Feynman is an open-source AI research agent that helps users investigate topics with language models. It supports local model providers and hosted model authentication through its setup process. The catalogue contains skills, agents, and instructions that extend Feynman’s workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add companion-inc/feynman --skill chai1git clone --depth 1 https://github.com/companion-inc/feynmanWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/companion-inc/feynman/chai1)<a href="https://agentmods.dev/skills/companion-inc/feynman/chai1"><img src="https://agentmods.dev/badge/skills/companion-inc/feynman/chai1/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/companion-inc/feynman/chai1"><img src="https://agentmods.dev/badge/skills/companion-inc/feynman/chai1.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00209 |
| Opus 5 | $0.00022 | $0.00105 |
| Sonnet 5 | $0.00009 | $0.00042 |
| Haiku 4.5 | $0.00004 | $0.00021 |
Grade A, and why
chai1 scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Chai-1
Use this skill for Chai-1-style biomolecular structure prediction and review.
Workflow:
- Convert the research question into an input manifest with chains, sequences, ligands, nucleic acids, templates, restraints, and seeds.
- Verify the available execution path before running: local model, managed endpoint, Modal job, SSH host, or documented remote API.
- Capture package/model version, exact input manifest, hardware, command or request body, and all raw output files.
- Save structure files and confidence artifacts in the active Feynman output folder.
- Review chain coverage, interface confidence, ligand plausibility, stereochemistry warnings, and conflicts with known structures.
Use the structure as evidence only after the provenance and confidence checks are attached.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 19 lines · 44 tokens per session scan A e650befe7e6a
chai1 is a skill published in the GitHub repository companion-inc/feynman (8,870 stars, last pushed 14d ago), licensed MIT. It adds 44 tokens to every session and 209 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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