Can it help with Row Level Security (RLS)?

Absolutely. It includes optimized RLS policy templates and patterns designed to ensure secure and efficient data access at the database level.

How does this skill help with database performance?

It provides optimized indexing strategies (like GIN and BRIN) and anti-pattern detection to identify slow queries, unindexed foreign keys, and table bloat.

Does it follow specific industry standards?

Yes, the patterns are based on Supabase best practices and MIT-licensed production-grade PostgreSQL implementation standards.

Is it suitable for managing database migrations?

Yes, it offers guidance on correct data types and schema design patterns ideal for writing safe, scalable, and maintainable database migrations.

PostgreSQL Patterns

Name: PostgreSQL Patterns
Author: affaan-m

byaffaan-m

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172,651

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데이터베이스 관리

Provides optimized PostgreSQL patterns for query performance, schema design, and database security within Claude Code.

The postgres-patterns skill equips Claude with specialized knowledge for architecting and maintaining high-performance PostgreSQL databases. It offers a quick reference for optimal index types, data type selection, and advanced SQL patterns like Row Level Security (RLS), cursor-based pagination, and queue processing with SKIP LOCKED. By integrating Supabase best practices, it helps developers detect anti-patterns such as unindexed foreign keys or table bloat, ensuring database migrations and queries are production-ready and scalable.

주요 기능

01Automated anti-pattern detection for slow queries and table bloat

02Data type best practices for IDs, strings, and timestamps

03Advanced SQL snippets for UPSERT and Cursor Pagination

04172,651 GitHub stars

05Optimized Row Level Security (RLS) implementation patterns

06Index selection guide for B-tree, GIN, BRIN, and Partial indexes

사용 사례

01Securing multi-tenant applications with production-grade RLS policies

02Troubleshooting slow queries and implementing indexing strategies

03Designing and optimizing database schemas and migrations

주요 기능

01Automated anti-pattern detection for slow queries and table bloat

02Data type best practices for IDs, strings, and timestamps

03Advanced SQL snippets for UPSERT and Cursor Pagination

04172,651 GitHub stars

05Optimized Row Level Security (RLS) implementation patterns

06Index selection guide for B-tree, GIN, BRIN, and Partial indexes

사용 사례

01Securing multi-tenant applications with production-grade RLS policies

02Troubleshooting slow queries and implementing indexing strategies

03Designing and optimizing database schemas and migrations