postgres▌

<essential_principles>

Postgres performance optimization rules across 8 priority categories, from query tuning to advanced features. \n \n Organized into 8 rule categories prioritized by impact: query performance and connection management (critical), security and RLS, schema design, concurrency, data access patterns, monitoring, and advanced features \n Each rule includes detailed explanations, incorrect vs. correct SQL examples, EXPLAIN output analysis, and performance metrics to guide optimization decisions \n Cover

Comprehensive Postgres guidance covering schema design, query optimization, replication, and PlanetScale-specific operations. \n \n Covers eight core topics: schema design, indexing, partitioning, query patterns, MVCC/VACUUM, process and memory architecture, WAL operations, and backup/recovery \n Includes PlanetScale-specific references for connection pooling, PgBouncer configuration, extensions, and the pscale CLI \n Provides optimization checklists, monitoring strategies via pg_stat views, and

Setup and programmatic management of Prisma Postgres databases across Console, CLI, and APIs. \n \n Four core workflows: manual Console setup, instant provisioning via create-db CLI, REST API integration with service tokens or OAuth, and type-safe TypeScript integration via @prisma/management-api-sdk \n Supports temporary database creation with auto-deletion after ~24 hours, claim URLs for persistence, and region selection \n Management API available at https://api.prisma.io/v1 with OpenAPI docs

Expert patterns for Neon serverless Postgres, branching, connection pooling, and ORM integration. \n \n Covers Prisma and Drizzle ORM setup with Neon, including dual connection string configuration (pooled vs. direct) for migrations and application queries \n Explains PgBouncer connection pooling limits (10K concurrent connections) and reserved superuser connections \n Provides guidance on choosing between Neon's neon-http driver (single queries) and neon-serverless driver (transactions and WebS

Comprehensive performance optimization guide for Postgres, maintained by Supabase. Contains rules across 8 categories, prioritized by impact to guide automated query optimization and schema design.

Analyze a single target project to identify data access artifacts that require integration testing, then produce a structured, actionable testing plan.

Execute safe, read-only queries against configured PostgreSQL databases.

postgres-schema-design

This skill covers using PostgreSQL with the pgvector extension as the storage backend for GrepAI.