GPU CLI: Remote GPU Compute for ML Training and Inference

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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

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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".

See templates/prompts.md for more examples.

Security

Input sanitization: character blocklist (; & | \ ( ) > < $ { } + newlines) plus subcommand allowlist. Commands are executed via direct gpu binary invocation — no shell re-evaluation (bash -c / eval).

See SECURITY.md for the full threat model, permission rationale, and version history.

Notes

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