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
23s
Input Tokens
1344
Output Tokens
594
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: 
    1. **Understanding the Problem**:
       - The task involves retrieving the cheapest flights from London to Paris for tomorrow (2025-05-29).
       - The `flights.search_flights` tool failed twice due to a timeout error.
       - According to the instructions, the maximum number of retries for a tool call is **3**.

    2. **Next Action Decision**:
       - Since the tool has failed twice, and the maximum allowed retries is 3, I will attempt **one final retry** of `flights.search_flights` with the same parameters:
         - `from_city`: 'London'
         - `to_city`: 'Paris'
         - `date`: '2025-05-29'
         - (Optional: `max_results` if needed for efficiency, though not strictly required for the task.)

    3. **Contingency Plan**:
       - If this third attempt also fails due to timeout or another error:
         - Log the failure in memory using `memory.store_item` with a key like `flight_search_failure_2025-05-29`.
         - Notify the user that the flight search could not be completed due to repeated timeouts, and suggest:
           - Trying again later.
           - Checking their internet connection (if applicable).
           - Contacting support if the issue persists.

    4. **Post-Success Plan**:
       - If the third attempt succeeds:
         - Proceed to filter the results by price (using `flights.filter_by_price` or `flights.get_cheapest_option`).
         - Select the top 3 cheapest options.
         - Store the results in memory under the key `top_flights` (as planned).
         - Present a summary to the user.

    5. **Optimization Note**:
       - No redundant calls will be made. The retry is justified as it is the final allowed attempt.
       - If the third attempt fails, no further retries will be made to avoid violating the instructions.
    

Response: 
    **Action**: Retry `flights.search_flights` one final time (3rd attempt) with parameters:
    ```json
    {
      "from_city": "London",
      "to_city": "Paris",
      "date": "2025-05-29"
    }
    ```
    **Post-Action Plan**:
    - On success: Filter for top 3 cheapest flights, store in memory (`top_flights`), and summarize for the user.
    - On failure: Log the error in memory, notify the user, and suggest next steps (retry later or contact support).