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

1714

Output Tokens

147

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 before the event (“Three days before is fine”) for the reminder. This completes the step of gathering user input. The next logical step is to search the user's emails to find the specific yearly company dinner event details, particularly the date. Once the email is located and read, the event date will be extracted, and the calendar tool can be used to add the event along with the reminder set to three days in advance.

Response: The next action is to search the user's emails for information about the yearly company dinner to extract the event date.