colab-gpu
Skill1 starsChanged 4 months agoNo licenceView on GitHub
Use this skill when any task requires a cloud GPU (T4), running ML experiments, NLA evaluations, or interpretability research on Google Colab. Covers fully autonomous setup via Chrome automation: opening Colab, selecting T4 GPU, connecting the runtime, bridging via colab-mcp, running cells, and monitoring. Read this before using any mcp__colab-mcp__* tools. Compatible as a sub-task within /deep-work.
- Installs packages
In this repository18 other files it gives its agents.
- borrower-defenseSkill
- claude-labellingSkill
- comet-bridgeSkill
- commercializeSkill
- deep-workSkill
- frontend-slidesSkill
- gemini-collabSkill
- gpu-grantSkill
- human-writing-checkSkill
- investor-materialsSkill
- investor-outreachSkill
- investor-pitch-deckSkill
- kaggle-gpuSkill
- linkedin-osSkill
- nano-bananaSkill
- nemotron-collabSkill
- research-slidesSkill
- skill-tsaSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
37 rules. About 0 are common, 20 are distinctive, and 17 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈20
Distinctive · estimate
This author's own choices. Worth a look.
17
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

