Validate Gpu Cluster Agent Skill

Check whether a DeepOps-deployed Slurm or Kubernetes GPU cluster is healthy and report a machine-readable verdict. Use for health checks, post-deploy verification, "is the cluster working?" questions, and after any node or driver change.

604 tokens

context cost

SKILL.md, read when the skill is used

files

instructions only

copies elsewhere

how many repositories repackaged it

1 464

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/NVIDIA/deepops --skill validate-gpu-cluster

The instruction itself

4 sections, as written by the author

Validate a GPU cluster

Which validator

Slurm cluster → scripts/validation/validate_slurm.py (run on a cluster

node)

Kubernetes cluster → scripts/validation/validate_k8s.py (run wherever

kubectl reaches the cluster)

Not deployed yet / checking the provisioning environment →

scripts/validation/deepops_doctor.py (run from the repository root)

All tools support --json and exit 0 only when every check passes. Full

contract: docs/deepops/validation.md.

Procedure

Run the matching validator with --json.

   python3 scripts/validation/validate_slurm.py --json
   python3 scripts/validation/validate_k8s.py --json --cuda-smoke

Use --skip-gpu-job (Slurm) or omit --cuda-smoke (Kubernetes) when a

strictly read-only check is required — for example on a busy production

cluster where a test job would queue behind real work.

Read the verdict from the JSON, not from ad-hoc commands:
ok: true — report healthy, include the key counts

(nodes_total, gpus_configured/gpus_allocatable).

ok: false — report each entry in failures verbatim; they name the

failing subsystem and the next diagnostic step.

When a GPU check fails, do not conclude "driver broken" from a bare

nvidia-smi over SSH — on Slurm nodes GPUs are hidden outside jobs.

Follow skills/diagnose-driver-install/ instead.

Interpreting common results

| Signal | Meaning |

|--------|---------|

| Slurm nodes_unavailable > 0 | Node down/drained — scontrol show node <name> for the reason. |

| Slurm gpus_configured: 0 | GRES not configured — check config/group_vars/slurm-cluster.yml GPU settings and rerun the Slurm playbook. |

| K8s gpus_allocatable: 0 | GPU Operator stack not ready — kubectl get pods -A \| grep -i nvidia; first-deploy driver builds can take 10+ minutes. |

| K8s smoke pod Pending | No schedulable GPU or image pull failure — kubectl -n deepops-validate describe pod. |

| Direct nvidia-smi over SSH says "No devices were found" on a Slurm node | Expected GPU-hide behavior, not a failure. |

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How to use it

Copy the folder

Take nvidia/validate-gpu-cluster from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.