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
29s
Input Tokens
1437
Output Tokens
502
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: Let me analyze this task step by step:

1. **Number of steps required**: The task involves 2-3 clear steps:
   - Get tomorrow's date (already completed - returned '2025-05-29')
   - Query the flights tool with the date and cities
   - Present the results to the user

2. **Tools availability**: There are dedicated, perfectly-suited tools available:
   - Calendar tool (already used successfully)
   - Flights tool (specifically designed for this exact purpose with matching parameters)

3. **Reasoning complexity**: Minimal reasoning is required:
   - Simple linear progression of steps
   - No complex decision-making needed
   - No need to combine or cross-reference multiple data sources
   - No adaptive planning or fallback strategies required

4. **Coordination needs**: Very limited:
   - Only need to pass the date from one tool to another
   - Simple parameter mapping (from_city='London', to_city='Paris', date='2025-05-29')

5. **Risk of failure**: Low:
   - Tools are available and functioning
   - Requirements are straightforward
   - No missing data or ambiguity

This task perfectly matches the 'Easy' complexity description: it has a small number of clear steps (2-3), dedicated tools exist for the exact purpose (calendar and flights tools), and minimal reasoning is needed.

Response: **Easy**

This task is classified as Easy complexity because:
- It requires only 2-3 straightforward steps (get date → query flights → present results)
- Dedicated, purpose-built tools are available that exactly match the requirements (calendar tool and flights tool)
- Minimal reasoning is needed - it's a simple linear progression without complex decision-making
- The task matches the example given for Easy complexity: "find tomorrow's date and query flights"
- No adaptive planning, fallback strategies, or complex data coordination is required
- The agent has already successfully completed the first step (getting tomorrow's date), demonstrating the straightforward nature of the task