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

12s

Input Tokens

1317

Output Tokens

818

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 instructions state that the **max retries for a tool call = 3**. Since 
`flights.search_flights` has only failed twice, one final retry is permitted under Rule 2. 
Before proceeding, confirm the tool status (which the context lists as *available*) and that 
parameters (from_city='London', to_city='Paris', date='2025-05-29') are correct. If the third 
attempt succeeds, proceed to filter and store as planned. If it fails again, follow Rule 2 to 
log the error and pivot to alternative strategies (e.g., checking for API status via system 
tools or alerting the user).

Response: Retry `flights.search_flights` (3rd attempt) with identical parameters 
(from_city='London', to_city='Paris', date='2025-05-29'). 

**Action:**
```
flights.search_flights(from_city="London", to_city="Paris", date="2025-05-29")
```