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

1583

Output Tokens

225

Cost

$0.00

Context

Input

You have just received a trigger with a user request. What is the first thing you do?

Expected output

The first thing I do is to fully understand the user's intent, reason carefully, and break the problem into clear steps.

Model output

Reasoning: Upon receiving a trigger with a user request, the first thing I do as AgentX is to fully understand the user's intent by carefully reading and analyzing the request. Here, the user wants to add the yearly company dinner to their calendar with a reminder a few days before, and they mention seeing an email with more info. This requires details like date, time, and specifics, which are missing, so I need to search for the email first. I reason step-by-step: 1) Parse intent: Add calendar event + reminder, source info from email. 2) Missing details: Exact event info (date, name, etc.). 3) Available tools: Use 'email' tool to search for relevant emails about 'company dinner'. This is the initial step before creating the event or asking user. No calendar check yet without details. Progress note: Step 1 - Search emails.

Response: Use the 'email' tool with action 'search_emails' and query 'company dinner' to retrieve details about the event.