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Found 139 Skills
PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector setup, indexing (HNSW, IVFFlat), hybrid search (FTS + BM25 + RRF), ParadeDB as Elasticsearch alternative, and re-ranking with Cohere/cross-encoders. Supports vector(1536) and halfvec(3072) types for OpenAI embeddings. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch
Work with JSONB data - queries, indexing, transformations
Fetch and persist article full text for RSS entries already stored in SQLite by ai-tech-rss-fetch. Use when backfilling or incrementally syncing body text from entries.url or entries.canonical_url into a companion table for downstream indexing, retrieval, or summarization.
MongoDB document modeling, aggregation pipeline optimization, sharding strategies, replica set configuration, connection pool management, and indexing patterns. Use this skill for MongoDB-specific issues, NoSQL performance optimization, and schema design.
Elasticsearch development best practices for indexing, querying, and search optimization
Check Meilisearch index status, tasks, health, and settings. Use for debugging search issues, monitoring indexing tasks, and inspecting index configuration. Read-only admin operations.
Set up and configure Torii indexer for GraphQL queries, gRPC subscriptions, and SQL access. Use when indexing your deployed world for client queries or real-time updates.
Expert blueprint for GDSkills skill discovery and indexing system. Enables AI agents to find relevant skills by topic/keyword. Use when building skill libraries OR implementing search functionality. Keywords skill discovery, indexing, search, metadata, skill registry.
Expert knowledge for Azure AI Video Indexer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Video Indexer APIs/widgets, live camera indexing, custom speech/brand models, or Azure OpenAI integrations, and other Azure AI Video Indexer related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure AI Vision (use azure-ai-vision).
Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.
Database specialist covering PostgreSQL, MongoDB, Redis, Oracle, and advanced data patterns for modern applications. Use when user asks about database schema design, query optimization, indexing strategies, data modeling, migrations, ORM configuration, or database performance tuning. Do NOT use for API design or server-side business logic (use moai-domain-backend instead).
Database schema design, indexing, and migration guidance for MongoDB-based applications.