hybrid-search-eval-author

Hybrid retrieval (BM25 + dense vector + optional reranker) is now the dominant production pattern for semantic search and RAG pipelines. The sibling skill vector-search-recall-tests covers recall@k for the vector stage in isolation. This skill covers the fused result: does RRF outperform a weighted sum? Does the reranker improve nDCG@10 enough to justify the added latency?

Per the [OpenSearch hybrid search blog], nDCG@10 improved an average of +12.08% over BM25 across seven BEIR datasets when using hybrid queries with normalization. The skill gives you the tests to verify - or disprove - that claim on your own corpus.

When to use