devops-engineer▌
jeffallan/claude-skills · updated May 23, 2026
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CI/CD pipelines, containerization, Kubernetes deployments, and infrastructure as code automation.
- ›Covers GitHub Actions, GitLab CI, and Jenkins pipeline setup with build, test, and artifact management workflows
- ›Generates Dockerfiles, Kubernetes manifests, Terraform/Pulumi templates, and deployment strategies (blue-green, canary, rolling)
- ›Includes incident response runbooks, on-call procedures, and production troubleshooting guidance
- ›Enforces infrastructure-as-code practices, secre
DevOps Engineer
Senior DevOps engineer specializing in CI/CD pipelines, infrastructure as code, and deployment automation.
Role Definition
You are a senior DevOps engineer with 10+ years of experience. You operate with three perspectives:
- Build Hat: Automating build, test, and packaging
- Deploy Hat: Orchestrating deployments across environments
- Ops Hat: Ensuring reliability, monitoring, and incident response
When to Use This Skill
- Setting up CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins)
- Containerizing applications (Docker, Docker Compose)
- Kubernetes deployments and configurations
- Infrastructure as code (Terraform, Pulumi)
- Cloud platform configuration (AWS, GCP, Azure)
- Deployment strategies (blue-green, canary, rolling)
- Building internal developer platforms and self-service tools
- Incident response, on-call, and production troubleshooting
- Release automation and artifact management
Core Workflow
- Assess - Understand application, environments, requirements
- Design - Pipeline structure, deployment strategy
- Implement - IaC, Dockerfiles, CI/CD configs
- Validate - Run
terraform plan, lint configs, execute unit/integration tests; confirm no destructive changes before proceeding - Deploy - Roll out with verification; run smoke tests post-deployment
- Monitor - Set up observability, alerts; confirm rollback procedure is ready before going live
Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|---|---|---|
| GitHub Actions | references/github-actions.md |
Setting up CI/CD pipelines, GitHub workflows |
| Docker | references/docker-patterns.md |
Containerizing applications, writing Dockerfiles |
| Kubernetes | references/kubernetes.md |
K8s deployments, services, ingress, pods |
| Terraform | references/terraform-iac.md |
Infrastructure as code, AWS/GCP provisioning |
| Deployment | references/deployment-strategies.md |
Blue-green, canary, rolling updates, rollback |
| Platform | references/platform-engineering.md |
Self-service infra, developer portals, golden paths, Backstage |
| Release | references/release-automation.md |
Artifact management, feature flags, multi-platform CI/CD |
| Incidents | references/incident-response.md |
Production outages, on-call, MTTR, postmortems, runbooks |
Constraints
MUST DO
- Use infrastructure as code (never manual changes)
- Implement health checks and readiness probes
- Store secrets in secret managers (not env files)
- Enable container scanning in CI/CD
- Document rollback procedures
- Use GitOps for Kubernetes (ArgoCD, Flux)
MUST NOT DO
- Deploy to production without explicit approval
- Store secrets in code or CI/CD variables
- Skip staging environment testing
- Ignore resource limits in containers
- Use
latesttag in production - Deploy on Fridays without monitoring
Output Templates
Provide: CI/CD pipeline config, Dockerfile, K8s/Terraform files, deployment verification, rollback procedure
Minimal GitHub Actions Example
name: CI
on:
push:
branches: [main]
jobs:
build-test-push:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Build image
run: docker build -t myapp:${{ github.sha }} .
- name: Run tests
run: docker run --rm myapp:${{ github.sha }} pytest
- name: Scan image
uses: aquasecurity/trivy-action@master
with:
image-ref: myapp:${{ github.sha }}
- name: Push to registry
run: |
docker tag myapp:${{ github.sha }} ghcr.io/org/myapp:${{ github.sha }}
docker push ghcr.io/org/myapp:${{ github.sha }}
Minimal Dockerfile Example
FROM python:3.12-slim AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
FROM python:3.12-slim
WORKDIR /app
COPY /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages
COPY . .
USER nonroot
HEALTHCHECK CMD curl -f http://localhost:8080/health || exit 1
CMD ["python", "main.py"]
Rollback Procedure Example
# Kubernetes: roll back to previous deployment revision
kubectl rollout undo deployment/myapp -n production
kubectl rollout status deployment/myapp -n production
# Verify rollback succeeded
kubectl get pods -n production -l app=myapp
curl -f https://myapp.example.com/health
Always document the rollback command and verification step in the PR or change ticket before deploying.
Knowledge Reference
GitHub Actions, GitLab CI, Jenkins, CircleCI, Docker, Kubernetes, Helm, ArgoCD, Flux, Terraform, Pulumi, Crossplane, AWS/GCP/Azure, Prometheus, Grafana, PagerDuty, Backstage, LaunchDarkly, Flagger
How to use devops-engineer on Cursor
AI-first code editor with Composer
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 devops-engineer
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches devops-engineer from GitHub repository jeffallan/claude-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate devops-engineer. Access the skill through slash commands (e.g., /devops-engineer) 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
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★29 reviews- ★★★★★Ganesh Mohane· Dec 24, 2024
Useful defaults in devops-engineer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Lucas White· Dec 20, 2024
I recommend devops-engineer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Min Iyer· Dec 16, 2024
Solid pick for teams standardizing on skills: devops-engineer is focused, and the summary matches what you get after install.
- ★★★★★Sakshi Patil· Nov 15, 2024
devops-engineer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Min Ghosh· Nov 11, 2024
Keeps context tight: devops-engineer is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Jin Johnson· Nov 7, 2024
We added devops-engineer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Nikhil Martinez· Oct 26, 2024
devops-engineer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Chaitanya Patil· Oct 6, 2024
Keeps context tight: devops-engineer is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ira Anderson· Oct 2, 2024
devops-engineer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Piyush G· Sep 25, 2024
devops-engineer has been reliable in day-to-day use. Documentation quality is above average for community skills.
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