database-design
Helps your agent plan how to organize data in a database. This includes deciding how data will be stored and accessed efficiently.
What it does
This tool helps you plan how to organize and store information in a database. It guides you in choosing the best database type and organizing tables and data efficiently.
When to use it
- ✓When starting a new project and needing to decide where to store data.
- ✓When you want to improve the speed of accessing your data.
- ✓When planning how information relates within the database.
Example of what to ask your AI
“I want to create a to-do list app. What database should I use and how should I organize the tables to store tasks and users?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool analyzes your needs and suggests the best database options and ways to organize information. It considers factors like data type, expected volume, and how you will access it.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill database-designOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/database-design/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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
Use when selecting a database model, reviewing schema relationships and indexes, or assessing a proposed schema with the bundled advisory tools.
Schema helper
scripts/schema_validator.py is a read-only heuristic inventory, not a Prisma or Drizzle parser. Missing schemas, unsupported formats and heuristic-only results return nonzero with passed: false and analysis_complete: false. Use the project-local ORM validator for syntax and type checks; review migration and constraint semantics separately.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
What is a database?
It's an organized place where you store information, like a cabinet with drawers and folders.
What is a database schema?
It's the blueprint for how information will be organized in tables, defining what data goes in each and how they connect.
Why is data organization important?
Good organization makes data access faster and prevents errors, making your application more efficient.
Details
Original description by the author
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2717
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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