postgres-patterns

Optimize PostgreSQL query performance and security with indexing and RLS policies.

89|19|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/krishnakanthb13/everything-antigravity --skill postgres-patterns-krishnakanthb13
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: postgres-patterns
Source: https://github.com/krishnakanthb13/everything-antigravity/tree/main/skills/postgres-patterns
Command: npx skills add https://github.com/krishnakanthb13/everything-antigravity --skill postgres-patterns-krishnakanthb13

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

PostgreSQL patterns provide a structured, battle-tested set of practices for building fast, secure, and scalable databases.

Core Features & Use Cases

  • Indexing strategies including B-tree, GIN, BRIN, partial indexes, and covering indexes for performance.
  • Data type and schema recommendations, including appropriate use of bigint, timestamptz, text, and constraints for data integrity.
  • Security and access control patterns, including Row Level Security (RLS) policies and safe querying practices.

Quick Start

Apply these patterns to your PostgreSQL project to improve query performance and security immediately.

Frequently Asked Questions about postgres-patterns

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

FAQPage Schema
How do I optimize PostgreSQL query performance using indexes?

Optimize PostgreSQL query performance by applying B-tree, GIN, BRIN, partial indexes, and covering indexes to accelerate data retrieval while avoiding common anti-patterns.

When should I use Row Level Security policies in PostgreSQL?

Use Row Level Security (RLS) policies in PostgreSQL when you need to enforce data access control and safe querying practices for scalable, multi-tenant database environments.

What are the best schema design patterns for scalable PostgreSQL databases?

The best schema design patterns for scalable PostgreSQL databases involve selecting appropriate data types like bigint, timestamptz, and text, alongside applying constraints to maintain data integrity.

Can I apply these PostgreSQL optimization patterns in Supabase?

Yes, these PostgreSQL optimization patterns apply directly to Supabase, allowing you to implement indexing strategies, schema designs, and RLS policies across similar PostgreSQL-based environments.

What are common PostgreSQL indexing anti-patterns to avoid?

Common PostgreSQL indexing anti-patterns include misusing data types, neglecting partial or covering indexes for specific queries, and deploying schemas without proper constraints for data integrity.