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Found 333 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.
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.
Golang backend architecture expert. Use when designing Go services with Gin, implementing layered architecture, configuring sqlc with PostgreSQL/Supabase, or building API authentication.
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.
List and test exposed PostgreSQL RPC functions for security issues and potential RLS bypass.
Execute PostgreSQL queries and introspection with named project connections using `postgres-cli` V2. Use when the user asks to inspect data, run SQL, debug schema, validate config, or build schema cache artifacts.
Эксперт DB replication. Используй для настройки репликации MySQL, PostgreSQL, MongoDB, failover и high availability.
Official PostgreSQL Model Context Protocol Server for database interaction.
PostgreSQL best practices, query optimization, connection troubleshooting, and performance insights for PlanetScale Postgres. Load when working with PlanetScale PostgreSQL databases.
Query SQLite, PostgreSQL, and MySQL databases and export results to CSV/JSON. Use when: (1) Extracting data for reports, (2) Database backup and migration, (3) Data analysis workflows, or (4) Automated database queries.
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
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.