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

48s

Input Tokens

1345

Output Tokens

967

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: Let me analyze the current situation and determine the next step:

1. **Current Progress**: We've completed steps 1-2: got tomorrow's date (2025-05-29) and retrieved 6 flights from London to Paris.

2. **User's Goal**: Find the CHEAPEST flights and return the TOP 3 options.

3. **Scratch Pad Plan**: The planned next step clearly states 'Filter by price and select top 3 cheapest options.'

4. **Available Methods**: The flights tool offers 'filter_by_price' and 'get_cheapest_option' methods.

5. **Per Instruction #1**: I should first understand the available methods and parameters before calling. However, since we need to process the 6 flights already returned, the logical next action is to filter/sort them by price.

6. **Best Approach**: Call `flights.filter_by_price` on the 6 returned flights to identify the cheapest options, then select the top 3.

7. **After This**: Per instruction #3, I must store meaningful results in memory using `memory.store_item` with key 'top_flights'.

The next tool call should be `flights.filter_by_price` to sort/filter the 6 flights by price so we can identify the top 3 cheapest options for the user.

Response: The next tool I will call is **flights.filter_by_price** on the 6 returned flights.

**Reasoning:**
1. The user explicitly requested the 'cheapest' flights and wants the 'top 3 options'
2. We have 6 flights available from the search_flights call
3. The scratch_pad planned next step is 'Filter by price and select top 3 cheapest options'
4. The flights tool has a `filter_by_price` method specifically designed for this purpose
5. After filtering, I will select the top 3 cheapest flights
6. Per instruction #3, I will then store these results in memory using `memory.store_item` with key 'top_flights' before presenting the summary to the user

This follows the logical chain: calendar → flights.search_flights → flights.filter_by_price → memory.store_item → present to user.