Ais correct — improving sentiment detection in agents begins with awell-structured promptthat includesexplicit task contextand clearly defined expectations, especially when detecting nuanced emotions likefrustration, urgency, or sarcasm.
According to UiPath’sPrompt Engineering Framework, a strong prompt should include:
Atask objective: e.g., “Detect sentiment and urgency in user messages”
Definitions or rules: e.g., “Urgency includes time sensitivity, threats of cancellation, or escalated language”
Output constraints: e.g., “Classify as Positive, Neutral, Negative, and Urgent (Yes/No)”
This helps the LLM:
Anchor its reasoning to what urgency means inyour business context
Avoid hallucinations or misinterpretation of neutral phrases
Generateconsistently labeled outputsfor downstream automation or review
Option B lacks structure — emotional tone ≠ clarity.
C is risky — too much freedom leads to inconsistent results.
D separates tasks that arebest handled together, especially since emotion often influences how a complaint should be triaged.
Byembedding sentiment-specific logic into the prompt, UiPath agents become better equipped todetect critical issues in real time, enabling faster response and better customer experience.
