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

1805

Output Tokens

691

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 necessary input, specifying that a reminder three days before the event is acceptable. This completes the current phase of gathering user preferences.

Following the established plan (scratch_pad goals), the next step is to find the details of the 'yearly company dinner', which the user indicated are available in an email. I must now use the `email` tool to search for the relevant email containing the event date and details.

Therefore, the next action is to call the `search_emails` function with a query targeting the event.

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