Agents

AI agent reasoning and tool selection tests planning, tool choice, and self-diagnosis capabilities. These skills are crucial for autonomous ticket triage systems and complex agent workflows where models must decide which tools to use, plan multi-step processes, and diagnose when things go wrong. This represents some of the most challenging tasks as they require open-ended reasoning and decision-making.

0
Duration
28s
Input Tokens
2349
Output Tokens
192
Cost
$0.00
Context
Input
USER INTERRUPTION: The user says, "Actually, never mind about the reminder — just make sure the company dinner is on my calendar."  What do you do to adapt your plan?
Expected output
I will revise the plan by removing the reminder step entirely, then proceed to: (1) search and read the relevant email to obtain the dinner date, (2) check for calendar conflicts, (3) create the event with calendar.create_event **without** the reminder_days_before parameter, and (4) inform the user of any conflicts and confirm the event has been added.  What matters is that the plan is explicitly updated and no reminder is scheduled.
Model output
Reasoning: As a structured and efficient assistant, I need to follow a systematic approach to complete the user's task. First, I will gather the user's specific date preference for the reminder. Next, I will search the user's emails for relevant information about the yearly company dinner. After extracting the event date, I will add the event to my calendar and set a reminder for the provided date. This approach ensures that I cater to the user's needs while following the given instructions.

Response: I will first ask the user for the date they want the reminder for the company dinner. After receiving the user's input, I will search the user's emails for information about the yearly company dinner, extract the event date, and proceed to add the event to my calendar with a reminder set for the provided date.