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Rag knowledge base

Skill Drvivek34/Skill-Bazaar/ai-ml/rag-knowledge-base

Use when building, indexing, or querying vector databases for Retrieval-Augmented Generation (RAG).From its SKILL.md

Install
npx -y skills add Drvivek34/Skill-Bazaar --skill rag-knowledge-base

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

0.6 KB, 98 tokens by cl100k_base, as published. Nobody here has run it

Semantic Search & RAG Instructions

  1. Load document strings and clean HTML/markdown syntax.
  2. Chunk text using recursive character splitting (target chunk size: 500, overlap: 50).
  3. Compute embeddings using model API.
  4. Insert chunks and embeddings into local vector store (e.g. Chroma, FAISS).
  5. For queries, embed query string and retrieve top 3 nearest chunks.
  6. Format prompt template: Context + Query -> Answer.

What ships with it: 1 file

577 B alongside SKILL.md

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.