LukasNiessen/kubernetes-skill

Kubernetes Skill for Claude Code and Codex. LLMs hallucinate a lot with K8s - KubeShark fixes this. It eliminates hallucinations and grounds your Kubernetes, Helm etc official best practices.

What it solves

KubeShark prevents LLM hallucinations when generating or reviewing Kubernetes manifests. It addresses common AI mistakes such as omitting security contexts, using deprecated APIs, forgetting resource limits, or creating fragile probes that can cause cascading failures.

How it works

Instead of providing a static manual, KubeShark implements a failure-mode-first workflow. When an AI agent (like Claude Code or Codex) encounters a Kubernetes task, it follows a seven-step process: capturing context, diagnosing potential failure modes, loading only the most relevant reference files (Conditional Reference Retrieval), proposing fixes with risk controls, generating artifacts, validating them, and delivering a structured output contract including assumptions and rollback notes.

Who it’s for

Developers and DevOps engineers using AI agents to manage Kubernetes manifests, Helm charts, and Kustomize overlays who require production-ready, secure, and reliable configurations.

Highlights

  • Hallucination Prevention: Uses a diagnostic sequence to avoid common K8s mistakes and deprecated APIs.
  • Token Efficiency: Employs Conditional Reference Retrieval (CRR) to load only the necessary platform-specific guidance (e.g., EKS, GKE, AKS) rather than dumping entire documentation into the prompt.
  • Security-First: Based on official Kubernetes documentation, NSA/CISA hardening guides, OWASP Top 10, and CIS benchmarks.
  • Comprehensive Coverage: Includes guidance for RBAC, NetworkPolicies, policy engines (Kyverno, OPA/Gatekeeper), and GitOps controllers (Argo CD, Flux).

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