g @companion-ai/feynman

If you installed the interim @advaitpaliwal/feynman package, migrate once:

npm uninstall -g @advaitpaliwal/feynman
npm install -g @companion-ai/feynman

Then run feynman setup to sign in to a model provider. To use Feynman in an ACP editor such as Zed, run it through pi-acp: "agent_servers": { "Feynman": { "command": "npx", "args": ["-y", "pi-acp"], "env": { "PI_ACP_PI_COMMAND": "feynman" } } }. See the installation guide for uninstalling and the setup guide for local models (LM Studio, LiteLLM, Ollama, vLLM) and Amazon Bedrock.

Skills Only

If you want just the research skills without the full terminal app:

macOS / Linux:

curl -fsSL https://feynman.is/install-skills | bash

Windows (PowerShell):

irm https://feynman.is/install-skills.ps1 | iex

That installs the skill library into ~/.codex/skills/feynman for Codex. For other targets, pass a scope:

curl -fsSL https://feynman.is/install-skills | bash -s -- --codex     # ~/.codex/skills/feynman (default)
curl -fsSL https://feynman.is/install-skills | bash -s -- --repo      # .agents/skills/feynman in the current repo
curl -fsSL https://feynman.is/install-skills | bash -s -- --opencode  # .opencode/skills/feynman in the current repo
& ([scriptblock]::Create((irm https://feynman.is/install-skills.ps1))) -Scope Codex     # or -Scope Repo, -Scope OpenCode

These installers download the bundled skills/ and prompts/ trees plus the repo guidance files referenced by those skills. They do not install the Feynman terminal, bundled Node runtime, auth storage, or Pi packages.


What you type → what happens

$ feynman "what do we know about scaling laws"
→ Searches papers and the web, answers with cited sources

$ feynman deepresearch "mechanistic interpretability"
→ Plan-first investigation with parallel researchers, synthesis, and citation verification

$ feynman lit "RLHF alternatives"
→ Literature review with consensus, disagreements, open questions, and lab/PI corpus mode when the input names a research group

$ feynman audit 2401.12345
→ Compares paper claims against the public codebase

$ feynman replicate "chain-of-thought improves math"
→ Plans replication checks and runs them only after an explicit environment choice

$ feynman recipe "fine-tune a small model for math reasoning"
→ Finds ranked, implementable ML training recipes from papers, datasets, docs, and code

Workflows

Ask naturally or use slash commands as shortcuts.

Command What it does
/deepresearch Source-heavy multi-agent investigation
/lit Literature review from paper search and primary sources; lab/PI inputs map publication trajectories and originality-ranked papers
/review Research review with severity and revision plan
/audit Paper vs. codebase mismatch audit
/replicate Plan replication checks; execute only after choosing an environment
/recipe Ranked ML training recipes with dataset, method, code, and verification status
/compare Source comparison matrix
/draft Paper-style draft from research findings
/autoresearch Bounded experiment loop with benchmark evidence
/summarize Summarize a paper, report, repo, or PDF without loading it raw into context
/btw Side conversation while the main research agent is busy, with optional handoff back into the main thread
/outputs Browse all research artifacts

Agents

Four bundled research agents, invoked by workflow prompts when decomposition helps.

  • Researcher — gather evidence across papers, web, repos, docs
  • Reviewer — internal research critique with severity-graded feedback
  • Writer — structured drafts from research notes
  • Verifier — inline citations, source URL verification, dead link cleanup

Skills & Tools

  • alphaXiv — paper search, Q&A, code reading, and annotations (via Feynman's alpha tools and feynman alpha command)
  • Literature databases — read-only Semantic Scholar, OpenAlex, arXiv ID lookup, PubMed, Europe PMC full text, bioRxiv/medRxiv, and Crossref, with stable identifiers. Set the free OPENALEX_API_KEY (create one) and optionally SEMANTIC_SCHOLAR_API_KEY (request one) to use your own rate limits
  • Hugging Face Hub — dataset metadata, split/schema inspection, and small file reads from model, dataset, and Space repos
  • Web research — search, page fetching, and PDF extraction through pi-web-access; Exa works without a key, and feynman search set configures Perplexity, Exa, or Gemini
  • Documents — local PDF and office-document parsing through pi-docparser
  • Compute — Docker, plus Modal or RunPod when their CLIs are installed, for replication and experiment runs you explicitly approve

How it works

Feynman runs on stock Pi (@earendil-works/pi-coding-agent). Its prompts, skills, agents, and research tools load as a Pi package alongside the bundled pi-subagents, pi-web-access, pi-docparser, and pi-btw packages. Paper search and analysis use alphaXiv. Research claims link to papers, docs, or repos with direct URLs.


Telemetry

Feynman sends anonymous usage telemetry to PostHog by default and prints a one-time notice on first run. It sends commands, workflow names and outcomes, tool names, model and provider names, token counts, latency, and error flags under a random install ID. It never sends prompts, model output, paper content, file paths, or tool arguments. Set FEYNMAN_TELEMETRY=off (or DO_NOT_TRACK=1) to disable it; feynman status shows the current setting. The full event list is in the configuration docs.


Star History

Star History Chart

The bundled Pi packages are pinned and update with Feynman, not through feynman update. See the package stack and release notes.

Contributing

See CONTRIBUTING.md for the full contributor guide.

git clone https://github.com/Companion-Inc/feynman.git
cd feynman
nvm use || nvm install
npm install
npm test
npm run typecheck
npm run build

Docs · Release Notes · MIT License

Frequently asked questions

Is feynman free to use?

feynman is open source under the MIT licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does feynman do?

The open source AI research agent.

What is feynman written in?

feynman is primarily written in TypeScript. Its source is publicly available at https://github.com/Companion-Inc/feynman, and it has 9,781 GitHub stars.