RAG Retrieval Patterns
Implements production-ready Retrieval-Augmented Generation patterns to ground AI responses in factual data and minimize hallucinations.
The RAG Retrieval skill provides a comprehensive toolkit for building high-performance, grounded AI applications. It offers standardized patterns for basic retrieval, inline citation tracking, and hybrid search techniques like Reciprocal Rank Fusion (RRF). Beyond simple search, it introduces advanced 2026 best practices for context sufficiency checks, which evaluate retrieved data before generation to prevent the model from guessing when information is missing. This skill is essential for developers building documentation bots, knowledge management systems, or any AI tool requiring verifiable factual accuracy.