rag-hybrid-search
Hybrid search combining semantic and keyword retrieval for RAG pipelines. Implement BM25 + dense vector search with fusion strategies.
npx skills add a5c-ai/babysitter --skill rag-hybrid-search --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# rag-hybrid-search Implement hybrid search combining semantic vector retrieval with keyword-based BM25 search for improved RAG pipeline accuracy and recall. ## Overview Hybrid search addresses the limitations of pure semantic or pure keyword search: - Semantic search excels at conceptual similarity but may miss exact matches - Keyword search finds exact terms but lacks semantic understanding - Hybrid combines both for superior retrieval performance ## Capabilities ### Search Strategies - Dense vector semantic search (embeddings) - Sparse vector keyword search (BM25, TF-IDF) - Hybrid fusion with configurable weighting - Reciprocal Rank Fusion (RRF) combination ### Retrieval Configuration - Configure embedding models for dense search - Tune BM25 parameters (k1, b values) - Set retrieval limits and thresholds - Apply metadata filtering ### Ranking & Reranking - Score normalization across search types - Weighted score fusion - Cross-encoder reranking - MMR (Maximum Marginal Relevance) diversity ### Index Management - Create and update hybrid indexes - Batch indexing with progress tracking - Index optimization and maintenance - Multi-index federation ## Usage ### Basic Hybrid Search wi
- Overview
- Capabilities
- Search Strategies
- Retrieval Configuration
- Ranking & Reranking
- Index Management
- Usage
- Basic Hybrid Search with LangChain
- Reciprocal Rank Fusion
- Pinecone Hybrid Search
- Weaviate Hybrid Search
- Task Definition
- Applicable Processes
- External Dependencies
What does the rag-hybrid-search skill do?
Hybrid search combining semantic and keyword retrieval for RAG pipelines. Implement BM25 + dense vector search with fusion strategies.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill rag-hybrid-search --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.