AI Agents Evaluation RAG

Groundedness Check Prompt

Verify a RAG answer is actually from its retrieved context — every claim traced to a retrieved passage, and any answer that outran its sources flagged.

Overview

RAG's whole promise is grounded answers, but a model will happily blend retrieved context with its own training and present the mix as sourced. This prompt checks groundedness specifically: it maps each part of the answer to the retrieved passage that supports it, flags claims with no supporting passage, and catches the case the system should have handled — answering confidently when the retrieved context didn't actually contain the answer.

Why This Works

  • Attributing each claim to a passage is the only real test of grounding
  • Catching confident-answer-without-context targets RAG's signature failure
  • Distinguishing 'wrong' from 'unsupported-but-right' isolates the retrieval problem

Best for

  • RAG systems and knowledge-grounded agents
  • Domains where an unsourced answer is dangerous
  • Evaluating retrieval quality and answer faithfulness together

Not for

  • Checking output against an arbitrary source — use the Hallucination Detection Prompt
  • Non-RAG generation with no retrieved context

Use cases

  • Verifying RAG answers are sourced, not invented
  • Catching answers that outran the retrieved context
  • Evaluating retrieval-augmented agents for grounding

Tip: Save time by exploring related resources and tools that integrate with this workflow.

Explore all resources