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rag-implementation

6.3

by davila7

72Favorites
140Upvotes
0Downvotes

Retrieval-Augmented Generation patterns including chunking, embeddings, vector stores, and retrieval optimization Use when: rag, retrieval augmented, vector search, embeddings, semantic search.

RAG

6.3

Rating

0

Installs

AI & LLM

Category

Quick Review

The skill provides a solid conceptual overview of RAG implementation with clear principles, capabilities, and anti-patterns. However, it lacks concrete implementation details, code examples, and step-by-step guidance needed to actually build a RAG system. The SKILL.md appears incomplete (text cuts off mid-sentence in principles). While the structure is organized with good sections for patterns and sharp edges, the task knowledge is insufficient—a CLI agent would know *what* to avoid but not *how* to implement chunking strategies, embeddings, or vector stores. The novelty is moderate as RAG is complex but the skill doesn't provide enough differentiation from standard documentation. To improve: add concrete code snippets, chunking algorithms, vector store setup examples, and retrieval pipeline implementations.

LLM Signals

Description coverage6
Task knowledge4
Structure6
Novelty5

GitHub Signals

18,239
1,655
133
73
Last commit 0 days ago

Publisher

davila7

davila7

Skill Author

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Publisher

davila7 avatar
davila7

Skill Author

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