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

28s

Input Tokens

1429

Output Tokens

449

Cost

$0.01

Context

Input

What is the complexity of this task?

Task complexity refers to how challenging a task is for the agent to complete, based on the number of steps required, the need for reasoning or coordination, and the availability of tools.

Examples:
- Easy: A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights).
- Medium: Several steps; requires combining many outputs from multiple tools (more than 4); moderate reasoning (e.g., summarize document changes across multiple files and generate a review).
- Complex: Many steps; adaptive planning; potential missing data or tool failures; fallback strategies required (e.g., plan a multi-leg trip with hotel, flight, visa checks, and dynamic adjustments).

Please select the appropriate complexity level for this task and explain why.

Expected output

This task is **easy**. It only requires determining tomorrow’s date and querying available flights — both of which have dedicated, reliable tools. There’s minimal reasoning

Model output

Reasoning: Based on the provided task complexity guidelines, this task falls under the 'Easy' category. The user request requires a very small number of clear steps: finding tomorrow's date and then using that date to query flights. Both steps have dedicated, readily available tools ('calendar' and 'flights'). The reasoning required is minimal, as it only involves passing the output of the calendar tool (the date '2025-05-29') as an input parameter to the flights tool along with the explicitly provided departure and arrival cities ('London' and 'Paris'). There is no need for adaptive planning, handling missing data, or complex tool coordination.

Response: Easy