Build RAG systems - embeddings, vector stores, chunking, and retrieval optimization
4.9
Rating
0
Installs
AI & LLM
Category
The skill provides a solid foundation for RAG system implementation with clear parameter schemas, practical code examples, and useful reference tables for chunking strategies and embedding costs. The description adequately covers core RAG capabilities, and the task knowledge includes concrete implementation steps with LangChain. Structure is clean and well-organized with appropriate sections. However, novelty is moderate—while RAG systems add value, much of this guidance (chunking strategies, embedding model selection, vector DB setup) could be accomplished by a capable CLI agent with sufficient context. The skill is most valuable for standardizing best practices and providing quick-reference tables rather than solving uniquely complex problems that would otherwise require many tokens.
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