rag-implementation
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
105 skills found
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Create, alter, and validate Snowflake semantic views using the Snowflake CLI.
Python skill for high-performance storage of chunked N-dimensional arrays using Zarr, supporting cloud storage (S3/GCS), parallel I/O, and integration with NumPy, Dask, and Xarray.
Syntax and construction guide for HashQL J-Expr queries, supporting #literal, #struct, #list, and function call patterns for HashQL files.
Efficiently manage git worktrees with automated file synchronization, background task execution, and CLI-based workspace orchestration.
Control and monitor Xiaomi Mijia smart home devices including status switching, device discovery, automation scenes, and environmental statistics.
Expert guidance for Neo4j Cypher queries and MCP server tools, focusing on schema introspection, graph operations, and efficient database development workflows.
Unified CLI tool to read, query, discover, and write AI agent conversations using the agents:// URI scheme across multiple coding agents and providers.
Efficiently extract, filter, and transform specific fields from JSON files using jq, saving up to 95% of context window usage compared to reading full files.
Query the Pollinations text API with web-search enabled models like Gemini and Perplexity for grounded, real-time research.
Generate spectrograms and advanced audio feature visualizations directly from your terminal with this audio analysis CLI.
Transform AI agents into proactive partners using WAL Protocol, persistent memory buffers, and autonomous cron scheduling to anticipate needs and improve performance.