メニュー
Check idle GPU availability across both nodes (gpu01 and gpu02) and recommend candidate devices before launching jobs. Use when you need to choose a node/GPU for training or inference, or to report GPU availability with a concrete recommendation.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | gpu-preflight |
| description | Check idle GPU availability across both nodes (gpu01 and gpu02) and recommend candidate devices before launching jobs. Use when you need to choose a node/GPU for training or inference, or to report GPU availability with a concrete recommendation. |
python3 ~/.codex/skills/gpu-preflight/scripts/gpu_preflight.py
gpu01 and gpu02 (8 GPUs each).node:gpu_index.gpu01, gpu02) before making any GPU scheduling recommendation.ssh in batch mode and fail fast if a node is unreachable (do not hang waiting for a password prompt).python3 ~/.codex/skills/gpu-preflight/scripts/gpu_preflight.py --help
Common options:
--nodes gpu01,gpu02 (override node list)--max-util 5 (candidate threshold, percent)--max-mem-used-mib 1000 (candidate threshold)--top-k 5 (how many candidates to print)--json (machine-readable output)Run and recover long-lived Codex CLI conversations in Linux tmux sessions with workspace-scoped metadata and SESSION_ID tracking. Use when Codex needs to keep watching one interactive session, continue the same conversation after detach/reattach, recover after terminal loss with exact `SESSION_ID` resume, or monitor tmux-backed Codex output without relying on VS Code integrated terminals.
Build, edit, render, import, and export presentation decks with the preloaded @oai/artifact-tool JavaScript surface through the artifacts tool.
Build, edit, recalculate, import, and export spreadsheet workbooks with the preloaded @oai/artifact-tool JavaScript surface through the artifacts tool.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Check Codex "cloud review" signals on a GitHub PR (thumbs-up reactions, comments/reviews, checks) and troubleshoot cases where the review appears to have "no feedback". Use when a PR is expected to be reviewed by Codex but gh/CLI output shows nothing.