database-design

Validate Prisma schemas and guide database schema design and indexing.

Updated Jun 4, 2026
One-click install
npx skills add https://github.com/achmf/KostaHub --skill database-design-achmf
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: database-design
Source: https://github.com/achmf/KostaHub/tree/main/.agent/skills/database-design
Command: npx skills add https://github.com/achmf/KostaHub --skill database-design-achmf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill addresses the complexity of database architecture by providing a structured framework for schema design, indexing strategies, and technology selection, preventing common performance bottlenecks and maintenance issues.

Core Features & Use Cases

  • Technology Selection: Evaluate and choose between PostgreSQL, Neon, Turso, SQLite, and PlanetScale based on specific project requirements like edge deployment or vector search needs.
  • Performance Optimization: Implement effective indexing strategies and resolve N+1 query problems using EXPLAIN ANALYZE methodologies.
  • Schema Validation: Use the included validator script to check Prisma schemas for naming conventions, missing primary keys, and index optimization opportunities.

Quick Start

Use the database-design skill to validate the current project schema and suggest indexing improvements.

Frequently Asked Questions about database-design

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate my Prisma schema for missing primary keys and naming conventions?

You can validate a Prisma schema by running automated validation scripts that check for missing primary keys, naming convention inconsistencies, and index optimization opportunities. This identifies schema inconsistencies and performance anti-patterns.

What's the best way to choose between PostgreSQL, Neon, Turso, and PlanetScale for my project?

Evaluating database engines involves analyzing specific project requirements like edge deployment or vector search needs. Architectural guidance supports decision-making by comparing PostgreSQL, Neon, Turso, SQLite, and PlanetScale based on these constraints.

How do I resolve N+1 query problems and optimize database indexing strategies?

Resolving N+1 query problems requires implementing effective indexing strategies and using EXPLAIN ANALYZE methodologies. This provides architectural guidance for query optimization and helps identify performance bottlenecks.

How does schema validation prevent common database performance bottlenecks?

Schema validation prevents performance bottlenecks by providing a structured framework for schema design and indexing strategies. Automated scripts detect anti-patterns, missing primary keys, and suboptimal indexes before they cause maintenance issues.

Can I use automated validation scripts to plan database migrations across different engines?

Automated validation scripts facilitate migration planning across various database engines by identifying schema inconsistencies. They validate Prisma schemas and provide architectural guidance for technology selection and optimization.