Agent skill · data analytics · jeremylongshore
coreweave-gpu-node-forensics
Triage a dead or degraded GPU on a CoreWeave node fast — decide reschedule vs GPU-reset vs node-reboot vs RMA from an Xid code or a pasted dmesg / nvidia-smi blob, so a bad card does not silently kill a multi-day training run. Use when a GPU throws an Xid error, a node "fell off the bus", a training run stalls or NCCL hangs on one rank, or you need to know whether to replace, reset, or just reschedule. Trigger with "xid error", "gpu fell off the bus", "coreweave gpu dead", "should I RMA this GPU", "gpu node triage".
Why this skill is useful
Adds a deterministic script for GPU triage based on NVIDIA Xid codes that fundamentally extends the AI's diagnostic capabilities.
What it needs
Requires python3 installed locally. About 8k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
CoreWeave GPU Node Forensics Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc. "NVIDIA" and "Xid" are trademarks of NVIDIA Corporation; Xid semantics are cited from NVIDIA's public documentation. Triages a dead or degraded GPU on a CoreWeave node in seconds and returns one grounded move — reschedule, reset-gpu, reboot-node, rma, watch, or app-bug-not-hardware — from an NVIDIA Xid code or a pasted dmesg / nvidia-smi blob. The classification is deterministic: a bundled script does the mapping so the agent never guesses whether a card is dead, degraded, or fine. Overview A single bad GPU can kill a 64-GPU, multi-day training run — thousands of dollars and days of wall-clock gone — because one rank stalls the whole collective. The expensive mistakes are triage mistakes: RMAing a healthy card for an app bug, restarting a job onto a GPU whose memory error was uncontained, or manually uncordoning a node the lifecycle controller is trying to replace. This skill kills that ambiguity. The decision logic is grounded in the NVIDIA Xid error catalog (<https://docs.nvidia.com/deploy/xid-errors/>) and CoreWeave's node-lifecycle / cordon behavior. The math-of-the-matter — which Xid means what, and how row-remapper state overrides it — lives in scripts/triage.py as a table the LLM does not get to re-litigate. Deep domain knowledge (the full code→action table, the row-remap decision, the cordon rules) loads from references/ on demand. The headline is the Xid 94-vs-95 split. A contained memory error (94) cost you one job restart on a healthy node; an uncontained one (95) means the GPU could not isolate the fault and everything it touched is suspect. Getting that one bit wrong is the difference between a 30-second reschedule and a run that quietly trained on corrupt gradients. The script decides it; the skill never eyeballs it. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/coreweave-gpu-node-forensics