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.

0
Duration
21s
Input Tokens
1280
Output Tokens
2558
Cost
$0.00
Context
Input
The flights.search_flights call has returned 6 available flights from London to Paris for tomorrow. What is the next tool you will call, and why?
Expected output
The next tool is memory, to store the flights tool call result.
Model output
Reasoning: We have 6 flights for 2025-05-29. To meet the goal of providing the cheapest options (top 3), the next step is to filter by price and limit to 3 results. This action follows the plan and will be followed by storing the results in memory.

Response: Call flights.filter_by_price with max_results=3 for date 2025-05-29, from London to Paris, to retrieve the three cheapest options from the 6 results.