postgres-semantic-search

postgres-semantic-search is a RAG & retrieval skill for AI agents, published by laguagu in the claude-code-nextjs-skills repository on GitHub. Skillspace rates postgres-semantic-search D (63/100) and it passed the safety scan; the rating is based on static analysis only.

PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector indexing, hybrid FTS/BM25 + RRF, ParadeDB, reranking, halfvec, multilingual search, query translation, and domain evals. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, Voyage rerank, graceful fallback, iterative_scan, filtered HNSW, websearch_to_tsquery, unaccent, multilingual FTS, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch, evaluation, benchmarking, Hit@K, MRR, halfvec cast, cross-lingual retrieval, non-English corpus, per-language indexing, query translation, RRF fusion across languages

Grade

D

Quality

63 / 100

Safety

Passed

GitHub stars

57

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