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 compute-env-setupgit 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/compute-env-setup)<a href="https://agentmods.dev/skills/companion-inc/feynman/compute-env-setup"><img src="https://agentmods.dev/badge/skills/companion-inc/feynman/compute-env-setup.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.00205 |
| Opus 5 | $0.00023 | $0.00102 |
| Sonnet 5 | $0.00009 | $0.00041 |
| Haiku 4.5 | $0.00005 | $0.00020 |
Grade A, and why
compute-env-setup 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 8d 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
Compute Environment Setup
Use this skill before running a research job that needs a nontrivial runtime.
Workflow:
- Identify the job type, hardware need, data size, package stack, secrets, and expected artifacts.
- Choose the smallest working route: local notebook runtime, project virtualenv/conda, Modal, SSH/Slurm, or managed endpoint.
- Verify credentials and CLIs through Feynman Settings or environment status without printing secret values.
- Write an environment note containing package versions, install commands, cache paths, hardware, and failure modes.
- Run a tiny smoke job before the expensive job and save the smoke logs.
The done state is a recorded, reproducible environment plus a successful smoke or a precise missing dependency.
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.
- 8d ago First seen · 19 lines · 45 tokens per session scan A 1655c8526d1f
compute-env-setup is a skill published in the GitHub repository companion-inc/feynman (8,870 stars, last pushed 12d ago), licensed MIT. It adds 45 tokens to every session and 205 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.
Other skills, from other repositories
hpc-foundations
Navigate foundational HPC knowledge across concepts, architectures, schedulers, Linux usage, storage and RDMA, containers, cloud basics, and cluster administration patterns distilled from hpclib.com. Use when the task is about understanding or explaining HPC basics, Slurm or PBS or LSF concepts, Linux-on-cluster…
pipeline-chipseq
Execute ENCODE ChIP-seq processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides stage-by-stage Nextflow execution with Docker containers and cloud deployment. Use when users need to process ChIP-seq data following ENCODE standards, run peak calling with MACS2, perform IDR analysis…
pipeline-dnaseseq
Execute ENCODE DNase-seq pipeline from FASTQ to hotspots and footprints. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing DNase-seq data, calling DNase hypersensitive sites, performing footprinting analysis. Trigger on: DNase-seq pipeline, DNase hypersensitive…
pipeline-wgbs
Execute ENCODE Whole Genome Bisulfite Sequencing (WGBS) pipeline from FASTQ to methylation calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing WGBS/bisulfite-seq data, calling methylation levels, generating bedMethyl files. Trigger on: WGBS pipeline…
nextflow-workflow-engine
Dataflow workflow engine for scalable bioinformatics pipelines. Defines processes (containerized tasks) connected by channels; runs local, HPC (SLURM/SGE), cloud (AWS/GCP/Azure), or Kubernetes via a single config change. Powers nf-core. Use Snakemake for rule-based Python workflows; use Nextflow for containerized…
ngs-pipeline-management
Next-generation sequencing pipeline management with Snakemake and Nextflow. Use for building, running, and debugging reproducible NGS workflows for RNA-seq, WGS, ChIP-seq, ATAC-seq, and amplicon sequencing. Covers pipeline design patterns, HPC/cloud execution, containerization, and workflow optimization.