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

764

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 clarified that they want the reminder set three days before the event. According to the established plan, the next step is to search the user's emails to locate the details of the yearly company dinner, as mentioned in the initial trigger. The agent must use the email tool's search function with a targeted query ('yearly company dinner') to retrieve relevant emails. This is critical to extract the event date and proceed with calendar integration.

Response: Now that the user has specified three days for the reminder, proceed by using the 'search_emails' action from the email tool to locate the event details. The query should be 'yearly company dinner' to identify the email containing the event date. After retrieving the email(s), use 'read_email' to extract the exact event details, including the date, ensuring the information is accurate before adding it to the calendar.