Guide · Agent skill
How to use the Kubernetes Operations Expert agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The Kubernetes Operations Expert skill gives an AI agent a structured playbook for working with Kubernetes, the system that runs containerised applications across clusters of servers. This guide explains what the skill changes about the agent's behaviour, how to install it from the ZIP, how to trigger it, and what you need before it is useful. After reading, you will be able to install the skill, ask for debugging or manifest help in plain language, and know which safety checks to keep in place.
Kubernetes Operations ExpertRightNow-AI/openfang · Apache-2.0 Download the skill Quick start
- 1Download the ZIP. Download the skill ZIP from this page. It contains SKILL.md.
- 2Unzip into a skills folder. Unzip into ~/.claude/skills/ for personal use or into a project's .claude/skills/ folder.
- 3Or upload it in the apps. In the Claude apps, go to Settings → Capabilities → Skills and upload the skill.
- 4Confirm kubectl access. Check that kubectl is installed and that kubectl config current-context shows the cluster you intend to use.
- 5Ask in plain language. Describe the problem, including namespace and pod or deployment name, and mention Kubernetes or kubectl.
- 6Review before acting. Read every suggested command and confirm it targets the right cluster before running it.
What is an agent skill and what does this one do?
An agent skill is a folder containing a SKILL.md file with instructions that an AI agent loads when a request matches the skill. This one is a specialist playbook for Kubernetes operations, covering kubectl, Helm, pods, deployments and debugging.
Once installed, the agent checks which cluster it is pointed at before changing anything, follows a standard debugging sequence, and recommends safe deployment patterns. The skill is written as guidance and command suggestions. The file itself does not run any commands.
- Confirms the current context before commands that modify resources
- Walks through pod status, events, logs, exec and resource usage when debugging
- Recommends resource requests and limits, health probes, PodDisruptionBudgets and RollingUpdate with maxUnavailable: 0
- Flags pitfalls such as using latest tags, storing secrets in ConfigMaps and deleting pods as a fix for CrashLoopBackOff
Install the Kubernetes skill
Download the ZIP from this page and unzip it. The skill folder contains a single file, SKILL.md. Place the folder in one of two locations depending on how you want to use it.
For a personal install across all projects, unzip into ~/.claude/skills/. For a single project, unzip into that project's .claude/skills/ folder. You can also upload the skill in the Claude apps under Settings → Capabilities → Skills.
- Personal: ~/.claude/skills/
- Project only: .claude/skills/ inside your project
- Claude apps: Settings → Capabilities → Skills, then upload
Check your requirements before you start
The advice assumes kubectl is installed and configured with access to a Kubernetes cluster. The skill does not supply credentials. You must provide cluster access yourself, and the agent cannot act on a cluster without it.
Helm is optional and only needed for the chart-based workflows the skill mentions.
- kubectl installed and configured with a working cluster context (required)
- Cluster credentials that you supply (required; the skill requests none)
- Helm (optional, for chart-based workflows)
kubectl config current-contextTrigger the skill with natural requests
You do not need a special command. Describe the problem in plain language that mentions Kubernetes, pods, deployments, kubectl or debugging, and the agent will apply the skill's guidance. Naming the namespace and pod or deployment helps the agent give specific commands.
Ask for the workflow you want: diagnosis, a manifest review, or an explanation of what a step means.
- "My pod in the payments namespace is stuck in CrashLoopBackOff. Walk me through debugging it."
- "Review this Deployment manifest for missing probes, resource limits and rollout settings."
- "Explain what ImagePullBackOff means and what to check first."
Debugging with the skill: the standard sequence
For a failing workload, the skill steps through the same order each time. Start with pod status, then describe the pod to read its Events, then read logs, exec into the container if needed, and finally check resource usage. The commands below come from the skill file.
Use --previous to read logs from a container that has crashed, and --follow to tail live logs.
