How does the skill handle database security?

It provides optimized Row Level Security (RLS) policy patterns and security default templates to ensure robust data access control.

Why does it recommend cursor pagination over OFFSET?

The skill promotes cursor pagination because it maintains O(1) performance, whereas OFFSET-based pagination becomes increasingly slow (O(n)) as the dataset grows.

Which index type should I use for JSONB data?

This skill recommends using GIN (Generalized Inverted Index) for JSONB columns to enable fast containment and key existence queries.

Can I use this for troubleshooting slow queries?

Yes, it includes specialized queries for pg_stat_statements to identify and analyze the most time-consuming operations in your database.

PostgreSQL Patterns & Optimization

Name: PostgreSQL Patterns & Optimization
Author: hieuck

byhieuck

0•

数据库管理

Optimizes database development with expert PostgreSQL patterns for query performance, schema design, and high-performance indexing.

This Claude Code skill provides a comprehensive suite of PostgreSQL best practices and implementation patterns designed to maximize database performance, security, and scalability. Based on Supabase industry standards, it helps developers navigate complex tasks such as choosing optimal index types (B-tree, GIN, BRIN), implementing Row Level Security (RLS), and managing connection pooling. It includes built-in detection for common anti-patterns like unindexed foreign keys and table bloat, ensuring your database remains efficient and maintainable as your application grows.

主要功能

01Anti-pattern detection for unindexed foreign keys and slow queries

02Production-grade SQL templates for UPSERT and cursor pagination

03Automated configuration recommendations for connection limits and timeouts

04Optimized Row Level Security (RLS) implementation patterns

05Advanced indexing guide for B-tree, GIN, and BRIN types

060 GitHub stars

使用场景

01Designing scalable and secure database schemas for multi-tenant applications

02Implementing efficient queue processing and pagination within PostgreSQL

03Optimizing slow-running SQL queries and identifying performance bottlenecks

主要功能

01Anti-pattern detection for unindexed foreign keys and slow queries

02Production-grade SQL templates for UPSERT and cursor pagination

03Automated configuration recommendations for connection limits and timeouts

04Optimized Row Level Security (RLS) implementation patterns

05Advanced indexing guide for B-tree, GIN, and BRIN types

060 GitHub stars

使用场景

01Designing scalable and secure database schemas for multi-tenant applications

02Implementing efficient queue processing and pagination within PostgreSQL

03Optimizing slow-running SQL queries and identifying performance bottlenecks