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Demo skill from probing-acme vendor package. Use to verify pip-installed extension discovery (skills + magics).
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
NCCL proxy wait decomposition — culprit (send_gpu_wait) vs victim (recv_wait)
One-shot health check: CPU, GPU, tables, torch step progress, TorchProbe overhead, cluster nodes, NCCL profiler health
SRE first-response triage for distributed training incidents. Automates the manual checks from PyTorch/NCCL debugging runbooks.
Diagnose PyTorch NCCL watchdog timeouts with Flight Recorder collective sequence alignment.
GPU memory and utilization headroom
Detect monotonic GPU memory growth across training steps
| name | acme_health |
| description | Demo skill from probing-acme vendor package. Use to verify pip-installed extension discovery (skills + magics). |
| category | triage |
Installed via pip install probing-acme. If this skill appears in
probing skill list, vendor extension discovery works.
