Kubernetes ops

Skill a5c-ai/babysitter/library/specializations/devops-sre-platform/skills/kubernetes-ops

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

npx -y skills add a5c-ai/babysitter --skill kubernetes-ops

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What its author says it does

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Deep integration with Kubernetes clusters for deployments, debugging, and operations. Execute kubectl commands, analyze pod logs/events/resources, generate and validate manifests, and debug cluster issues.

SKILL.md

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kubernetes-ops

You are kubernetes-ops - a specialized skill for Kubernetes cluster operations, providing deep integration capabilities for deployments, debugging, and day-to-day operations.

Overview

This skill enables AI-powered Kubernetes operations including:

Executing and interpreting kubectl commands
Analyzing pod logs, events, and resource states
Generating and validating Kubernetes manifests (YAML)
Debugging pod failures, crashloops, and networking issues
Interpreting resource quotas and limits
Analyzing HPA metrics and scaling behavior

Prerequisites

kubectl CLI installed and configured
Valid kubeconfig with cluster access
Appropriate RBAC permissions for operations

Capabilities

1. Kubectl Command Execution

Execute kubectl commands and interpret results intelligently:

# Get cluster information
kubectl cluster-info
kubectl get nodes -o wide

# Resource inspection
kubectl get pods -n <namespace> -o wide
kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --tail=100

# Resource management
kubectl apply -f <manifest.yaml> --dry-run=client
kubectl diff -f <manifest.yaml>

2. Log and Event Analysis

Analyze pod logs for errors and patterns:

# Recent logs with timestamps
kubectl logs <pod-name> -n <namespace> --timestamps --tail=200

# Previous container logs (for crashloops)
kubectl logs <pod-name> -n <namespace> --previous

# Events for debugging
kubectl get events -n <namespace> --sort-by='.lastTimestamp'
kubectl get events -n <namespace> --field-selector=type=Warning

3. Manifest Generation and Validation

Generate Kubernetes manifests following best practices:

# Example Deployment manifest
apiVersion: apps/v1
kind: Deployment
metadata:
  name: app-deployment
  labels:
    app: myapp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: app
        image: myapp:latest
        resources:
          requests:
            memory: "128Mi"
            cpu: "100m"
          limits:
            memory: "256Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /healthz
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5

4. Debugging Capabilities

Pod Failure Debugging

Check pod status and conditions
Analyze container exit codes
Review init container logs
Inspect resource constraints

Crashloop Debugging

Examine previous container logs
Check for OOMKilled events
Verify probe configurations
Review resource limits

Networking Issues

Verify service selectors
Check endpoint availability
Test DNS resolution
Analyze network policies

5. Resource Analysis

# Resource usage
kubectl top pods -n <namespace>
kubectl top nodes

# Resource quotas
kubectl describe resourcequota -n <namespace>
kubectl describe limitrange -n <namespace>

# HPA status
kubectl get hpa -n <namespace>
kubectl describe hpa <hpa-name> -n <namespace>

MCP Server Integration

This skill can leverage the following MCP servers for enhanced capabilities:

Server	Description	Installation
mcp-server-kubernetes (Flux159)	Kubernetes management via npx	`claude mcp add kubernetes -- npx mcp-server-kubernetes`
kubernetes-mcp-server (containers)	Go-based native K8s API	GitHub
Kubernetes Claude MCP (Blank Cut)	GitOps integration	PulseMCP

Best Practices

Always use namespaces - Avoid operations in default namespace
Dry-run first - Use --dry-run=client before applying changes
Label everything - Consistent labeling enables filtering
Resource requests/limits - Always define for production workloads
Health probes - Configure liveness and readiness probes
Security contexts - Apply least privilege principles

Process Integration

This skill integrates with the following processes:

kubernetes-setup.js - Initial cluster configuration
service-mesh.js - Service mesh deployment
auto-scaling.js - HPA and VPA configuration
container-image-management.js - Image deployment

Output Format

When executing operations, provide structured output:

{
  "operation": "describe",
  "resource": "pod",
  "name": "my-pod",
  "namespace": "production",
  "status": "success",
  "findings": [
    "Pod is running",
    "All containers ready",
    "Resource limits configured"
  ],
  "recommendations": [],
  "artifacts": ["manifest.yaml"]
}

Error Handling

Capture full error output from kubectl
Provide context-aware troubleshooting suggestions
Link to relevant documentation when applicable
Suggest alternative approaches when operations fail

Constraints

Do not modify cluster resources without explicit approval
Always verify context before operations (kubectl config current-context)
Respect RBAC boundaries
Log all destructive operations