Design database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for PostgreSQL and MySQL.
Install
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill database-schema-designSKILL.md
Database Schema Design
Table of Contents
Overview
Design scalable, normalized database schemas with proper relationships, constraints, and data types. Includes normalization techniques, relationship patterns, and constraint strategies.
When to Use
- New database schema design
- Data model planning
- Table structure definition
- Relationship design (1:1, 1:N, N:N)
- Normalization analysis
- Constraint and trigger planning
- Performance optimization at schema level
Quick Start
PostgreSQL - Eliminate Repeating Groups:
-- NOT 1NF: repeating group in single column
CREATE TABLE orders_bad (
id UUID PRIMARY KEY,
customer_name VARCHAR(255),
product_ids VARCHAR(255) -- "1,2,3" - repeating group
);
-- 1NF: separate table for repeating data
CREATE TABLE orders (
id UUID PRIMARY KEY,
customer_name VARCHAR(255),
created_at TIMESTAMP DEFAULT NOW()
);
CREATE TABLE order_items (
id UUID PRIMARY KEY,
order_id UUID NOT NULL,
product_id UUID NOT NULL,
quantity INTEGER NOT NULL,
FOREIGN KEY (order_id) REFERENCES orders(id) ON DELETE CASCADE
);
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| First Normal Form (1NF) | First Normal Form (1NF) |
| Second Normal Form (2NF) | Second Normal Form (2NF) |
| Third Normal Form (3NF) | Third Normal Form (3NF) |
| Entity-Relationship Patterns | Entity-Relationship Patterns |
Best Practices
✅ DO
- Follow established patterns and conventions
- Write clean, maintainable code
- Add appropriate documentation
- Test thoroughly before deploying
❌ DON'T
- Skip testing or validation
- Ignore error handling
- Hard-code configuration values
Related skills
azure-kustomicrosoft605KQuery and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection.supabase-postgres-best-practicessupabase421KPostgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or imporprisma-database-setupprisma321KGuides for configuring Prisma with different database providers (PostgreSQL, MySQL, SQLite, MongoDB, etc.). Use when setting up a new project, changing databases, or troubleshooting connection issues. Triggers on "configure postgres", "connect to mysql", "setup mongodb", "sqlite setup".prisma-client-apiprisma320KPrisma Client API reference covering model queries, filters, operators, and client methods. Use when writing database queries, using CRUD operations, filtering data, or configuring Prisma Client. Triggers on "prisma query", "findMany", "create", "update", "delete", "$transaction".