Task Router Skill
Task Router
Safely run local `gpu` commands via a guarded wrapper (`runner.sh`) with preflight checks and budget/time caps.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install angusbezzina/gpu-cli打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
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
gpu commands you specify (e.g., runner.sh gpu status --json, runner.sh gpu run python train.py).gpu doctor --json then gpu status --json.--json for structured outputs.Safety & scope
Bash(runner.sh*), Read. No network access requested by the skill; gpu handles its own networking.runner.sh gpu … command.Quick prompts
runner.sh gpu status --json and summarize pod state".runner.sh gpu doctor --json and summarize failures".runner.sh gpu inventory --json --available and recommend a GPU under $0.50/hr".runner.sh gpu run echo hello then post the output".Notes
--gpu-type "RTX 4090", -p 8000:8000, or --rebuild).这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
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
gpu … commands via a wrapper (runner.sh) with a strict whitelist and injection checks.gpu --version, gpu doctor --json).gpu stop -y) on timeout/cancel.Non-goals
Quick usage (from an agent)
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
apps/portal/content/docs/ai-agent-skill.mdx.# 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`).
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.
Task Router
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