How does this skill improve database performance?

It analyzes your SQL code against Supabase's high-impact rules to identify missing indexes, inefficient joins, and sub-optimal data access patterns.

Can it help with Row-Level Security (RLS)?

Yes, the skill contains specific categories for Security and RLS to ensure your data policies are both performant and correctly implemented.

Is this skill only for Supabase users?

No, while the rules are maintained by Supabase, the best practices are applicable to any standard Postgres environment, including AWS RDS, GCP Cloud SQL, and self-hosted instances.

Does it provide concrete code examples?

Yes, the skill provides 'Before' and 'After' SQL examples to demonstrate exactly how to apply best practices to your specific code snippets.

Postgres Best Practices

Name: Postgres Best Practices
Author: sickn33

bysickn33

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31,722

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Database Management

Optimizes Postgres database performance and schema design using industry-leading standards maintained by Supabase.

This skill integrates the comprehensive Postgres performance optimization guide by Supabase directly into your development workflow. It enables Claude to provide expert-level guidance on query optimization, schema architecture, connection pooling, and Row-Level Security (RLS) implementation. By applying prioritized rules across eight critical categories—ranging from query execution speeds to concurrency management—the skill ensures that your database interactions are efficient, secure, and production-ready, helping to prevent common performance bottlenecks before they reach deployment.

Key Features

01Automated SQL query performance analysis and missing index detection

02Connection management and pooling configuration best practices

03Security auditing for Row-Level Security (RLS) and access patterns

0431,722 GitHub stars

05Production-grade schema design and indexing strategy recommendations

06Detailed SQL examples comparing inefficient and optimized implementations

Use Cases

01Refactoring slow SQL queries to improve execution times and resource usage

02Auditing Postgres security configurations to ensure data privacy and RLS compliance

03Designing scalable database schemas for new application features

Key Features

01Automated SQL query performance analysis and missing index detection

02Connection management and pooling configuration best practices

03Security auditing for Row-Level Security (RLS) and access patterns

0431,722 GitHub stars

05Production-grade schema design and indexing strategy recommendations

06Detailed SQL examples comparing inefficient and optimized implementations

Use Cases

01Refactoring slow SQL queries to improve execution times and resource usage

02Auditing Postgres security configurations to ensure data privacy and RLS compliance

03Designing scalable database schemas for new application features