Detecting when an agent should stop and ask a question is crucial for effective interaction and relies on several mechanisms. Primarily, an agent monitors its confidence levels in understanding user intent or generating a response; if these fall below a predefined threshold, it signals a need for clarification. Another key indicator is the presence of ambiguity, where multiple interpretations of user input are equally plausible, necessitating a question to resolve the uncertainty. Agents also identify missing essential information required to complete a task or provide an accurate answer, prompting them to inquire for details. Furthermore, if the current conversation significantly deviates from expected patterns or known intents, it suggests a potential misunderstanding or a need to confirm the user's new direction. Implementing these checks ensures the agent remains helpful and avoids making incorrect assumptions, thereby enhancing user experience. More details: https://btnews.or.kr/shop/bannerhit.php?bn_id=5&url=https://infoguide.com.ua