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

Input Tokens

1372

Output Tokens

571

Cost

$0.00

Context

Input

You attempted to call flights.search_flights, but the tool failed twice due to a timeout error. What is your next action according to the model instructions?

Expected output

Retry the flights.search_flights call one more time (maximum retries = 3), and if it fails again, log the failure and proceed with fallback steps or inform the user.

Model output

Reasoning: The task is to determine the next action after two timeout failures on flights.search_flights. According to instructions, max retries for a tool call = 3. Two failures have occurred, so one retry remains. The tool call parameters should be the same: from_city='London', to_city='Paris', date='2025-05-29'. The failures should be logged and explained. After a successful call, results will be stored in memory. The next action is thus the third attempt of flights.search_flights.

Response: Retry flights.search_flights with parameters from_city='London', to_city='Paris', date='2025-05-29' as the third and final attempt, logging the previous two timeout failures. If successful, store results in memory.