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Found 158 Skills
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
Configure and manage the GrepAI watch daemon. Use this skill for real-time code indexing and file monitoring.
Three.js 3D building system with spatial indexing, structural physics, and multiplayer networking. Use when creating survival games, sandbox builders, or any game with player-constructed structures. Covers performance optimization (spatial hash grids, octrees, chunk loading), structural validation (arcade/heuristic/realistic physics modes), and multiplayer sync (delta compression, client prediction, conflict resolution).
MongoDB query optimization and indexing strategies. Use when writing queries, creating indexes, building aggregation pipelines, or debugging slow operations. Triggers on "slow query", "create index", "optimize query", "aggregation pipeline", "explain output", "COLLSCAN", "ESR rule", "compound index", "partial index", "TTL index", "text search", "geospatial", "$indexStats", "profiler".
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.
Database schema design, indexing, and migration guidance for MongoDB-based applications.
Optimize SQL queries for performance with indexing strategies, query rewriting, and execution plan analysis. Use when queries are slow, optimizing database performance, or analyzing query execution.
Expert-level MongoDB database design, aggregation pipelines, indexing, replication, and production operations
Apply quantization to reduce memory by 4-32x. Enable HNSW indexing for 150x faster search. Configure caching strategies and implement batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors. Deploy these optimizations to achieve 12,500x performance gains.
Work with JSONB data - queries, indexing, transformations
Ingest and transform large data files (CSV/JSON) into Elasticsearch indices. Stream-based processing for files up to 30GB, cross-version migration (ES 8.x ↔ 9.x), custom JavaScript transformations, and reindexing with transforms. Use when you need to load data into Elasticsearch, migrate indices, or transform data during ingestion.
Reviews PostgreSQL code for indexing strategies, JSONB operations, connection pooling, and transaction safety. Use when reviewing SQL queries, database schemas, JSONB usage, or connection management.