rag-implementation
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
74
2.12x
Quality
71%
Does it follow best practices?
Impact
70%
2.12xAverage score across 3 eval scenarios
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Passed
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tessl review fix ./tests/ext_conformance/artifacts/agents-wshobson/llm-application-dev/skills/rag-implementation/SKILL.mdThe canonical home for this skill is rag-implementation in wshobson/agents
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