Individual skill
rag-eval
Use when the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or generation.
skills/eval_pipeline/05-rag-eval/SKILL.md
Source commit 6416629995e5309cfce3b02ae30ae585797ec398
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- Last checked
- Nov 4, 2026
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- Repository last updated
- Nov 7, 2026
- License
- Apache-2.0
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- alignment Repository topic
- reward Repository topic
- reward-model Repository topic
- rlhf Repository topic
- agent Repository topic
- evaluation Repository topic
- grader Repository topic
- llm Repository topic
- agent-skills Repository topic
- ai-agent Repository topic
- engineering Derived category
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# RAG Eval
Evaluate RAG systems by diagnosing retrieval and generation separately. A single
"RAG accuracy" number hides whether the problem is finding the right documents or
using them correctly. This skill separates them so you know what to fix.
## When to Activate
- User has a RAG pipeline (retriever + generator) with traces
- User wants to know if their RAG system hallucinates
- User is optimizing chunking strategy and needs before/after comparison
- User wants to build a RAG evaluation dataset
## Checklist