🧪 Skills

GPU CLI: Remote GPU Compute for ML Training and Inference

Safely run local `gpu` commands via a guarded wrapper (`runner.sh`) with preflight checks and budget/time caps.

v1.1.1
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Description


name: gpu-cli description: Safely run local gpu commands via a guarded wrapper (runner.sh) with preflight checks and budget/time caps. argument-hint: runner.sh gpu [subcommand] [flags] allowed-tools: Bash(runner.sh*), Read

GPU CLI Skill (Stable)

Use this skill to run the local gpu binary from your agent. It only allows invoking the bundled runner.sh (which internally calls gpu) and read-only file access.

What it does

  • Runs gpu commands you specify (e.g., runner.sh gpu status --json, runner.sh gpu run python train.py).
  • Recommends a preflight: gpu doctor --json then gpu status --json.
  • Streams results back to chat; use --json for structured outputs.

Safety & scope

  • Allowed tools: Bash(runner.sh*), Read. No network access requested by the skill; gpu handles its own networking.
  • Avoid chaining or redirection; provide a single runner.sh gpu … command.
  • You pay your provider directly; this may start paid pods.

Quick prompts

  • "Run runner.sh gpu status --json and summarize pod state".
  • "Run runner.sh gpu doctor --json and summarize failures".
  • "Run runner.sh gpu inventory --json --available and recommend a GPU under $0.50/hr".
  • "Run runner.sh gpu run echo hello then post the output".

Notes

  • For image/video/LLM work, ask the agent to include appropriate flags (e.g., --gpu-type "RTX 4090", -p 8000:8000, or --rebuild).

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Compatible Platforms

Pricing

Free

Related Configs