postgres-patterns

Review PostgreSQL schemas and queries for optimization and security patterns.

2|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/Zenobia000/ai-brainstorming --skill postgres-patterns-zenobia000
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: postgres-patterns
Source: https://github.com/Zenobia000/ai-brainstorming/tree/main/.claude/custom-rule%26skill/skills/postgres-patterns
Command: npx skills add https://github.com/Zenobia000/ai-brainstorming --skill postgres-patterns-zenobia000

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the frustration of writing slow, unoptimized PostgreSQL queries, designing inefficient database schemas, and misconfiguring security settings that lead to performance bottlenecks, data bloat, and unauthorized access risks.

Core Features & Use Cases

  • Query Optimization: Provides index cheat sheets, cursor pagination patterns, and slow query anti-pattern detection to speed up database operations.
  • Schema Design Guidance: Covers correct data type selection, composite and covering index best practices, and partial index usage to reduce storage waste and improve query speed.
  • Security & Configuration: Includes optimized Row Level Security policy templates, connection pooling settings, and secure default configurations aligned with Supabase standards. Use Case: A backend developer building a new user management feature can use this Skill to quickly implement the correct indexes for common user lookup queries and set up RLS to ensure users can only access their own data.

Quick Start

Use the postgres-patterns skill to review your existing products table schema and add the optimal index for queries filtering by category and price range.

Frequently Asked Questions about postgres-patterns

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

FAQPage Schema
How do I optimize slow PostgreSQL queries in my application?

Optimize slow PostgreSQL queries by applying index cheat sheets, cursor pagination patterns, and slow query anti-pattern detection to eliminate performance bottlenecks and speed up database operations.

What are the best practices for PostgreSQL schema design and index selection?

PostgreSQL schema design best practices include correct data type selection, composite and covering index usage, and partial indexes to reduce storage waste and improve query speed.

How do I implement Row Level Security policies aligned with Supabase standards?

Implement Row Level Security policies using optimized templates and secure default configurations aligned with Supabase standards to prevent unauthorized data access risks in application workflows.

When should I use partial indexes vs composite indexes in PostgreSQL?

Use partial indexes to reduce storage waste for specific query subsets, and apply composite or covering indexes to optimize queries filtering by multiple columns like category and price range.

Does this approach work for configuring connection pooling in PostgreSQL?

Yes, configuring connection pooling in PostgreSQL is supported through optimized connection pooling settings designed to prevent bottlenecks and improve database performance for backend applications.