coreweave-common-errors
Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave".
Best use case
coreweave-common-errors is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave".
Teams using coreweave-common-errors should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/coreweave-common-errors/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How coreweave-common-errors Compares
| Feature / Agent | coreweave-common-errors | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# CoreWeave Common Errors ## Error Reference ### 1. Pod Stuck Pending -- No GPU Available ```bash kubectl describe pod <pod-name> | grep -A5 Events # "0/N nodes are available: insufficient nvidia.com/gpu" ``` **Fix**: Check GPU availability: `kubectl get nodes -l gpu.nvidia.com/class=A100_PCIE_80GB`. Try a different GPU type or region. ### 2. CUDA Out of Memory ``` torch.cuda.OutOfMemoryError: CUDA out of memory ``` **Fix**: Reduce batch size, enable gradient checkpointing, or use a larger GPU (A100-80GB instead of 40GB). ### 3. Image Pull BackOff **Fix**: Create an imagePullSecret: ```bash kubectl create secret docker-registry regcred \ --docker-server=ghcr.io \ --docker-username=$GH_USER \ --docker-password=$GH_TOKEN ``` ### 4. NCCL Timeout (Multi-GPU) ``` NCCL error: unhandled system error ``` **Fix**: Ensure all GPUs are on the same node (NVLink). For multi-node, use InfiniBand-connected nodes. ### 5. PVC Not Mounting **Fix**: Check storage class availability: `kubectl get sc`. Use CoreWeave storage classes like `shared-hdd-ord1` or `shared-ssd-ord1`. ### 6. Node Affinity Mismatch **Fix**: List valid GPU class labels: ```bash kubectl get nodes -o json | jq -r '.items[].metadata.labels["gpu.nvidia.com/class"]' | sort -u ``` ### 7. Service Not Reachable **Fix**: Check Service and Endpoints: ```bash kubectl get svc,endpoints <service-name> ``` ## Resources - [CoreWeave Documentation](https://docs.coreweave.com) - [GPU Instance Types](https://docs.coreweave.com/docs/platform/instances/gpu-instances) ## Next Steps For diagnostics, see `coreweave-debug-bundle`.
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