From rmyndharis-antigravity-skills
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
How this skill is triggered — by the user, by Claude, or both
Slash command
/rmyndharis-antigravity-skills:hybrid-search-implementationThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Patterns for combining vector similarity and keyword-based search.
Patterns for combining vector similarity and keyword-based search.
resources/implementation-playbook.md.resources/implementation-playbook.md for detailed patterns and examples.npx claudepluginhub rmyndharis/antigravity-skills10plugins reuse this skill
First indexed Jun 2, 2026
Showing the 6 earliest of 10 plugins
Combines vector similarity and keyword search for improved retrieval in RAG systems and search engines. Use when pure vector search misses exact matches.
Combines vector and keyword search for improved retrieval in RAG systems and search engines. Covers fusion methods like RRF, linear weighting, cross-encoder reranking, and cascade filtering.
Builds production-ready semantic search with vector DBs (Pinecone/Qdrant/Weaviate), embeddings (OpenAI/Voyage/Cohere), chunking, hybrid search, and reranking for RAG systems.