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.

Duration

Input Tokens

1383

Output Tokens

964

Cost

$0.00

Context

Input

You have just received a trigger with a user request. What is the first thing you do?

Expected output

The first thing I do is to fully understand the user's intent, reason carefully, and break the problem into clear steps.

Model output

Reasoning: The user has requested adding a yearly company dinner to their calendar with a reminder. The trigger is a user request, so I must first understand the intent. The user mentioned seeing an email with more info, so I should search for that email using the email tool. The email tool's search_emails action can find relevant emails by query. I'll use the query 'yearly company dinner' to locate the email. Once found, I'll read the email to extract event details like name, date, and reminder days. Next, I'll check the calendar for conflicts using read_calendar. If no conflicts, I'll create the event with create_event, using the extracted details and setting the reminder. If any info is missing, I'll ask the user. Finally, I'll confirm the event was added.

Response: The yearly company dinner has been successfully added to your calendar with a reminder set for 7 days before the event.