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

1838

Output Tokens

180

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: Let's analyze the current situation:
1. We have received the user's response about reminder preference: 'Three days before is fine'
2. Looking at the scratch pad, we have completed the first step of getting the reminder preference
3. According to our plan, the next action is to search for emails about the yearly company dinner
4. We have the email tool available with search_emails action that we can use
5. We should use relevant keywords to find the email containing dinner information

Response: The next action is to search for emails containing information about the yearly company dinner using the email tool's search_emails action. We should use keywords like 'yearly company dinner' to find relevant emails that contain the event details.