{"skill":{"slug":"rag-engineer","displayName":"Rag Engineer","summary":"Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LL...","tags":{"latest":"1.0.0"},"stats":{"comments":0,"downloads":36,"installsAllTime":1,"installsCurrent":1,"stars":0,"versions":1},"createdAt":1771383014118,"updatedAt":1778491570900},"latestVersion":{"version":"1.0.0","createdAt":1771383014118,"changelog":"Initial public release of rag-engineer\n\n- Introduces skill for designing and building Retrieval-Augmented Generation (RAG) systems.\n- Highlights core capabilities: vector embeddings, chunking strategies, retrieval pipelines, and hybrid search.\n- Provides actionable patterns (e.g., semantic chunking, hierarchical retrieval).\n- Lists anti-patterns and common pitfalls (“Sharp Edges”) with recommended solutions.\n- Details prerequisites and related skills for effective integration.\n- Authored by 무펭이 🐧 and released under Apache 2.0.","license":null},"metadata":null,"owner":{"handle":"mupengi-bot","userId":"s17cb0n67gxg14m41wrqex0hr183j5d2","displayName":"mupengi-bot","image":"https://avatars.githubusercontent.com/u/259087580?v=4"},"moderation":null}