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.

100
Duration
15s
Input Tokens
1559
Output Tokens
209
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 now responded, specifying that they would like the reminder to be set three days before the event. According to the plan detailed in the scratch_pad and the remaining goals, the current step after receiving the user's preference is to look up the actual date and details of the yearly company dinner. The context states that I should do this by searching the user's emails for relevant information about the event. Once the details are found, I can proceed with adding the event to the calendar and configuring a reminder according to the user's instructions. Therefore, the next concrete action is to use the 'email' tool to search for emails related to the company dinner (perhaps with keywords like 'yearly company dinner') in order to extract the date and any necessary information.

Response: The next action is to search the user's emails for information about the yearly company dinner (e.g., by searching for 'yearly company dinner') in order to find the event date and details.