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Tao Run On Brev

skill

Brev managed GPU instances with Docker support. Use when running TAO training, evaluation, or inference on Brev GPU instances, managing Brev deployments, or dispatching TAO jobs through the Brev CLI. Trigger phrases include "run on Brev", "Brev GPU instance", "submit job to Brev", "Brev CLI deployment".

Works with: Claude Code (native)  ·  Cursor, Codex CLI (manual)
native: this artifact type is that client's own format

Install (Claude Code):

cp -r tao-run-on-brev ~/.claude/skills/

Security audit

Not scanned yet. We audit npm-published capabilities for known advisories, install-time scripts and permission surface; this one has no npm package we can resolve, or has not reached the queue.

Its own instructions

Its SKILL.md says when to use it, shows worked examples and covers setup.

Read from the capability’s own SKILL.md. This is not a grade and does not compare to the instruction-depth verdict on an MCP server — a skill has no tools to document, so that rubric does not apply to it.

You searched for one. Check the rest of your stack:

npx tashan-cli doctor

Reads the config already on your machine and names what is dead, deprecated or running code at install time. No account, nothing uploaded.

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Pro adds the history to tashan doctor, so a run over your own config says which of yours gained an advisory, started running an install script, or lost its last maintainer — and what to move to.

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source ↗  ·  skill:NVIDIA/tao-run-on-brev

Everything on this page is public evidence and free. What it cannot know is whether you run this — check your whole config, free, in the browser. tashan Pro adds the series behind each row and names a replacement for anything dying.

Already running this? Check your whole config — free, in your browser, nothing installed. Or npx tashan-cli doctor locally, which sends nothing at all.

Measured 2026-08-20  ·  scorer s5  ·  how  ·  something wrong here?