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rag-pro

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RAG guidance — chunking, retrieval tuning, hybrid search, reranking, citations, evaluation, and production RAG.

skills/rag-pro/SKILL.md

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## Overview

RAG (Retrieval-Augmented Generation) grounds LLMs in your data: retrieve relevant chunks, stuff them into the prompt, generate answers with citations. It's the highest-ROI LLM pattern — and the one where "it works in the demo" most often collapses in production. The unglamorous truth: chunking, retrieval quality, and evaluation matter far more than model choice.

This skill covers production RAG end to end: ingestion and chunking, retrieval tuning (hybrid, reranking, filters), synthesis with citations, evaluation, and the operational concerns of a live system.

## When to use

- Building question-answering over documents.
- Improving RAG answer quality.
- Tuning chunking and retrieval.
- Adding citations to generated answers.
- Evaluating RAG systems.
- Operating RAG in production (updates, access control, monitoring).
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