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Found 5 Skills
Implement hybrid search combining dense vectors and sparse retrieval for optimal RAG results. Use this skill when vector search alone isn't providing accurate results. Activate when: hybrid search, BM25, keyword search, sparse retrieval, dense retrieval, reranking, ensemble retrieval.
Implement GraphRAG patterns combining knowledge graphs with retrieval for complex reasoning. Use this skill when building RAG over interconnected data or needing relationship-aware retrieval. Activate when: GraphRAG, knowledge graph, graph retrieval, entity relationships, Neo4j RAG, graph database, connected data.
Use when reranking search candidates is needed with Alibaba Cloud Model Studio rerank models, including hybrid retrieval, top-k refinement, and multilingual relevance sorting.
Complete RAG and search engineering skill. Covers chunking strategies, hybrid retrieval (BM25 + vector), cross-encoder reranking, query rewriting, ranking pipelines, nDCG/MRR evaluation, and production search systems. Modern patterns for retrieval-augmented generation and semantic search.
Retrieval-Augmented Generation - chunking strategies, embedding, vector search, hybrid retrieval, reranking, query transformation. Use when building RAG pipelines, knowledge bases, or context-augmented applications.