Local GPU Kubernetes Validation
NVIDIA/dcgm-exporter
A skill your agent uses when validating DCGM Exporter in a local GPU-backed k3d/Kubernetes environment.
Safely uninstall NVIDIA NIM Operator from Kubernetes with inventory checks, explicit approval gates for destructive actions, optional custom resource cleanup, optional CRD removal, and…
$ npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/k8s-nim-operator nim-operator-uninstall --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/k8s-nim-operator.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/nim-operator-uninstall .claude/skills/nim-operator-uninstall && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "nim-operator-uninstall" agent skill from https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstall into .claude/skills/nim-operator-uninstall/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nim-operator-uninstall", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstallType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/k8s-nim-operator nim-operator-uninstall --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/k8s-nim-operator.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/nim-operator-uninstall .agents/skills/nim-operator-uninstall && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nim-operator-uninstall" agent skill from https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstall into .agents/skills/nim-operator-uninstall/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nim-operator-uninstall", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/k8s-nim-operator nim-operator-uninstall --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/k8s-nim-operator.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/nim-operator-uninstall .cursor/skills/nim-operator-uninstall && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "nim-operator-uninstall" agent skill from https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstall into .cursor/skills/nim-operator-uninstall/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nim-operator-uninstall", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/k8s-nim-operator.git --path .agents/skills/nim-operator-uninstall--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/k8s-nim-operator nim-operator-uninstall --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/k8s-nim-operator.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/nim-operator-uninstall .gemini/skills/nim-operator-uninstall && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "nim-operator-uninstall" agent skill from https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstall into .gemini/skills/nim-operator-uninstall/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nim-operator-uninstall", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/k8s-nim-operator nim-operator-uninstallInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/k8s-nim-operator.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/nim-operator-uninstall .github/skills/nim-operator-uninstall && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "nim-operator-uninstall" agent skill from https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstall into .github/skills/nim-operator-uninstall/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nim-operator-uninstall", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/k8s-nim-operator nim-operator-uninstall --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/k8s-nim-operator.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/nim-operator-uninstall .opencode/skills/nim-operator-uninstall && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "nim-operator-uninstall" agent skill from https://github.com/NVIDIA/k8s-nim-operator/tree/main/.agents/skills/nim-operator-uninstall into .opencode/skills/nim-operator-uninstall/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nim-operator-uninstall", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
nim-operator-uninstallSafely uninstall NVIDIA NIM Operator from Kubernetes with inventory checks, explicit approval gates for destructive actions, optional custom resource cleanup, optional CRD removal, and…
Nim Operator Uninstall is an agent skill from NVIDIA/k8s-nim-operator, published by the product's own GitHub organization. Safely uninstall NVIDIA NIM Operator from Kubernetes with inventory checks, explicit approval gates for destructive actions, optional custom resource cleanup, optional CRD removal, and post-uninstall validation. Use when a customer wants to remove or clean up the NIM Operator itself, not the GPU Operator or unrelated cluster dependencies.
Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/validation.md` and `scripts/validate-nim-operator-uninstall.sh`).
It sits in DevOps & Cloud, covering Container orchestration. It works with NVIDIA AI Platform and Kubernetes. The repository describes itself as: An Operator for deployment and maintenance of NVIDIA NIMs and NeMo microservices in a Kubernetes environment. The licence is Apache-2.0.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 315bf38. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
kubectlhelmsshFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use kubectl, helm and ssh, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Nim Operator Uninstall loads about 3.6k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 91 tokens; SKILL.md has 1,218 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from NVIDIA/k8s-nim-operator at commit 315bf38, republished under its Apache-2.0 licence (© NVIDIA). 1,218 words, ~3,607 tokens.
.claude/skills/nim-operator-uninstall/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Use this skill to remove the NVIDIA NIM Operator Helm release from a Kubernetes cluster. This skill is intentionally separate from install because uninstall is destructive and needs stronger confirmation.
By default, uninstall only removes the NIM Operator Helm release. Do not delete NIM custom resources, CRDs, namespaces, persistent volumes, secrets, GPU Operator, cert-manager, KServe, or Dynamo dependencies unless the user explicitly approves that specific action.
Assume commands run from the root of the k8s-nim-operator repository unless the user gives another working directory. Before using repo-relative paths such as .agents/skills/..., verify the current directory:
pwd
test -f .agents/skills/nim-operator-uninstall/SKILL.mdIf this check fails, ask for the correct repository root or cd to it before continuing.
Run read-only inventory before proposing any destructive command. Before running each destructive step, print the exact command, summarize what will be removed, and ask for confirmation.
Read-only examples: kubectl get, kubectl describe, helm list, helm status, helm get values.
