
database-schema-designer
by yonatangross
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SKILL.md
name: database-schema-designer description: SQL and NoSQL schema design with normalization, indexing, and migration patterns. Use when designing database schemas, creating tables, optimizing slow queries, or planning database migrations. version: 2.0.0 author: AI Agent Hub tags: [database, schema-design, sql, nosql, performance, migrations] context: fork agent: database-engineer user-invocable: false
Database Schema Designer
This skill provides comprehensive guidance for designing robust, scalable database schemas for both SQL and NoSQL databases. Whether building from scratch or evolving existing schemas, this framework ensures data integrity, performance, and maintainability.
Overview
- Designing new database schemas
- Refactoring or migrating existing schemas
- Optimizing database performance
- Choosing between SQL and NoSQL approaches
- Creating database migrations
- Establishing indexing strategies
- Modeling complex relationships
- Planning data archival and partitioning
Database Design Philosophy
Core Principles
1. Model the Domain, Not the UI
- Schema reflects business entities and relationships
- Don't let UI requirements drive data structure
- Separate presentation concerns from data model
2. Optimize for Reads or Writes (Not Both)
- OLTP (transactional): Normalized, optimized for writes
- OLAP (analytical): Denormalized, optimized for reads
- Choose based on access patterns
3. Plan for Scale From Day One
- Indexing strategy
- Partitioning approach
- Caching layer
- Read replicas
4. Data Integrity Over Performance
- Use constraints, foreign keys, validation
- Performance issues can be optimized later
- Data corruption is costly to fix
SQL Database Design
Normalization
Database normalization reduces redundancy and ensures data integrity.
1st Normal Form (1NF)
Rule: Each column contains atomic (indivisible) values, no repeating groups.
-- ❌ Violates 1NF (multiple values in one column)
CREATE TABLE orders (
id INT PRIMARY KEY,
customer_id INT,
product_ids VARCHAR(255) -- '101,102,103' (bad!)
);
-- ✅ Follows 1NF
CREATE TABLE orders (
id INT PRIMARY KEY,
customer_id INT
);
CREATE TABLE order_items (
id INT PRIMARY KEY,
order_id INT,
product_id INT,
FOREIGN KEY (order_id) REFERENCES orders(id)
);
2nd Normal Form (2NF)
Rule: Must be in 1NF + all non-key columns depend on the entire primary key.
3rd Normal Form (3NF)
Rule: Must be in 2NF + no transitive dependencies (non-key columns depend only on primary key).
Indexing Strategies
Indexes speed up reads but slow down writes. Use strategically.
When to Create Indexes
-- ✅ Index foreign keys
CREATE INDEX idx_orders_customer_id ON orders(customer_id);
-- ✅ Index frequently queried columns
CREATE INDEX idx_users_email ON users(email);
-- ✅ Index columns used in WHERE, ORDER BY, GROUP BY
CREATE INDEX idx_orders_created_at ON orders(created_at);
-- ✅ Composite index for multi-column queries
CREATE INDEX idx_orders_customer_status ON orders(customer_id, status);
Composite Indexes (Column Order Matters)
-- ✅ Good: Index supports both queries
CREATE INDEX idx_orders_customer_status ON orders(customer_id, status);
-- Query 1: Uses index efficiently
SELECT * FROM orders WHERE customer_id = 123 AND status = 'pending';
-- Query 2: Uses index (customer_id only)
SELECT * FROM orders WHERE customer_id = 123;
-- ❌ Query 3: Doesn't use index (status is second column)
SELECT * FROM orders WHERE status = 'pending';
Rule of Thumb: Put most selective column first, or most frequently queried alone.
Constraints
Use constraints to enforce data integrity at the database level.
CREATE TABLE products (
id INT PRIMARY KEY,
price DECIMAL(10, 2) CHECK (price >= 0),
stock INT CHECK (stock >= 0),
discount_percent INT CHECK (discount_percent BETWEEN 0 AND 100)
);
Database Migrations
Migration Best Practices
1. Always Reversible
-- Up migration
ALTER TABLE users ADD COLUMN phone VARCHAR(20);
-- Down migration
ALTER TABLE users DROP COLUMN phone;
2. Backward Compatible
-- ✅ Good: Add nullable column
ALTER TABLE users ADD COLUMN middle_name VARCHAR(50);
-- ❌ Bad: Add required column (breaks existing code)
ALTER TABLE users ADD COLUMN middle_name VARCHAR(50) NOT NULL;
3. Data Migrations Separate from Schema Changes
-- Migration 1: Schema change
ALTER TABLE orders ADD COLUMN status VARCHAR(20) DEFAULT 'pending';
-- Migration 2: Data migration
UPDATE orders SET status = 'completed' WHERE completed_at IS NOT NULL;
Quick Start Checklist
When designing a new schema:
- Identify entities and relationships
- Choose SQL or NoSQL based on requirements
- Normalize to 3NF (SQL) or decide embed/reference (NoSQL)
- Define primary keys (INT auto-increment or UUID)
- Add foreign key constraints
- Choose appropriate data types
- Add unique constraints where needed
- Plan indexing strategy (foreign keys, WHERE columns)
- Add NOT NULL constraints for required fields
- Create CHECK constraints for validation
- Plan for soft deletes (deleted_at column) if needed
- Add timestamps (created_at, updated_at)
- Design migration scripts (up and down)
- Test migrations on staging
Related Skills
alembic-migrations- Alembic-specific migration patterns for SQLAlchemy projectszero-downtime-migration- Safe schema changes without service interruptiondatabase-versioning- Version control strategies for database objectscaching-strategies- Cache layer design to complement database performance
Key Decisions
| Decision | Choice | Rationale |
|---|---|---|
| Normalization target | 3NF for OLTP | Reduces redundancy while maintaining query performance |
| Primary key strategy | INT auto-increment or UUID | UUIDs for distributed systems, INT for single-database |
| Soft deletes | deleted_at timestamp column | Preserves audit trail, enables recovery, supports compliance |
| Composite index order | Most selective column first | Optimizes index usage for common query patterns |
Skill Version: 2.0.0 Last Updated: 2026-01-08 Maintained by: AI Agent Hub Team
Capability Details
schema-design
Keywords: schema, table, entity, relationship, erd Solves:
- Design database schema
- Model relationships
- ERD creation
normalization
Keywords: normalize, 1nf, 2nf, 3nf, denormalize Solves:
- Normalization levels
- When to denormalize
- Reduce redundancy
indexing
Keywords: index, b-tree, composite, query performance Solves:
- Which columns to index
- Optimize slow queries
- Index types
migrations
Keywords: migration, alter table, zero downtime, backward compatible Solves:
- Write safe migrations
- Zero-downtime changes
- Reversible migrations
Score
Total Score
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