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Found 325 Skills
Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning a database migration, reviewing migration artifacts, or validating that integration tests cover Oracle/PostgreSQL differences.
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
Golang backend architecture expert. Use when designing Go services with Gin, implementing layered architecture, configuring sqlc with PostgreSQL/Supabase, or building API authentication.
Complete guide for using drift database library in Dart applications (CLI, server-side, non-Flutter). Use when building Dart apps that need local SQLite database storage or PostgreSQL connection with type-safe queries, reactive streams, migrations, and efficient CRUD operations. Includes setup with sqlite3 package, PostgreSQL support with drift_postgres, connection pooling, and server-side patterns.
Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database operations.
List and test exposed PostgreSQL RPC functions for security issues and potential RLS bypass.
CRITICAL - Detect exposed PostgreSQL database connection strings in client-side code. Direct DB access is a P0 issue.
Database operations for SQLite, PostgreSQL, and MySQL. Use for queries, schema inspection, migrations, and AI-assisted query generation.
Clean and format SQL migrations for Supabase - idempotency, RLS policies, formatting, schema fixes. Use when: fix this SQL, clean migration, RLS policy, Supabase schema, format postgres, prepare for SQL Editor, idempotent migration.
This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
Comprehensive guide for database management patterns covering PostgreSQL and MongoDB including schema design, indexing, transactions, replication, and performance tuning