hybrid-search-implementation

Quick Review

Excellent hybrid search skill with comprehensive implementation patterns. The description clearly identifies use cases (RAG systems, search engines, combining semantic + exact matching). Provides four complete, production-ready templates covering pure Python fusion algorithms, PostgreSQL with pgvector, Elasticsearch integration, and a full RAG pipeline. Strong task knowledge with RRF and linear combination methods, proper normalization, database schema setup, and reranking strategies. Well-structured with clear architecture diagrams, comparison tables, and best practices. High novelty—implementing hybrid search with proper fusion algorithms, database-specific optimizations, and reranking would require significant effort and domain expertise from a CLI agent alone. Minor improvement possible: could include performance benchmarking guidance or adaptive weight tuning strategies.