k8s-skills
Reduces mean time to recovery (MTTR) by providing verified troubleshooting patterns for LLM-driven infrastructure agents.
Read-only Kubernetes troubleshooting skills for Claude Code, Codex, Gemini CLI and Copilot. Each one tested by an agent on a real kind cluster.
- Ask Claude to troubleshoot specific errors on a real Kubernetes cluster
- Generate solutions for common Kubernetes infrastructure issues
- Find the root cause of deployment failures using tested troubleshooting skills
Reduces mean time to recovery (MTTR) by providing verified troubleshooting patterns for LLM-driven infrastructure agents. It mitigates the risk of AI-generated hallucinations during critical Kubernetes incident response.
DevOps engineers using AI coding assistants to automate complex Kubernetes cluster diagnostics and troubleshooting.
https://github.com/k8s-servant/k8s-skills
By k8s-servant
How to Get It
claude plugins install k8s-servant/k8s-skills
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Troubleshoot specific errors on a real Kubernetes cluster
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 31 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 31 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.