AI Skills for PostgreSQL

Facilitates knowledge base management and retrieval across various storage layers, enhancing organization and sync capabilities.

Provides comprehensive patterns for database access using JetBrains Exposed ORM, including DSL queries, DAO, and connection pooling.

Automates the verification process for Quarkus projects, ensuring builds, tests, and security scans are completed before deployment.

Provides best practices for Django architecture, REST API design, and ORM usage to build scalable and maintainable applications.

Provides JPA/Hibernate patterns for efficient entity design, query optimization, and transaction management in Spring Boot applications.

Provides best practices for database migrations, covering schema changes, data migration, rollback, and zero-downtime deployments.

Provides PostgreSQL database patterns for query optimization, schema design, indexing, and security based on Supabase best practices.

Helps diagnose and resolve Odoo performance issues, optimizing queries, configurations, and memory usage for better efficiency.

Provides a comprehensive backup and restore strategy for Odoo, including automated scheduling and cloud storage integration.

Creates a new Rails project with a predefined tech stack including PostgreSQL, Inertia.js, React, and Tailwind CSS.

Sets up a production-ready Docker environment for Odoo with PostgreSQL, ensuring efficient deployment and management.

Provisions instant temporary Postgres databases for quick prototyping and development without requiring login or credit card.

Enhances SQL query performance through optimization techniques, indexing strategies, and EXPLAIN analysis for faster database operations.

Enables the creation of knowledge-grounded AI systems using Retrieval-Augmented Generation (RAG) with vector databases and semantic search.

Designs optimized PostgreSQL schemas with best practices for data types, indexing, and performance patterns.

Guides the design and implementation of event stores for event-sourced systems, optimizing event storage and retrieval.

Implements hybrid search combining vector and keyword methods for enhanced retrieval in search engines and RAG systems.

Facilitates efficient resource management in Python using context managers for reliable cleanup and streaming operations.

Facilitates the creation of production-ready FastAPI projects with async patterns and dependency injection for high-performance APIs.

Provides expert PostgreSQL code reviews focusing on best practices, anti-patterns, and unique quality standards for optimal database performance.