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

1759

Output Tokens

588

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 required information regarding the reminder duration (three days). According to the previously established plan and the current status in the scratch pad, the next logical step is to find the details of the 'yearly company dinner', specifically the date, by searching the user's emails as mentioned in the trajectory.

Response: The next action is to search the user's emails for information regarding the yearly company dinner to identify the date. I will use the `email` tool with the `search_emails` action, using a query like 'yearly company dinner'.