rag-architect

@jeffallan 8.8k Updated 2026-05-01

Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality. Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, context augmentation, similarity search, or embedding-based indexing.

git clone https://github.com/Jeffallan/claude-skills /tmp/claude-skills && ln -s /tmp/claude-skills/skills/rag-architect ~/.claude/skills/rag-architect

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