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.

100
Duration
8s
Input Tokens
1245
Output Tokens
657
Cost
$0.00
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: I need to classify the complexity of the task 'find information about available flights from London to Paris for tomorrow' based on the description and example provided in the task. Looking at the context, I can see the actual trajectory that was followed: 1) Determine tomorrow's date using the calendar tool, 2) Use the flights tool to search for available flights, and 3) Compile and present results to the user. This task involves only 3 clear steps with dedicated tools readily available (calendar and flights). The reasoning required is minimal - just understanding that we need a date before searching for flights. There's no need for combining multiple tool outputs beyond passing the date to the flights tool, and no adaptive planning or fallback strategies are required. Based on the examples provided, this clearly falls into the 'Easy' complexity category.

Response: Easy