Can it help me fix slow database queries?

Yes, it provides an indexing cheat sheet, anti-pattern detection scripts, and guidance on identifying slow queries using pg_stat_statements.

Does it include security recommendations?

Absolutely. The skill includes optimized patterns for Row Level Security (RLS) and security-focused configuration templates.

How does it handle pagination for large datasets?

The skill promotes O(1) cursor pagination patterns over traditional O(n) OFFSET pagination to ensure consistent performance as your data grows.

Are the patterns compatible with Supabase?

Yes, these patterns are based on Supabase best practices, making them ideal for both Supabase users and developers using standard PostgreSQL distributions.

What database system is this skill optimized for?

This skill is specifically designed for PostgreSQL, incorporating best practices derived from the Supabase team and MIT-licensed community standards.

PostgreSQL Patterns

Name: PostgreSQL Patterns
Author: hieuck

byhieuck

0•

数据库管理

Provides optimized PostgreSQL database patterns for query performance, schema design, and security enforcement.

This skill acts as a comprehensive reference for PostgreSQL best practices, offering Claude immediate access to high-performance query patterns, efficient schema design principles, and robust security configurations. Based on Supabase's battle-tested standards, it helps developers implement advanced indexing strategies like GIN and BRIN, select scalable data types, detect common database anti-patterns, and correctly configure Row Level Security (RLS). It is an essential companion for database migrations, architecting new schemas, and troubleshooting performance bottlenecks in production environments.

主要功能

01Production-ready SQL patterns for UPSERT, cursor pagination, and job queues

020 GitHub stars

03Anti-pattern detection scripts for unindexed foreign keys and table bloat

04Comprehensive indexing cheat sheet for B-tree, GIN, BRIN, and composite indexes

05Best-practice data type recommendations for IDs, strings, and monetary values

06Performance-tuned configuration templates for connection limits and timeouts

使用场景

01Optimizing slow SQL queries through advanced indexing and query restructuring

02Securing multi-tenant applications using optimized Row Level Security (RLS) policies

03Designing and implementing scalable database schemas for new applications

主要功能

01Production-ready SQL patterns for UPSERT, cursor pagination, and job queues

020 GitHub stars

03Anti-pattern detection scripts for unindexed foreign keys and table bloat

04Comprehensive indexing cheat sheet for B-tree, GIN, BRIN, and composite indexes

05Best-practice data type recommendations for IDs, strings, and monetary values

06Performance-tuned configuration templates for connection limits and timeouts

使用场景

01Optimizing slow SQL queries through advanced indexing and query restructuring

02Securing multi-tenant applications using optimized Row Level Security (RLS) policies

03Designing and implementing scalable database schemas for new applications