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GPU CLI: Remote GPU Compute for ML Training and Inference

Name: GPU CLI: Remote GPU Compute for ML Training and Inference
Author: angusbezzina

作者 Angus Bezzina · GitHub ↗ · v1.2.0 · MIT-0

cross-platform ✓ 安全检测通过

518

总下载

当前安装

版本数

在 OpenClaw 中安装

/install gpu-cli

功能描述

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

使用说明 (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".
See templates/prompts.md for more examples.

Security

Input sanitization: character blocklist (; & | \ ( ) > \x3C $ { }+ newlines) plus subcommand allowlist. Commands are executed via directgpu 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).

安全使用建议

This skill appears to do exactly what it says: run the local 'gpu' CLI through a guarded wrapper. Before installing/using it: 1) review and keep dry-run on until you trust it (SKILL_DRY_RUN=true); 2) don't set SKILL_CONFIRM=yes unless you understand the cost implications (it can start paid pods via your provider); 3) verify and install the 'gpu' binary from a trusted source (the runner prints a curl | sh URL—treat that like any remote installer and inspect it first); 4) be aware the wrapper delegates networking and auth to the gpu binary, so you should audit/confirm that binary and its credentials separately; 5) if you rely on complex argument parsing, test edge cases (quoting, unusual gpu-type strings) because the script uses simple text parsing and fallbacks that may be brittle.

功能分析

Type: OpenClaw Skill Name: gpu-cli Version: 1.2.0 The gpu-cli skill is a well-engineered wrapper for a local GPU management utility, featuring robust security controls designed to prevent shell injection. The 'runner.sh' script implements a strict character blocklist, a subcommand allowlist, and utilizes direct array-based execution to avoid shell re-evaluation. The bundle includes comprehensive security documentation (SECURITY.md) and a self-test suite (selftest.sh) specifically designed to verify its injection-prevention logic, demonstrating a clear focus on safety and alignment with its stated purpose.

能力评估

✓ Purpose & Capability

The skill claims to run the local 'gpu' binary with guardrails and the bundle contains a wrapper (runner.sh), tests, docs, and a manifest matching that goal. It does not request unrelated credentials, binaries, or network permissions.

ℹ Instruction Scope

SKILL.md restricts allowed tools to the bundled runner and read-only access; runner.sh enforces a prefix and subcommand allowlist, a metacharacter blocklist, dry-run/confirmation gates, price/runtime caps, and direct exec of the gpu binary. This stays inside the stated scope. Minor note: some parsing (sed/grep/jq fallbacks and read -ra splitting) is best-effort and brittle in edge cases—this is a robustness concern, not an evidence of malicious behavior.

✓ Install Mechanism

No install spec is provided (instruction-only), so nothing is downloaded or written by the skill itself. The runner.sh prints a suggested install command for the external 'gpu' binary (a curl | sh URL) only in an error message — that is not executed by the skill but is a user-visible suggestion you should verify before running.

✓ Credentials

The skill does not request secrets or external service credentials. It exposes configuration via SKILL_* env vars (dry-run, caps, confirm, etc.) which are reasonable for this wrapper. It delegates networking and auth to the user-installed 'gpu' CLI, which is expected for this purpose.

✓ Persistence & Privilege

The skill is not always-on and does not request elevated privileges or system-wide config changes. It may invoke 'gpu daemon start' via the gpu binary (to remediate transient errors) which can create background processes — this behavior is consistent with managing GPU jobs and is attributable to the gpu CLI rather than the skill itself.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install gpu-cli
安装完成后，直接呼叫该 Skill 的名称或使用 /gpu-cli 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.2.0

- Added SECURITY.md detailing the full threat model, permission rationale, and version history. - Updated usage documentation to reference templates/prompts.md for more prompt examples. - Expanded security section: described input sanitization mechanisms and how commands are executed securely. - Improved transparency by highlighting where to find more safety and scope details.

v1.1.1

**Summary:** Safety-focused update introducing a guarded runner and simplified scope. - Introduces a `runner.sh` script as the only permitted interface to wrap all `gpu` commands with preflight checks and budget/time caps. - Restricts allowed operations to specific tools: `Bash(runner.sh*)` and `Read` (removes direct file references and broader shell access). - Retires detailed internal command documentation and references, favoring concise usage guidance and safety notes. - Provides new prompt examples and recommends running preflight checks (`gpu doctor`, `gpu status`) before jobs. - Emphasizes user responsibility for billing, clarifies that network and job lifecycle are managed solely by the `gpu` binary.

v1.1.0

Improved search discoverability with richer description and tags

v1.0.0

Initial release of gpu-cli: run local commands on remote GPUs with secure, zero-trust encryption. - Provides a `gpu` command to run code remotely as if local, including pod provisioning, code sync, and output streaming. - Supports NVIDIA GPU inventory, pricing, diagnostics, and job status. - Includes volume and vault (encrypted storage) management commands. - Adds features for LLM inference, ComfyUI workflows, serverless endpoints, and interactive notebook execution. - Offers detailed configuration, organization, authentication, and daemon control commands. - Most commands support `--json` for structured output; clear documentation for usage and troubleshooting.

元数据

Slug gpu-cli

版本 1.2.0

许可证 MIT-0

累计安装 1

当前安装数 1

历史版本数 4

常见问题

GPU CLI: Remote GPU Compute for ML Training and Inference 是什么？

Safely run local `gpu` commands via a guarded wrapper (`runner.sh`) with preflight checks and budget/time caps. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 518 次。

如何安装 GPU CLI: Remote GPU Compute for ML Training and Inference？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install gpu-cli」即可一键安装，无需额外配置。

GPU CLI: Remote GPU Compute for ML Training and Inference 是免费的吗？

是的，GPU CLI: Remote GPU Compute for ML Training and Inference 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

GPU CLI: Remote GPU Compute for ML Training and Inference 支持哪些平台？

GPU CLI: Remote GPU Compute for ML Training and Inference 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 GPU CLI: Remote GPU Compute for ML Training and Inference？

由 Angus Bezzina（@angusbezzina）开发并维护，当前版本 v1.2.0。