engineering-skills▌
alirezarezvani/claude-skills · updated Apr 24, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
23 production-ready engineering skills organized into core engineering, AI/ML/Data, and specialized tools.
Engineering Team Skills
23 production-ready engineering skills organized into core engineering, AI/ML/Data, and specialized tools.
Quick Start
Claude Code
/read engineering-team/senior-fullstack/SKILL.md
Codex CLI
npx agent-skills-cli add alirezarezvani/claude-skills/engineering-team
Skills Overview
Core Engineering (13 skills)
| Skill | Folder | Focus |
|---|---|---|
| Senior Architect | senior-architect/ |
System design, architecture patterns |
| Senior Frontend | senior-frontend/ |
React, Next.js, TypeScript, Tailwind |
| Senior Backend | senior-backend/ |
API design, database optimization |
| Senior Fullstack | senior-fullstack/ |
Project scaffolding, code quality |
| Senior QA | senior-qa/ |
Test generation, coverage analysis |
| Senior DevOps | senior-devops/ |
CI/CD, infrastructure, containers |
| Senior SecOps | senior-secops/ |
Security operations, vulnerability management |
| Code Reviewer | code-reviewer/ |
PR review, code quality analysis |
| Senior Security | senior-security/ |
Threat modeling, STRIDE, penetration testing |
| AWS Solution Architect | aws-solution-architect/ |
Serverless, CloudFormation, cost optimization |
| MS365 Tenant Manager | ms365-tenant-manager/ |
Microsoft 365 administration |
| TDD Guide | tdd-guide/ |
Test-driven development workflows |
| Tech Stack Evaluator | tech-stack-evaluator/ |
Technology comparison, TCO analysis |
AI/ML/Data (5 skills)
| Skill | Folder | Focus |
|---|---|---|
| Senior Data Scientist | senior-data-scientist/ |
Statistical modeling, experimentation |
| Senior Data Engineer | senior-data-engineer/ |
Pipelines, ETL, data quality |
| Senior ML Engineer | senior-ml-engineer/ |
Model deployment, MLOps, LLM integration |
| Senior Prompt Engineer | senior-prompt-engineer/ |
Prompt optimization, RAG, agents |
| Senior Computer Vision | senior-computer-vision/ |
Object detection, segmentation |
Specialized Tools (5 skills)
| Skill | Folder | Focus |
|---|---|---|
| Playwright Pro | playwright-pro/ |
E2E testing (9 sub-skills) |
| Self-Improving Agent | self-improving-agent/ |
Memory curation (5 sub-skills) |
| Stripe Integration | stripe-integration-expert/ |
Payment integration, webhooks |
| Incident Commander | incident-commander/ |
Incident response workflows |
| Email Template Builder | email-template-builder/ |
HTML email generation |
Python Tools
30+ scripts, all stdlib-only. Run directly:
python3 <skill>/scripts/<tool>.py --help
No pip install needed. Scripts include embedded samples for demo mode.
Rules
- Load only the specific skill SKILL.md you need — don't bulk-load all 23
- Use Python tools for analysis and scaffolding, not manual judgment
- Check CLAUDE.md for tool usage examples and workflows
How to use engineering-skills 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 engineering-skills
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches engineering-skills from GitHub repository alirezarezvani/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 engineering-skills. Access the skill through slash commands (e.g., /engineering-skills) 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
4.6★★★★★48 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
Registry listing for engineering-skills matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yusuf Gupta· Dec 16, 2024
Registry listing for engineering-skills matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kwame Kapoor· Dec 8, 2024
Useful defaults in engineering-skills — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Fatima Singh· Dec 4, 2024
We added engineering-skills from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Noor Rao· Nov 27, 2024
I recommend engineering-skills for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Fatima Harris· Nov 23, 2024
engineering-skills fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Piyush G· Nov 19, 2024
Keeps context tight: engineering-skills is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Harper Flores· Nov 7, 2024
Keeps context tight: engineering-skills is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ishan Abbas· Oct 26, 2024
I recommend engineering-skills for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Aanya Liu· Oct 18, 2024
Keeps context tight: engineering-skills is the kind of skill you can hand to a new teammate without a long onboarding doc.
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