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gpu-cli

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

angusbezzina0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install angusbezzina/gpu-cli

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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).

Source information

Source
github
Repository
openclaw/skills
Path
skills/angusbezzina/gpu-cli
Version
—
Commit
baa51939cbf39f69897702f334958c1564c36545
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

GPU CLI ClawHub Skill (Stable)

Purpose: Safely run local gpu commands from OpenClaw/ClawHub agents with guardrails (dry‑run preview, command whitelist, budget/time caps, and clear remediation), without modifying GPU CLI itself.

What this skill does

  • Executes only gpu … commands via a wrapper (runner.sh) with a strict whitelist and injection checks.
  • Performs preflight checks (gpu --version, gpu doctor --json).
  • Defaults to dry‑run previews; can enforce confirm + caps.
  • Provides optional cost/time caps before execution; attempts cleanup (gpu stop -y) on timeout/cancel.
  • Maps common exit codes to helpful guidance (auth, daemon restart, transient retry).

Non-goals

  • No telemetry, no secret handling; uses the installed GPU CLI and your provider keys in OS keychain.
  • Does not change GPU CLI behavior; all safeguards are in this skill only.

Quick usage (from an agent)

  • Trigger: "/gpu" or phrases like "Use GPU CLI to …" (as configured on ClawHub)
  • Example: "Use GPU CLI to run gpu status --json"
  • Example: "Use GPU CLI to run gpu run python train.py on an RTX 4090"

Files

  • manifest.yaml — ClawHub skill metadata, permissions, triggers, settings.
  • runner.sh — Execution wrapper with guardrails.
  • selftest.sh — Local checks for preflight and injection denial.
  • templates/prompts.md — Curated prompts for common tasks.

Notes for publishers

  • Mark channel as Stable, add logo/screenshots/demo, and link docs at apps/portal/content/docs/ai-agent-skill.mdx.
  • Keep permissions minimal: Bash + Read, workspace‑scoped; network off for the skill itself.

Extracted content

SKILL.md
# 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`).
README
GPU CLI ClawHub Skill (Stable)

Purpose: Safely run local `gpu` commands from OpenClaw/ClawHub agents with guardrails (dry‑run preview, command whitelist, budget/time caps, and clear remediation), without modifying GPU CLI itself.

What this skill does
- Executes only `gpu …` commands via a wrapper (`runner.sh`) with a strict whitelist and injection checks.
- Performs preflight checks (`gpu --version`, `gpu doctor --json`).
- Defaults to dry‑run previews; can enforce confirm + caps.
- Provides optional cost/time caps before execution; attempts cleanup (`gpu stop -y`) on timeout/cancel.
- Maps common exit codes to helpful guidance (auth, daemon restart, transient retry).

Non-goals
- No telemetry, no secret handling; uses the installed GPU CLI and your provider keys in OS keychain.
- Does not change GPU CLI behavior; all safeguards are in this skill only.

Quick usage (from an agent)
- Trigger: "/gpu" or phrases like "Use GPU CLI to …" (as configured on ClawHub)
- Example: "Use GPU CLI to run gpu status --json"
- Example: "Use GPU CLI to run gpu run python train.py on an RTX 4090"

Files
- `manifest.yaml` — ClawHub skill metadata, permissions, triggers, settings.
- `runner.sh` — Execution wrapper with guardrails.
- `selftest.sh` — Local checks for preflight and injection denial.
- `templates/prompts.md` — Curated prompts for common tasks.

Notes for publishers
- Mark channel as Stable, add logo/screenshots/demo, and link docs at `apps/portal/content/docs/ai-agent-skill.mdx`.
- Keep permissions minimal: Bash + Read, workspace‑scoped; network off for the skill itself.

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