概要
The RAG Implementation skill provides a comprehensive framework for building production-grade Retrieval-Augmented Generation systems. It streamlines the process of integrating LLMs with external knowledge bases by offering standardized patterns for document chunking, embedding generation, and vector database configuration. Beyond basic retrieval, this skill guides developers through advanced optimization techniques like hybrid search, reranking, and contextual compression, ensuring that AI applications deliver accurate, fact-based responses while minimizing hallucinations through rigorous grounding and source citation.