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
4s
Input Tokens
1273
Output Tokens
273
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: The task is to determine the complexity of a given task based on predefined criteria: number of steps, need for reasoning, tool usage, and potential for adaptive planning or fallbacks. The current task involves assessing a scenario where the agent needs to find flights from London to Paris for tomorrow. From the context, we observe that:

1. The user request is straightforward: find available flights with clear parameters (origin, destination, date).
2. The necessary tools are available: calendar (to get tomorrow's date) and flights (to query flight availability).
3. The number of steps is small: (a) get tomorrow's date, (b) use that date to query flights, (c) return results.
4. There is minimal reasoning required—just interpreting the date and formatting it correctly for the flight tool.
5. All required tools are available and functioning, and no fallback strategies are needed.
6. The trajectory shows that this task is already in progress and is proceeding linearly.

This aligns with the definition of an 'Easy' task: a small number of clear steps, dedicated tools exist, and minimal reasoning is needed.

Therefore, the task complexity is 'Easy'.

Response: Easy