Meridian Line's customs-compliance agent is asked for the correct HS code and duty rate for a shipment of refrigeration units, but the retrieved tariff schedule does not clearly cover this exact product variant. Rather than fabricate a plausible-looking code, what should the agent be designed to do?
Select an answer to reveal the explanation.
Short Explanation
Customs classification is not a place for a model to plausibly extrapolate. If the source material doesn't clearly answer the question, the guardrail should make the agent say so and hand it to a human broker, not manufacture a confident-sounding number.
Full Explanation
HS-code classification carries real legal and financial consequences for a shipment, which makes it exactly the kind of output where an ungrounded guess is a governance failure, not a minor inaccuracy. The correct guardrail behavior is for the agent to recognize when retrieved context does not clearly support a classification, decline to assert one, and escalate to a human customs broker rather than fabricate an answer. Returning a best guess with a buried caveat still produces a usable-looking wrong answer that a busy broker can act on without noticing the caveat, which defeats the purpose of the guardrail. Averaging duty rates across nearby codes invents a number that has no basis in tariff law, since duty rates are not interpolated between HS codes, this manufactures a plausible-sounding but meaningless figure. Retrying the retrieval query until something comes back conflates 'a result was returned' with 'a result answers the question,' and will happily surface an irrelevant HS code just because the search was broadened enough to match something. Exam framing: an output guardrail should force refusal or human handoff when the retrieved evidence does not support a confident, specific claim, especially in a regulated domain like customs classification.