Destructive examples: helm uninstall, kubectl delete, namespace deletion, CRD deletion.
nim-operatornim-operatorreferences/validation.md..agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.sh.End users do not need to know the internal file layout. They should ask the agent for the cleanup outcome they want. Recognize and support these prompt patterns:
Inventory only:
Use the NIM Operator uninstall skill to inventory the current installation. Do not delete anything.Safe default uninstall:
Use the NIM Operator uninstall skill to uninstall the NIM Operator Helm release. Preserve CRDs, custom resources, namespace, GPU Operator, cert-manager, and KServe unless I explicitly approve deleting them.Uninstall a specific release or namespace:
Use the NIM Operator uninstall skill to remove release <release> from namespace <namespace>. Inventory resources first and ask before uninstalling.Full API cleanup:
Use the NIM Operator uninstall skill to remove the Helm release and then ask me whether to delete NIM Operator CRDs. Show existing custom resources before deleting any CRDs.Validate after uninstall:
Use the NIM Operator uninstall skill to validate that the operator release and controller pods are gone. Tell me which CRDs and custom resources remain.Remote cluster through SSH:
Use the NIM Operator uninstall skill against my remote Kubernetes host <user>@<host>. Run commands over SSH, show every command before running it, and do not delete anything until I approve.This section is for humans, CI jobs, and reviewers who want to run the same workflow without an agent. Run local commands from the repository root and ensure kubectl points at the target cluster before running helm uninstall.
Inventory only:
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.shInventory with overrides:
NIM_OPERATOR_RELEASE=nim-operator \
NIM_OPERATOR_NAMESPACE=nim-operator \
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.shSafe default uninstall. This removes only the Helm release and preserves CRDs, custom resources, namespace, GPU Operator, cert-manager, KServe, and Dynamo dependencies:
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.sh
helm uninstall nim-operator -n nim-operator
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.sh
helm list -n nim-operator
kubectl get pods -n nim-operatorRemote SSH usage if the skill folder has been copied to the remote host:
ssh <user>@<host> '~/.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.sh'
ssh <user>@<host> 'helm uninstall nim-operator -n nim-operator'
ssh <user>@<host> '~/.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.sh'
ssh <user>@<host> 'helm list -n nim-operator'
ssh <user>@<host> 'kubectl get pods -n nim-operator'Ask only for missing choices that materially affect removal:
If the user wants a quick default uninstall, uninstall only the nim-operator Helm release from namespace nim-operator and preserve CRDs, custom resources, namespace, GPU Operator, cert-manager, and KServe.
Start inventory by calling the bundled validation helper:
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.shThis is the canonical pre-uninstall call site for the skill. It checks client tools, cluster access, the Helm release, operator namespace resources, NIM Operator CRDs, and any NIM/NeMo custom resources.
If the helper is unavailable or a narrower manual check is needed, run these read-only checks before proposing uninstall commands:
kubectl config current-context
kubectl cluster-info
helm list -A | grep nim-operator
helm status nim-operator -n nim-operator
helm get values nim-operator -n nim-operator
kubectl get pods -n nim-operator
kubectl get deployment -n nim-operator -l app.kubernetes.io/instance=nim-operator,app.kubernetes.io/name=k8s-nim-operator
kubectl get crd | grep -E 'apps.nvidia.com'Inventory NIM and NeMo custom resources across all namespaces:
kubectl get nimservices.apps.nvidia.com -A
kubectl get nimcaches.apps.nvidia.com -A
kubectl get nimpipelines.apps.nvidia.com -A
kubectl get nimbuilds.apps.nvidia.com -A
kubectl get nemodatastores.apps.nvidia.com -A
kubectl get nemoentitystores.apps.nvidia.com -A
kubectl get nemocustomizers.apps.nvidia.com -A
kubectl get nemoevaluators.apps.nvidia.com -A
kubectl get nemoguardrails.apps.nvidia.com -AIf any custom resources exist, warn that deleting CRDs will delete or orphan API access to those resources. Ask whether the user wants to delete custom resources first.
Do this step BEFORE uninstalling the Helm release.
NIM and NeMo custom resources each carry an operator-managed finalizer (for example finalizer.nimcache.apps.nvidia.com, finalizer.nimservice.apps.nvidia.com). Only the running operator removes these finalizers during deletion. If the Helm release is uninstalled first, the controller is gone, so any later kubectl delete of a custom resource blocks forever: the object keeps its deletionTimestamp and its finalizer, which in turn blocks CRD deletion and wedges the namespace in Terminating. If you have already hit this, see "Recovery From Stuck Finalizers".
