AI Agents Evaluation Hallucination

Hallucination Detection Prompt

Catch the confident invention — check an AI output's claims against its source and flag every statement that isn't supported, with the unsupported span quoted.

Overview

The dangerous AI failure isn't being wrong loudly — it's being wrong confidently, with an invented fact that reads exactly like a real one. This prompt audits an output against its source material: it extracts the checkable claims, marks each as supported, contradicted, or unsupported, and quotes the exact span that isn't backed by the source — so hallucinations are caught before a user trusts them.

Why This Works

  • Classifying every claim catches the plausible invention, not just obvious errors
  • Quoting the unsupported span makes the finding actionable, not vague
  • Judging only against the source is what separates hallucination from 'sounds right'

Best for

  • RAG systems and summarizers grounded in source text
  • High-stakes outputs where a wrong fact is costly
  • Evaluation pipelines needing a hallucination check

Not for

  • Open-ended generation with no source to check against
  • Grounded-answer verification specifically — use the Groundedness Check Prompt

Use cases

  • Checking a RAG or summary output against its source
  • Catching invented facts before they reach a user
  • Auditing agent answers for unsupported claims

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

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