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

1607

Output Tokens

158

Cost

$0.00

Context

Input

The user has replied: "Three days before is fine."  According to the plan for the yearly company-dinner task, what is the next action?

Expected output

Call email.search_emails with a query such as "yearly company dinner" (optionally including the current year) to locate the relevant email(s) containing the event details, and store the returned email_id(s) for the subsequent email.read_email step.

Model output

Reasoning: The user has provided the number of days they would like to receive the reminder for the yearly company dinner, which is three days before the event. The next step in the plan is to search the user's emails for information about the yearly company dinner. This will help in identifying the event date, which is crucial for adding the event to the calendar and setting the reminder. Once the email is found and the event date is extracted, we can proceed with the remaining goals such as adding the event to the calendar and checking for conflicts.

Response: Search the user's emails for information about the yearly company dinner to extract the event date and proceed with adding the event to the calendar and setting the reminder.