Only if the user explicitly approves deleting NIM and NeMo custom resources, show and run targeted deletes while the operator is still running. Prefer deleting specific resources the user selected. If the user approves deleting all NIM Operator custom resources, use:
kubectl delete nimservices.apps.nvidia.com --all -A
kubectl delete nimcaches.apps.nvidia.com --all -A
kubectl delete nimpipelines.apps.nvidia.com --all -A
kubectl delete nimbuilds.apps.nvidia.com --all -A
kubectl delete nemodatastores.apps.nvidia.com --all -A
kubectl delete nemoentitystores.apps.nvidia.com --all -A
kubectl delete nemocustomizers.apps.nvidia.com --all -A
kubectl delete nemoevaluators.apps.nvidia.com --all -A
kubectl delete nemoguardrails.apps.nvidia.com --all -AWarn that this may remove model-serving workloads, caches, jobs, and service state owned by those custom resources.
Verification gate: before moving on to the Helm uninstall, confirm every custom resource is actually gone (not just marked for deletion). Re-run the inventory and ensure each command returns no resources:
kubectl get nimservices.apps.nvidia.com -A
kubectl get nimcaches.apps.nvidia.com -A
kubectl get nimpipelines.apps.nvidia.com -A
kubectl get nimbuilds.apps.nvidia.com -A
kubectl get nemodatastores.apps.nvidia.com -A
kubectl get nemoentitystores.apps.nvidia.com -A
kubectl get nemocustomizers.apps.nvidia.com -A
kubectl get nemoevaluators.apps.nvidia.com -A
kubectl get nemoguardrails.apps.nvidia.com -AIf any resource is still present with a deletionTimestamp and a lingering finalizer, do not proceed to helm uninstall. The operator must stay running to drain the finalizer; wait for it to clear before continuing, or see "Recovery From Stuck Finalizers".
Only after any approved custom resources have been fully deleted (the verification gate above returns nothing) should you uninstall the Helm release. Uninstalling while NIM or NeMo custom resources still exist removes the controller that clears their finalizers and will wedge those resources, their CRDs, and the namespace.
After user approval, uninstall only the Helm release:
helm uninstall nim-operator -n nim-operatorThen call the bundled validation helper again to collect post-uninstall evidence:
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.shAlso verify the key release and controller resources directly:
helm list -n nim-operator
kubectl get pods -n nim-operator
kubectl get deployment -n nim-operator -l app.kubernetes.io/instance=nim-operator,app.kubernetes.io/name=k8s-nim-operatorIf Helm reports the release is not found, do not treat that as success automatically. Check whether operator resources still exist in the namespace.
Keep CRDs by default. Delete CRDs only if the user explicitly approves full API cleanup.
kubectl delete crd \
nimservices.apps.nvidia.com \
nimcaches.apps.nvidia.com \
nimpipelines.apps.nvidia.com \
nimbuilds.apps.nvidia.com \
nemodatastores.apps.nvidia.com \
nemoentitystores.apps.nvidia.com \
nemocustomizers.apps.nvidia.com \
nemoevaluators.apps.nvidia.com \
nemoguardrails.apps.nvidia.comBefore deleting CRDs, re-run custom resource inventory. If custom resources still exist, ask again before proceeding.
Keep the namespace by default. Delete it only if the user explicitly approves and it contains no resources the user wants to preserve:
kubectl get all -n nim-operator
kubectl delete namespace nim-operatorIf the namespace hangs in Terminating with a condition that names finalizer.<kind>.apps.nvidia.com (for example NamespaceFinalizersRemaining), a custom resource was left with an undrained finalizer. See "Recovery From Stuck Finalizers".
Use this if custom resources, CRDs, or a namespace are already stuck because the Helm release was uninstalled before the custom resources were deleted. With the controller gone, the operator-managed finalizers cannot be drained. Typical symptoms:
deletionTimestamp but still lists finalizer.<kind>.apps.nvidia.com and never disappears.kubectl delete crd <name>.apps.nvidia.com blocks because instances remain.kubectl delete namespace <ns> hangs in Terminating with NamespaceFinalizersRemaining naming finalizer.<kind>.apps.nvidia.com.Recommended recovery: reinstall the operator so it drains the pending finalizers, then redo cleanup in the correct order.
# Reinstall the same release/version that was removed.
helm upgrade --install nim-operator <chart> -n nim-operator --create-namespace
# Wait for the controller pod to be Running.
kubectl get pods -n nim-operator
# The operator now reconciles the pending deletions; stuck custom resources clear in ~15s.
kubectl get nimcaches.apps.nvidia.com -AOnce the custom resources clear, follow the correct order: delete any remaining custom resources while the operator runs, run the verification gate, then helm uninstall, then CRDs, then the namespace.
