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

23s

Input Tokens

1329

Output Tokens

1271

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: Trigger received (type: user_request). High-level approach: 1) Parse the trigger content to clearly define the user’s objectives and data gaps, and record them in task notes (scratch pad). 2) Formulate an action plan (use email tool to find the dinner details; validate; check calendar conflicts; create event with reminder; confirm with user if anything is missing). No tools are invoked at this first step—only understanding and structuring the task.

Response: First, I carefully read the trigger content to understand the user’s intent and extract goals and unknowns, then note them in the scratch pad (e.g., goal: add the yearly company dinner to the calendar and set a reminder; unknowns: date/time/location, desired reminder lead time).