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Prevent Kubernetes hallucinations by diagnosing and fixing failure modes: insecure workload defaults, resource starvation, network exposure, privilege sprawl, fragile rollouts, and API drift. Use when generating, reviewing, refactoring, or migrating manifests, Helm charts,

shell
$ npx -y skills add LukasNiessen/kubernetes-skill --skill kubernetes-skill --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/kubernetes-skill
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

Prevent Kubernetes hallucinations by diagnosing and fixing failure modes: insecure workload defaults, resource starvation, network exposure, privilege sprawl, fragile rollouts, and API drift. Use when generating, reviewing, refactoring, or migrating manifests, Helm charts,

SKILL.md

kubernetes-skill.SKILL.md
name: kubernetes-skill
description: "Prevent Kubernetes hallucinations by diagnosing and fixing failure modes: insecure workload defaults, resource starvation, network exposure, privilege sprawl, fragile rollouts, and API drift. Use when generating, reviewing, refactoring, or migrating manifests, Helm charts, Kustomize overlays, cluster policies, and platform-specific Kubernetes work for EKS, GKE, AKS, OpenShift, GitOps controllers, or observability stacks."

KubeShark: Failure-Mode Workflow for Kubernetes

Run this workflow top to bottom.

1) Capture execution context

Record before writing manifests:

  • cluster version (e.g. 1.30, 1.31) and distribution (EKS, GKE, AKS, k3s, vanilla)
  • target namespace and environment criticality (dev/staging/prod)
  • workload type (Deployment, StatefulSet, Job, CronJob, DaemonSet)
  • deployment method (raw YAML, Helm, Kustomize, operator-managed)
  • policy enforcement (Pod Security Admission level, Kyverno, OPA/Gatekeeper)
  • cloud provider and CNI (affects networking, storage classes, load balancers)
  • platform controllers/add-ons (GitOps, observability, ingress, service mesh, autoscaling)

If unknown, state assumptions explicitly.

2) Diagnose likely failure mode(s)

Select one or more based on user intent and risk:

  • insecure workload defaults: missing security contexts, PSS violations, host access
  • resource starvation: missing requests/limits, no PDB, scheduling chaos
  • network exposure: flat networking, missing policies, wrong Service types, DNS issues
  • privilege sprawl: overly permissive RBAC, leaked secrets, excess ServiceAccount rights
  • fragile rollouts: misconfigured probes, mutable tags, unsafe update strategies
  • API drift: wrong apiVersion, deprecated APIs, schema violations, tool-specific errors

3) Load only the relevant reference file(s)

Primary failure-mode references:

  • `references/insecure-workload-defaults.md`
  • `references/resource-starvation.md`
  • `references/network-exposure.md`
  • `references/privilege-sprawl.md`
  • `references/fragile-rollouts.md`
  • `references/api-drift.md`

Supplemental references (only when needed):

  • `references/deployment-patterns.md`
  • `references/stateful-patterns.md`
  • `references/job-patterns.md`
  • `references/daemonset-operator-patterns.md`
  • `references/security-hardening.md`
  • `references/observability.md`
  • `references/multi-tenancy.md`
  • `references/storage-and-state.md`
  • `references/helm-patterns.md`
  • `references/kustomize-patterns.md`
  • `references/validation-and-policy.md`
  • `references/examples-good.md`
  • `references/examples-bad.md`
  • `references/do-dont-patterns.md`

Conditional Reference Retrieval (CRR) references (load only when the signal is detected):

  • `references/conditional/eks-patterns.md` for EKS, AWS, IRSA, EKS Pod Identity, AWS Load Balancer Controller, EBS/EFS CSI, Karpenter
  • `references/conditional/gke-patterns.md` for GKE, Autopilot, Workload Identity Federation for GKE, Dataplane V2, GCE Ingress, Config Sync
  • `references/conditional/aks-patterns.md` for AKS, Microsoft Entra Workload ID, Azure CNI, AGIC, Azure Disk/File/Blob CSI
  • `references/conditional/openshift-patterns.md` for OpenShift, OKD, ROSA, ARO, Routes, SCCs, OLM, `oc`
  • `references/conditional/gitops-controllers.md` for Argo CD, ApplicationSet, Flux, GitOps reconciliation, sync waves
  • `references/conditional/observability-stacks.md` for Prometheus Operator, ServiceMonitor, PodMonitor, OpenTelemetry, Loki, Grafana

Do not load multiple CRR files unless the task spans multiple detected platforms/tools.

4) Propose fix path with explicit risk controls

For each fix, include:

  • why this addresses the failure mode
  • what could still go wrong at deploy time or runtime
  • guardrails (validation commands, policy checks, rollback path)

5) Generate implementation artifacts

When applicable, output:

  • Kubernetes manifests (YAML with security contexts, resource limits, labels)
  • Helm values/templates or Kustomize overlays
  • NetworkPolicies, RBAC resources, PodDisruptionBudgets
  • Policy rules (Kyverno/OPA) and admission controls

6) Validate before finalize

Always provide validation steps tailored to deployment method and risk tier:

  • `kubectl apply --dry-run=server` or `kubectl diff`
  • `kubeconform` for schema validation against target cluster version
  • cross-resource consistency check (label/selector/port alignment)
  • policy scan (PSS profile check, Kyverno/OPA audit)

Never recommend direct production apply without reviewed diff and approval.

7) Output contract

Return:

  • assumptions and cluster version floor
  • selected failure mode(s)
  • chosen remediation and tradeoffs
  • validation/test plan
  • rollback/recovery notes (rollout undo, revision history, data safety)
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Repo: LukasNiessen/kubernetes-skill