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.

Input Tokens

Output Tokens

Duration

Cost

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 me analyze the current situation and determine the next action:

1. Current Status:
- User has responded with "Three days before is fine" regarding the reminder setting
- From the scratch pad, we were waiting for this input to proceed
- The next steps in our plan involve searching emails for event details

2. Progress Check:
- Step 1 (Get reminder preference) ✓ COMPLETED
- Step 2 (Search emails) → NEXT ACTION
- Remaining steps are clearly outlined in scratch pad

3. Next Action Analysis:
- Now that we have the reminder preference (3 days), we need to find the actual event date
- According to the tools available, we should use the email search tool
- We need to search for emails containing information about the yearly company dinner

Response: The next action is to use the email.search_emails tool to search for emails containing information about the yearly company dinner. The search should be executed with appropriate keywords to find the most recent and relevant email about the event.