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
24s
Input Tokens
1533
Output Tokens
601
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: Based on the model instructions, I need to analyze the situation systematically. The flights.search_flights tool has failed twice due to timeout errors. According to rule #2, the maximum retries for a tool call is 3, so I have one more attempt available. However, I should also consider if there's an alternative approach.

Let me review the current situation:
1. I successfully got tomorrow's date (2025-05-29) from the calendar tool
2. The flights.search_flights tool timed out twice
3. I'm on step 2 of 4 in my plan
4. I still need to find flights from London to Paris for tomorrow

According to the instructions:
- Rule #2 states max retries = 3, and I should log and explain failures
- Rule #4 says to avoid redundant tool calls
- Rule #5 emphasizes working in cycles: analyze, plan, act, reflect, decide next action

Since I've only tried twice and the limit is 3, I should:
1. Try one more time with the flights.search_flights tool
2. If it fails again, I need to log the failure and explain to the user that the flight search service is currently unavailable
3. Consider storing the failure information in memory for tracking purposes

Response: According to the model instructions, since flights.search_flights has failed twice due to timeout errors and the maximum retries is 3 (Rule #2), my next action should be:

1. **Make a third and final attempt** to call flights.search_flights with the same parameters (from_city='London', to_city='Paris', date='2025-05-29')

2. **If it fails again**, I should:
   - Log and explain the failure to the user
   - Store the failure information in memory using memory.store_item with a key like 'flight_search_failure' 
   - Inform the user that the flight search service is currently unavailable due to persistent timeout issues
   - Suggest alternative actions (like trying again later or using a different service)

3. **If it succeeds**, I should:
   - Continue with the planned next steps (filter by price, select top 3)
   - Store the results in memory as originally planned

This approach follows Rule #2 (respecting the 3-retry limit), Rule #3 (storing meaningful results/failures in memory), and Rule #5 (working in cycles with reflection and decision-making).