database-design▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Structured guidance for database selection, schema design, and query optimization decisions.
- ›Covers six core areas: database selection (PostgreSQL, Neon, Turso, SQLite), ORM choice (Drizzle, Prisma, Kysely), schema normalization, indexing strategy, query optimization, and safe migrations
- ›Emphasizes context-driven decision-making rather than defaulting to PostgreSQL; includes a checklist for schema design prerequisites
- ›Highlights common anti-patterns: unnecessary PostgreSQL adoption,
Database Design
Learn to THINK, not copy SQL patterns.
🎯 Selective Reading Rule
Read ONLY files relevant to the request! Check the content map, find what you need.
| File | Description | When to Read |
|---|---|---|
database-selection.md |
PostgreSQL vs Neon vs Turso vs SQLite | Choosing database |
orm-selection.md |
Drizzle vs Prisma vs Kysely | Choosing ORM |
schema-design.md |
Normalization, PKs, relationships | Designing schema |
indexing.md |
Index types, composite indexes | Performance tuning |
optimization.md |
N+1, EXPLAIN ANALYZE | Query optimization |
migrations.md |
Safe migrations, serverless DBs | Schema changes |
⚠️ Core Principle
- ASK user for database preferences when unclear
- Choose database/ORM based on CONTEXT
- Don't default to PostgreSQL for everything
Decision Checklist
Before designing schema:
- Asked user about database preference?
- Chosen database for THIS context?
- Considered deployment environment?
- Planned index strategy?
- Defined relationship types?
Anti-Patterns
❌ Default to PostgreSQL for simple apps (SQLite may suffice) ❌ Skip indexing ❌ Use SELECT * in production ❌ Store JSON when structured data is better ❌ Ignore N+1 queries
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
How to use database-design 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 database-design
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches database-design from GitHub repository sickn33/antigravity-awesome-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 database-design. Access the skill through slash commands (e.g., /database-design) 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▌
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★55 reviews- ★★★★★Isabella Gonzalez· Dec 28, 2024
We added database-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ren Rao· Dec 16, 2024
database-design has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ava Dixit· Dec 12, 2024
Solid pick for teams standardizing on skills: database-design is focused, and the summary matches what you get after install.
- ★★★★★Dhruvi Jain· Dec 8, 2024
Solid pick for teams standardizing on skills: database-design is focused, and the summary matches what you get after install.
- ★★★★★Oshnikdeep· Nov 27, 2024
We added database-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Lucas Jain· Nov 19, 2024
Solid pick for teams standardizing on skills: database-design is focused, and the summary matches what you get after install.
- ★★★★★Ren Ramirez· Nov 7, 2024
database-design fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Alexander Verma· Nov 3, 2024
We added database-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ren Menon· Oct 26, 2024
We added database-design from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Tariq Thompson· Oct 22, 2024
database-design fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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