ClarificationAgent

To clarify ambiguous user questions, a diagnostic analysis restates the query, identifies logical gaps, and surfaces hidden assumptions to produce a structured clarification report before the final answer is generated.

Question diagnosis in prompt engineering exposes cognitive biases and unspoken premises within a user query. This process transforms vague inputs into precise, answer-ready refined questions to guide subsequent interactions.

Detecting hidden assumptions and cognitive biases in support conversations requires systematically evaluating the query's logical structure. The output includes identified biases, unspoken premises, and a refined question for accuracy.

Yes, you can use question analysis to improve research question quality by systematically exposing logical gaps and ambiguities. It generates a diagnostic report with a refined question and a diagnosis confidence score.

The best way to structure question analysis for product inquiries is outputting a diagnostic report containing the restated question, identified ambiguities, hidden assumptions, cognitive biases, and a refined question.