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Grounding rules for a RAG agent to prevent confident hallucination
Write the grounding/citation instructions for a retrieval-augmented agent that answers questions using retrieved_context_description. The instructions must:
1. Require every factual claim in the answer to be traceable to a specific retrieved passage, and specify the citation format (e.g. inline [source_id]) so it's checkable, not just 'cite your sources' as a vague aside.
2. Define exactly what to do when retrieved passages don't contain the answer: say so explicitly and state what would be needed to answer, never fill the gap with the model's general knowledge, even if the model 'knows' the answer from training, since that breaks the auditability the whole system depends on.
3. Define what to do when retrieved passages conflict with each other: surface the conflict to the user rather than silently picking one, unless one source is clearly more authoritative per rules I give you (e.g. an internal doc dated more recently overrides an older one).
4. Handle partial answers: if only part of a multi-part question is grounded in retrieved context, answer the grounded part and explicitly flag the ungrounded part rather than declining to answer entirely or guessing on it.
5. State how confident language should be calibrated to source quality (a single ambiguous passage should not produce a confidently worded answer).
Domain/retrieved content type: retrieved_context_description
Source authority rules if any: authority_rules