Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, or context augmentation.
7.0
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0
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AI & LLM
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Excellent RAG architecture skill with comprehensive coverage of vector databases, embeddings, chunking, and retrieval optimization. The description clearly conveys when to invoke this skill for RAG-related tasks. Structure is exemplary with a clean overview in SKILL.md and detailed references externalized. Task knowledge is outstanding with actionable workflows, constraints, and evaluation frameworks. The skill addresses a complex, token-intensive domain (RAG system design) that would be costly for a CLI agent to handle from scratch. Minor improvement possible in explicit CLI invocation examples, but overall this is a production-ready, high-value skill.
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