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A comprehensive guide maintained by Supabase for optimizing Postgres performance. It provides critical rules and best practices across query performance, schema design, connection management, and security (including RLS). Use this skill when writing, reviewing, or optimizing complex SQL queries, database schemas, or configurations to ensure optimal database health and performance.

Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

An expert assistant providing deep knowledge and best practices for Prisma ORM. It covers the entire lifecycle of database interaction, including optimal schema design, relation modeling, safe migration workflows, and advanced query optimization techniques (addressing N+1 issues and implementing raw queries) across PostgreSQL, MySQL, and SQLite.

This skill specializes in designing, optimizing, and evaluating prompts for Large Language Models (LLMs). It allows users to generate optimized prompt templates, structured output schemas (e.g., JSON mode, function calling), and comprehensive test suites. Use this skill when building new LLM applications, implementing complex reasoning patterns like Chain-of-Thought, defining system guardrails, or building robust evaluation frameworks to measure and improve model performance.

An advanced workflow orchestrator designed to perform multi-phase, deep-dive schema optimization on large datasets (e.g., BigQuery exports). It systematically analyzes schema structure, identifies unused or redundant fields, assesses potential impact, and generates a comprehensive, actionable report with recommended optimization strategies and estimated savings.

A specialized methodology for reviewing APIs, configuration schemas, and interfaces to identify 'footguns'—design choices where the path of least resistance leads to insecurity. This analysis focuses on making secure usage the default, covering topics like dangerous defaults, primitive vs. semantic type safety, and insecure algorithm selection. It is crucial for architects and reviewers to prevent developer misuse at the design level.

This skill provides systematic patterns and best practices for transforming slow database queries into high-performance operations. It covers techniques like proper indexing, query plan analysis (e.g., using EXPLAIN), schema design improvements, and resolving common issues like N+1 query problems. Use it to debug performance bottlenecks, reduce database load, and ensure scalable application backends.

A comprehensive skill for optimizing complex SQL queries, designing robust database schemas, and troubleshooting performance bottlenecks across various dialects (PostgreSQL, MySQL, etc.). Use this when queries are slow, complex set-based logic is needed (CTEs, Window Functions), or when structuring/migrating a database schema. It provides detailed query plan analysis, advanced indexing strategies, and industry best practices.

This skill provides comprehensive performance optimization and best practices for PostgreSQL, maintained by Supabase. It guides users on optimizing database performance, covering critical areas such as writing efficient SQL queries, designing robust schemas, implementing proper indexing, managing connection pooling, and enforcing Row-Level Security (RLS).

This skill translates complex business requirements and specification documents into a complete, production-ready Postgres schema for Supabase. It covers the full development lifecycle, including entity extraction, defining robust tables with constraints, generating migration SQL files, implementing Row Level Security (RLS) policies, and producing corresponding TypeScript types. It is the foundational step for building any robust SaaS application on Supabase.

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.

This powerful tool helps translate natural language requirements into robust, normalized relational database schemas. It can generate comprehensive schema designs, complete with relationships, constraints, and advanced architectural concerns like multi-tenancy, soft deletes, and audit trails. Furthermore, it automates the generation of database migrations (supporting Prisma, TypeORM, Alembic, etc.), corresponding type definitions (TypeScript/Python), seed data, and Entity-Relationship Diagrams (ERD) using Mermaid.