How does it handle Kubernetes secrets?

The skill is designed to prevent plain text secret exposure by filtering output and focusing on metadata or keys rather than sensitive values during debugging.

Does it support troubleshooting for specific pod errors?

Yes, it includes built-in workflows for common issues like CrashLoopBackOff, ImagePullBackOff, and OOMKilled events using automated log and event analysis.

Can I use this for production cluster operations safely?

Yes, the skill enforces strict safety rules including mandatory context verification, explicit namespace requirements, and dry-run flags for all destructive actions.

How does this skill save tokens during K8s operations?

It uses specialized Python scripts that filter and condense verbose kubectl output into essential data points, reducing context usage by up to 70% compared to raw commands.

What tools are required to use this skill?

You must have kubectl (version 1.25+) and jq (version 1.6+) installed on your local system for the scripts and commands to function properly.

Kubernetes Operations

Name: Kubernetes Operations
Author: nodnarbnitram

bynodnarbnitram

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Deployment & DevOps

Simplifies Kubernetes cluster management and debugging with token-efficient commands and safety-first workflows.

About

This skill provides a comprehensive toolkit for managing Kubernetes environments through Claude Code, offering optimized scripts for debugging pods, managing resources, and monitoring cluster health. It emphasizes safety and cost-efficiency by using condensed output formats that save up to 70% in token usage while preventing common mistakes like running commands in the wrong context or accidentally exposing secrets. Whether you're troubleshooting a CrashLoopBackOff or scaling deployments, this extension ensures precise, secure, and resource-conscious interaction with your K8s clusters.

Key Features

Token-efficient debugging scripts for pods and cluster health
Context-aware safety checks to prevent production accidents
Streamlined resource management for deployments, services, and configmaps
Automated troubleshooting workflows for OOMKilled and ImagePullBackOff issues
Integrated dry-run verification for all destructive operations
1 GitHub stars

Use Cases

Rapidly debugging failing pods without flooding the AI context with verbose logs
Investigating service connectivity and network issues within complex namespaces
Safe cluster maintenance including node draining and deployment scaling

About

Key Features

Token-efficient debugging scripts for pods and cluster health
Context-aware safety checks to prevent production accidents
Streamlined resource management for deployments, services, and configmaps
Automated troubleshooting workflows for OOMKilled and ImagePullBackOff issues
Integrated dry-run verification for all destructive operations
1 GitHub stars

Use Cases

Rapidly debugging failing pods without flooding the AI context with verbose logs
Investigating service connectivity and network issues within complex namespaces
Safe cluster maintenance including node draining and deployment scaling