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

21s

Input Tokens

2588

Output Tokens

213

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: 1. The user has now specified they want the reminder set **three days before** the yearly company dinner, resolving the pending input request.
   2. The next step in the plan (per scratch_pad) is to **search emails** for details about the event, specifically the date.
   3. The `email.search_emails` tool will be used with the query **"yearly company dinner"** to locate relevant emails.
   4. After retrieving results, the agent will read the most relevant email to extract the event date, then proceed to calendar updates.
   5. This aligns with the remaining goals: search emails → extract date → add to calendar → set reminder (3 days prior).

Response: {"tool_use": {"tool_name": "email", "action": "search_emails", "parameters": {"query": "yearly company dinner"}}}