Agents

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?

The next tool is memory, to store the flights tool call result.

Reasoning: 1.  **Analyze the current state and task:** The task requires finding the top 3 cheapest flights from London to Paris for tomorrow. The `flights.search_flights` call has just returned 6 available flights.
2.  **Review the user's original request (from context):** The user wants to 'find the cheapest flights from London to Paris for tomorrow, and return the top 3 options'.
3.  **Determine the next logical step:** Since we have 6 raw results, the next step, as indicated by the planned steps in the scratchpad ('Planned next step: Filter by price and select top 3 cheapest options.'), is to use the available `flights` tool methods to narrow down these results.
4.  **Examine available `flights` methods:** The `flights` tool has methods like `filter_by_price`, `sort_by_duration`, `get_cheapest_option`, and `get_flight_details`.
5.  **Select the appropriate next call:** To satisfy the 'cheapest' and 'top 3' requirements, the most direct and effective next step is to use a filtering or sorting mechanism on the 6 results. Since the context implies the results of `search_flights` are what we work with, we need to refine this set. The user wants the *top 3 cheapest*. While there isn't an explicit 'filter_by_price' call shown in the previous step, the standard procedure after receiving search results is to filter or sort them based on the user's criteria (cheapest). The most appropriate tool method to ensure we get the cheapest options is either implicitly using `filter_by_price` (if it operates on the previous result set) or, more commonly in this flow, using a method that sorts/selects the best based on price. Given the goal is to get the top 3 cheapest, and the raw results are available, the next action should be to use the method that isolates the best ones according to price.
6.  **Consult the memory instruction (Rule 3):** "Always store meaningful results in memory using the memory tool. This means after every tool call, you store the results in memory."
7.  **Synthesize the sequence:**
    *   **Action 1 (Required by Rule 3):** Store the 6 flight results from `flights.search_flights` into memory.
    *   **Action 2 (Required by Task Goal):** Use a flights tool method to find the top 3 cheapest from that set.

8.  **Refining the immediate next call:** The prompt asks for the *next tool call*. Before filtering/sorting further, the instruction mandates storing the current result.
    *   *Next Call:* `memory.store_item` to save the 6 flights.
    *   *Why:* Rule 3 explicitly states to store the results of *every* tool call.

9.  **Considering the alternative (Tooling for the goal):** If the system assumes the 6 results are implicitly available to subsequent filtering calls without an explicit memory step first, the next step would be `flights.filter_by_price` or `flights.get_cheapest_option` (though `get_cheapest_option` might only return one). However, strict adherence to Rule 3 dictates storing the result first.

**Conclusion based on strict adherence to Rule 3:** The immediate next tool call must be to store the 6 flights returned by `flights.search_flights` in memory before proceeding to filter them.

Response: The next tool you will call is `memory.store_item`.

**Reasoning:** According to Instruction Rule 3, "Always store meaningful results in memory using the memory tool. This means after every tool call, you store the results in memory." Since the `flights.search_flights` call just returned 6 available flights, the agent must immediately store these results in memory (e.g., under a key like 'current_flights') before proceeding to the next step of filtering and selecting the top 3 cheapest options.