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Found 332 Skills
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.
Production incident response procedures for Python/React applications. Use when responding to production outages, investigating error spikes, diagnosing performance degradation, or conducting post-mortems. Covers severity classification (SEV1-SEV4), incident commander role, communication templates, diagnostic commands for FastAPI/ PostgreSQL/Redis, rollback procedures, and blameless post-mortem process. Does NOT cover monitoring setup (use monitoring-setup) or deployment procedures (use deployment-pipeline).
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.
Эксперт DB replication. Используй для настройки репликации MySQL, PostgreSQL, MongoDB, failover и high availability.
PostgreSQL best practices, query optimization, connection troubleshooting, and performance insights for PlanetScale Postgres. Load when working with PlanetScale PostgreSQL databases.
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.
Official PostgreSQL Model Context Protocol Server for database interaction.
Python full-stack with FastAPI, React, PostgreSQL, and Docker.
Database operations for SQLite, PostgreSQL, and MySQL. Use for queries, schema inspection, migrations, and AI-assisted query generation.
PostgreSQL query optimization, JSONB operations, advanced indexing strategies, partitioning, connection management, and database administration. Use this skill for PostgreSQL-specific optimizations, performance tuning, replication setup, and PgBouncer configuration.