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轮询训练任务状态(Kaggle kernel / SSH tmux session / Colab runtime)。单次查询,不循环。要周期性监控请组合 /loop。触发词:查训练状态、kernel status、实验跑完没、training 进度。
How this skill is triggered — by the user, by Claude, or both
Slash command
/trainhub:train-watchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
| 参数 | 必填 | 含义 |
| 参数 | 必填 | 含义 |
|---|---|---|
run | 是 | run_name(与 train-submit 对齐) |
platform | 否(默认读 .trainhub.json) | kaggle / ssh / colab |
kaggle kernels status <account>/<kernel_prefix>-<run_name> 2>&1 | grep -v -i warning
状态映射:
RUNNING → 继续COMPLETE → 调 train-harvest run=<run_name>ERROR / CANCELLED → 拉 log 诊断:
kaggle kernels output <id> -p /tmp/kg-err-<run_name>
tail -100 /tmp/kg-err-<run_name>/<script_name>.log
ssh <host> 'tmux list-sessions 2>/dev/null | grep <run_name>'
ssh <host> 'tail -30 <remote_dir>/<run_name>/train.log'
training complete 或 mAP → COMPLETEError / Traceback → ERRORColab 没有服务端轮询 API。建议约定:训练脚本末尾 curl -s POST 一个 webhook(或把 results.csv 传到 Drive),train-watch 通过检查 Drive 判定完成。
本 skill 单次查询。要每 10min 自动轮询用 /loop:
/loop 10m 跑 train-watch run=L2-P4-ema-p5-kaggle,COMPLETE 时调 train-harvest
/loop 配合时的终止条件Loop 内容里指定"所有 runs 都 COMPLETE 后 CronDelete",避免空转。
npx claudepluginhub shallow-dusty/claude-plugins --plugin trainhubCreates bite-sized, testable implementation plans from specs or requirements, with file structure and task decomposition. Activates before coding multi-step tasks.