🧪 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
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
gpucommands you specify (e.g.,runner.sh gpu status --json,runner.sh gpu run python train.py). - Recommends a preflight:
gpu doctor --jsonthengpu status --json. - Streams results back to chat; use
--jsonfor structured outputs.
Safety & scope
- Allowed tools:
Bash(runner.sh*),Read. No network access requested by the skill;gpuhandles 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 --jsonand summarize pod state". - "Run
runner.sh gpu doctor --jsonand summarize failures". - "Run
runner.sh gpu inventory --json --availableand recommend a GPU under $0.50/hr". - "Run
runner.sh gpu run echo hellothen 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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