Yusuke710/vastai-skill

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/Yusuke710/vastai-skill.

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# vastai-skill Let your AI Agents have access to GPU on [Vast.ai](https://vast.ai). An agent rents a GPU with the native `vastai` CLI, works on it over plain `ssh`/`rsync`, and destroys it when done. This repo provides the two missing pieces: - **[`skills/vastai-gpu/SKILL.md`](skills/vastai-gpu/SKILL.md)** — the skill that teaches an agent the full workflow: find/rent → connect → sync/run → transfer artifacts → destroy. - **`vastai-connect <instance_id>`** — the one gap the native CLI leaves: blocks until a freshly rented instance is actually SSH-reachable, then writes a `Host` alias to its own `~/.ssh/vastai.conf` (auto-included from `~/.ssh/config`, which is never touched again). Optionally opens VS Code/Cursor with `--ide`. <p align="center"> <img src="vastai-skill.png" alt="vastai-skill overview" width="49%"> <img src="vastai-skill-screenshot.png" alt="vastai-skill screenshot" width="49%"> </p> ## Setup ```bash # 1. Native vastai CLI + API key (from https://cloud.vast.ai/manage-keys/) uv tool install vastai vastai set api-key <key> # 2. Register your SSH public key at https://cloud.vast.ai/manage-keys/ # 3. This tool uv tool install git+https://github.com/Yusuke710/vastai-skill.git # 4. The skill — same SKILL.md works for both agents; symlink it where yours looks. # Claude Code: ln -s "$(pwd)/skills/vastai-gpu" ~/.claude/skills/vastai-gpu # Codex: ln -s "$(pwd)/skills/vastai-gpu" ~/.agents/skills/vastai-gpu # or ask your agent to add this skill ``` Then ask your agent for something that needs a GPU. e.g. Train a model on GPU etc ## The workflow (what the agent does) ### 1. Find and rent ```bash vastai search offers 'gpu_name=RTX_3060 num_gpus=1 reliability>0.98' -o 'dph' --raw vastai create instance <offer_id> --image vastai/pytorch:latest --disk 30 --ssh --raw ``` ### 2. Wait until reachable ```bash vastai-connect <instance_id> --alias vast-gpu # blocks, then writes SSH alias ``` ### 3. Work over plain ssh/rsync. This is where you iteratively run experiments on a GPU ```bash rsync -az --filter=':- .gitignore' ./ vast-gpu:/workspace/proj/ ssh vast-gpu 'cd /workspace/proj && uv sync && uv run python train.py' rsync -az vast-gpu:/workspace/proj/outputs/ ./outputs/ ``` ### 4. Destroy the instance ```bash vastai destroy instance <instance_id> # destroy, never stop ``` Details (long-running jobs, GPU verification, failure handling, cost rules) live in [the skill](skills/vastai-gpu/SKILL.md). ## Connecting your IDE (optional) Since the instance gets a plain SSH alias, VS Code or Cursor can attach to it with their [Remote - SSH](https://code.visualstudio.com/docs/remote/ssh) extension — pick the alias (e.g. `vast-gpu`) from the remote host list, or let the tool open it for you: ```bash vastai-connect <instance_id> --ide code # or --ide cursor ``` ## License MIT

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vastai-gpu

مديرو الشبكات وأنظمة الحاسوب

Rent a GPU on vast.ai, run experiments on it over SSH/rsync, pull artifacts back, and destroy it. Use when a task needs a GPU (training, CUDA, large-model inference).

لغة النص الأصلي: الإنجليزية

2026-07-10

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