- Pod status: look for CrashLoopBackOff, Pending or ImagePullBackOff
- Events: check for scheduling failures, probe failures or OOM kills
- Logs: use --previous for crashed containers and --follow for live output
- Exec: interactive shell for debugging
- Resources: compare CPU and memory usage with limits
kubectl get pods -n <ns>
kubectl describe pod <name> -n <ns>
kubectl logs <pod> -n <ns> --previous
kubectl logs <pod> -n <ns> --follow
kubectl exec -it <pod> -n <ns> -- sh
kubectl top pods -n <ns>Use the skill for deployment and manifest reviews
Ask the agent to review a manifest or design a deployment and it will apply the skill's patterns: Deployment for stateless workloads, StatefulSet for databases and stateful services, readiness and liveness probes on every container, and startup probes for slow-starting apps.
For networking, the skill favours ClusterIP for internal services, LoadBalancer or Ingress for external traffic, and NetworkPolicy to restrict pod-to-pod traffic by label. It also includes a DNS check you can run to test name resolution.
- Set resource requests and limits, but keep memory limits well above requests to avoid OOM kills
- Use PodDisruptionBudget during node maintenance
- Keep manifests in version control and avoid the default namespace
kubectl run debug --rm -it --image=busybox -- nslookup service-name.namespace.svc.cluster.localSafety notes: scripts, network and production changes
The skill runs no scripts and uses no network access. Its commands are suggestions that you or the agent must run in your own environment, with the credentials you have granted. Treat every suggested command as something to review before running.
The skill recommends commands such as deletes and exec sessions that can affect live workloads. Do not let production changes go through without human review. Confirm the context first, and prefer declarative manifests over imperative commands for production.
- Run kubectl config current-context before any command that modifies resources
- Review deletes and exec sessions before running them against live workloads
- Use declarative YAML in version control for production changes
- Keep secrets in Kubernetes Secrets or an external secret manager, not ConfigMaps
What people use it for
- Diagnosing a pod stuck in CrashLoopBackOff, Pending or ImagePullBackOff by following the standard sequence
- Reviewing a Deployment manifest for missing readiness probes, resource limits and rolling update settings
- Planning a zero-downtime rollout with RollingUpdate and maxUnavailable: 0
- Checking service name resolution inside the cluster with a temporary busybox pod
- Learning what Kubernetes events, probe failures and OOM kills mean while you troubleshoot
Frequently asked questions
Is the Kubernetes agent skill free?
The source lists the licence as Apache-2.0 and does not state a price. Check the licence file in the repository for the terms that apply to you.
What do I need before I can use the Kubernetes skill?
You need kubectl installed and configured with access to a Kubernetes cluster. Helm is optional for chart-based workflows. You must supply your own cluster credentials, since the skill requests none.
Where do I put the skill files?
Unzip the downloaded ZIP into ~/.claude/skills/ for personal use, or into a project's .claude/skills/ folder. You can also upload it in the Claude apps under Settings → Capabilities → Skills.
Does the skill run commands on my cluster?
No. The skill is a SKILL.md file of guidance and command suggestions, and it runs no scripts and uses no network access. Any command runs only when you or the agent execute it with credentials you provide.
Can I use this skill with no cluster?
Not usefully. The advice assumes kubectl and a working cluster context, so without cluster access the commands cannot be run. Learning the concepts is possible, but the debugging workflow needs a live cluster.
How does this compare with just asking a chatbot about Kubernetes?
The skill gives the agent a fixed debugging order and a set of deployment defaults to apply each time, so answers are more consistent. It does not add new tools or access, so you still need kubectl and your own credentials.
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Our verdict
This skill suits DevOps engineers and developers who run Kubernetes clusters and want consistent troubleshooting and best-practice manifest reviews, and engineers new to Kubernetes who want the usual debugging steps explained. It is not a fit for anyone without cluster access, or for non-technical users who want a point-and-click tool. Keep human review on any production change, since the commands it recommends can affect live workloads.
Download the skill