Avoid manually stripping finalizers (for example kubectl patch <kind> <name> -n <ns> --type merge -p '{"metadata":{"finalizers":[]}}'). That forces deletion without running the operator's own cleanup and can orphan PVCs, Jobs, and other owned resources. Prefer the reinstall-and-drain approach above.
Do not uninstall these from this skill unless the user explicitly asks for a broader cluster cleanup workflow:
Run the bundled validation helper:
.agents/skills/nim-operator-uninstall/scripts/validate-nim-operator-uninstall.shIf a manual spot-check is needed, run:
helm list -n nim-operator
kubectl get pods -n nim-operator
kubectl get deployment -n nim-operator -l app.kubernetes.io/instance=nim-operator,app.kubernetes.io/name=k8s-nim-operator
kubectl get crd | grep -E 'apps.nvidia.com'Report:
© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in .agents/skills/nim-operator-uninstall of NVIDIA/k8s-nim-operator.
Open the folder on GitHubat commit 315bf38
Nim Operator Uninstall next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Nim Operator Uninstall this skillNVIDIA/k8s-nim-operator | 159 | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | |
| Local GPU Kubernetes ValidationNVIDIA/dcgm-exporter | 1.9k | — | ~116 | Automated safety check: Pass | Apache-2.0 | |
| Dstack Presetsdstackai/dstack | 2.3k | — | ~403 | Automated safety check: Pass | MPL-2.0 | |
| Helm Dev EnvironmentNVIDIA/OpenShell | 16k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 | |
| Aicr Analyzing SnapshotsNVIDIA/aicr | 440 | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Deploy Controllerai-runway/airunway | 102 | — | ~927 | Automated safety check: Pass | Apache-2.0 |
NVIDIA/dcgm-exporter
A skill your agent uses when validating DCGM Exporter in a local GPU-backed k3d/Kubernetes environment.
dstackai/dstack
Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format.
NVIDIA/OpenShell
Start up, tear down, and configure the local Kubernetes development environment for OpenShell.
NVIDIA/aicr
A skill your agent uses when analyzing an AICR snapshot YAML file, reviewing cluster state, comparing provider characteristics, extracting GPU/network topology insights, or generating a cluster…
ai-runway/airunway
Interactively build, push or load, and deploy an airunway component (controller or any provider) to the cluster
dstackai/dstack
dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters.
NVIDIA/k8s-nim-operator
Install NVIDIA NIM Operator on Kubernetes with prerequisite checks, optional NVIDIA GPU Operator dependency installation, public or local Helm chart selection, optional Dynamo support, and optional…
Works with
Categories
Safely uninstall NVIDIA NIM Operator from Kubernetes with inventory checks, explicit approval gates for destructive actions, optional custom resource cleanup, optional CRD removal, and…. Nim Operator Uninstall is an agent skill from NVIDIA/k8s-nim-operator, published by the product's own GitHub organization. Safely uninstall NVIDIA NIM Operator from Kubernetes with inventory checks, explicit approval gates for destructive actions, optional custom resource cleanup, optional CRD removal, and post-uninstall validation.
Nim Operator Uninstall fits situations like: A customer wants to remove; clean up the NIM Operator itself; not the GPU Operator; unrelated cluster dependencies.
Run `npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a claude-code`. Or copy the skill folder (.agents/skills/nim-operator-uninstall in NVIDIA/k8s-nim-operator) into .claude/skills/nim-operator-uninstall in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a codex`. Or copy the skill folder (.agents/skills/nim-operator-uninstall in NVIDIA/k8s-nim-operator) into .agents/skills/nim-operator-uninstall in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/k8s-nim-operator --skill nim-operator-uninstall -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nim-operator-uninstall, .gemini/skills/nim-operator-uninstall, .github/skills/nim-operator-uninstall and .opencode/skills/nim-operator-uninstall in your project.
Going by SKILL.md and its folder, Nim Operator Uninstall needs a shell for the scripts in its folder and the command-line tools its instructions call (kubectl, helm and ssh). Our summary lists: A Bash shell.
SKILL.md contains no URLs. Its commands use ssh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Nim Operator Uninstall is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 656 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Nim Operator Uninstall: Local GPU Kubernetes Validation (NVIDIA/dcgm-exporter, 1.9k stars), Dstack Presets (dstackai/dstack, 2.3k stars), Helm Dev Environment (NVIDIA/OpenShell, 16k stars) and Aicr Analyzing Snapshots (NVIDIA/aicr, 440 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/k8s-nim-operator, which has 159 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 5, 2026.
Source: NVIDIA/k8s-nim-operator on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.