kubernetes-specialist

jeffallan/claude-skills · updated May 11, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/jeffallan/claude-skills --skill kubernetes-specialist
0 commentsdiscussion
summary

Kubernetes workload deployment, configuration, security, and troubleshooting across single and multi-cluster environments.

  • Covers Deployments, StatefulSets, DaemonSets, Jobs, Helm charts, RBAC policies, NetworkPolicies, and storage configuration with declarative YAML manifests
  • Includes troubleshooting workflows for pod crashes, resource analysis, log inspection, and rollback procedures using kubectl commands
  • Enforces security best practices: resource limits, health probes, least-priv
skill.md

Kubernetes Specialist

When to Use This Skill

  • Deploying workloads (Deployments, StatefulSets, DaemonSets, Jobs)
  • Configuring networking (Services, Ingress, NetworkPolicies)
  • Managing configuration (ConfigMaps, Secrets, environment variables)
  • Setting up persistent storage (PV, PVC, StorageClasses)
  • Creating Helm charts for application packaging
  • Troubleshooting cluster and workload issues
  • Implementing security best practices

Core Workflow

  1. Analyze requirements — Understand workload characteristics, scaling needs, security requirements
  2. Design architecture — Choose workload types, networking patterns, storage solutions
  3. Implement manifests — Create declarative YAML with proper resource limits, health checks
  4. Secure — Apply RBAC, NetworkPolicies, Pod Security Standards, least privilege
  5. Validate — Run kubectl rollout status, kubectl get pods -w, and kubectl describe pod <name> to confirm health; roll back with kubectl rollout undo if needed

Reference Guide

Load detailed guidance based on context:

Topic Reference Load When
Workloads references/workloads.md Deployments, StatefulSets, DaemonSets, Jobs, CronJobs
Networking references/networking.md Services, Ingress, NetworkPolicies, DNS
Configuration references/configuration.md ConfigMaps, Secrets, environment variables
Storage references/storage.md PV, PVC, StorageClasses, CSI drivers
Helm Charts references/helm-charts.md Chart structure, values, templates, hooks, testing, repositories
Troubleshooting references/troubleshooting.md kubectl debug, logs, events, common issues
Custom Operators references/custom-operators.md CRD, Operator SDK, controller-runtime, reconciliation
Service Mesh references/service-mesh.md Istio, Linkerd, traffic management, mTLS, canary
GitOps references/gitops.md ArgoCD, Flux, progressive delivery, sealed secrets
Cost Optimization references/cost-optimization.md VPA, HPA tuning, spot instances, quotas, right-sizing
Multi-Cluster references/multi-cluster.md Cluster API, federation, cross-cluster networking, DR

Constraints

MUST DO

  • Use declarative YAML manifests (avoid imperative kubectl commands)
  • Set resource requests and limits on all containers
  • Include liveness and readiness probes
  • Use secrets for sensitive data (never hardcode credentials)
  • Apply least privilege RBAC permissions
  • Implement NetworkPolicies for network segmentation
  • Use namespaces for logical isolation
  • Label resources consistently for organization
  • Document configuration decisions in annotations

MUST NOT DO

  • Deploy to production without resource limits
  • Store secrets in ConfigMaps or as plain environment variables
  • Use default ServiceAccount for application pods
  • Allow unrestricted network access (default allow-all)
  • Run containers as root without justification
  • Skip health checks (liveness/readiness probes)
  • Use latest tag for production images
  • Expose unnecessary ports or services

Common YAML Patterns

Deployment with resource limits, probes, and security context

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
  namespace: my-namespace
  labels:
    app: my-app
    version: "1.2.3"
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
        version: "1.2.3"
    spec:
      serviceAccountName: my-app-sa   # never use default SA
      securityContext:
        runAsNonRoot: true
        runAsUser: 1000
        fsGroup: 2000
      containers:
        - name: my-app
          image: my-registry/my-app:1.2.3   # never use latest
          ports:
            - containerPort: 8080
          resources:
            requests:
              cpu: "100m"
              memory: "128Mi"
            limits:
              cpu: "500m"
              memory: "512Mi"
          livenessProbe:
            httpGet:
              path: /healthz
              port: 8080
            initialDelaySeconds: 15
            periodSeconds: 20
          readinessProbe:
            httpGet:
              path: /ready
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 10
          securityContext:
            allowPrivilegeEscalation: false
            readOnlyRootFilesystem: true
            capabilities:
              drop: ["ALL"]
          envFrom:
            - secretRef:
                name: my-app-secret   # pull credentials from Secret, not ConfigMap

Minimal RBAC (least privilege)

apiVersion: v1
kind: ServiceAccount
metadata:
  name: my-app-sa
  namespace: my-namespace
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: my-app-role
  namespace: my-namespace
rules:
  - apiGroups: [""]
    resources: ["configmaps"]
    verbs: ["get", "list"]   # grant only what is needed
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: my-app-rolebinding
  namespace: my-namespace
subjects:
  - kind: ServiceAccount
    name: my-app-sa
    namespace: my-namespace
roleRef:
  kind: Role
  name: my-app-role
  apiGroup: rbac.authorization.k8s.io

NetworkPolicy (default-deny + explicit allow)

# Deny all ingress and egress by default
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: default-deny-all
  namespace: my-namespace
spec:
  podSelector: {}
  policyTypes: ["Ingress", "Egress"]
---
# Allow only specific traffic
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-my-app
  namespace: my-namespace
spec:
  podSelector:
    matchLabels:
      app: my-app
  policyTypes: ["Ingress"]
  ingress:
    - from:
        - podSelector:
            matchLabels:
              app: frontend
      ports:
        - protocol: TCP
          port: 8080

Validation Commands

After deploying, verify health and security posture:

# Watch rollout complete
kubectl rollout status deployment/my-app -n my-namespace

# Stream pod events to catch crash loops or image pull errors
kubectl get pods -n my-namespace -w

# Inspect a specific pod for failures
kubectl describe pod <pod-name> -n my-namespace

# Check container logs
kubectl logs <pod-name> -n my-namespace --previous   
how to use kubernetes-specialist

How to use kubernetes-specialist on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add kubernetes-specialist
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jeffallan/claude-skills --skill kubernetes-specialist

The skills CLI fetches kubernetes-specialist from GitHub repository jeffallan/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/kubernetes-specialist

Reload or restart Cursor to activate kubernetes-specialist. Access the skill through slash commands (e.g., /kubernetes-specialist) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.654 reviews
  • Charlotte Yang· Dec 20, 2024

    Useful defaults in kubernetes-specialist — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mia Menon· Dec 16, 2024

    We added kubernetes-specialist from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Hana Flores· Dec 12, 2024

    kubernetes-specialist has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Mia Mehta· Dec 12, 2024

    kubernetes-specialist reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Dhruvi Jain· Dec 4, 2024

    Solid pick for teams standardizing on skills: kubernetes-specialist is focused, and the summary matches what you get after install.

  • Oshnikdeep· Nov 23, 2024

    We added kubernetes-specialist from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Mia Verma· Nov 11, 2024

    Keeps context tight: kubernetes-specialist is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Charlotte Kapoor· Nov 11, 2024

    Registry listing for kubernetes-specialist matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Arjun Diallo· Nov 7, 2024

    Solid pick for teams standardizing on skills: kubernetes-specialist is focused, and the summary matches what you get after install.

  • Arjun Abebe· Nov 3, 2024

    kubernetes-specialist fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

showing 1-10 of 54

1 / 6