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

58s

Input Tokens

1658

Output Tokens

1166

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 provided the missing information: they want a reminder 3 days before the event. According to the plan documented in the scratch pad, the current step was waiting for user input about reminder timing. Now that this is received, the next logical step is to search the user's emails to find information about the yearly company dinner. The scratch pad explicitly lists 'Search emails to find the yearly company dinner date' as the next remaining goal. This will allow me to extract the event date and details needed to create the calendar event and set the reminder.

Response: Search the user's emails for information about the yearly company dinner using the email tool's search_emails action with an appropriate query (e.g., 'yearly company dinner').