Opper

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.

Input Tokens

Output Tokens

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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Reasoning: The user has rescinded the request for a reminder and only wants the dinner placed on the calendar. Therefore:
1. Discard the branch of the plan that gathered reminder-timing input and the later step that would create the reminder.
2. Update the scratch_pad/remaining-goals list:
   • Search emails for the yearly company-dinner details (date, time, location).
   • Read the relevant email to confirm the exact event date/time.
   • Add the event to the calendar (no reminder field required).
   • Check for calendar conflicts and notify the user if any exist.
3. No further user input is needed at the moment, so immediately proceed with email→calendar workflow.
4. When done, confirm to the user that the dinner is on the calendar (and mention any conflicts, if found).

Response: Understood—I'll skip the reminder and just make sure the company dinner is on your calendar. Let me locate the event details now and add it for you.