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

11s

Input Tokens

1239

Output Tokens

330

Cost

$0.00

Context

Input

Of the available tools. Which ones will you need to use to successfully complete the task?

Expected output

All tools will need to be used: calendar, flights,memory

Model output

Reasoning: To find the cheapest flights from London to Paris for tomorrow and return the top 3 options, I need to first determine tomorrow's date using the calendar tool. Then, I will use the flights tool to search for flights based on the cities and date. Finally, I will store the results in memory.

1. **Step 1:** Use the calendar tool to get tomorrow's date.
   - Method: `get_tomorrow_date` from the calendar tool.

2. **Step 2:** Use the flights tool to search for flights from London to Paris on tomorrow's date and get the top 3 cheapest options.
   - Method: `search_flights` with parameters `from_city`: "London", `to_city`: "Paris", `date`: retrieved date, `max_results`: 3.

3. **Step 3:** Store the flight results in memory using the memory tool for future reference.
   - Method: `store_item` with key `flights_London_Paris` and value as the JSON string of the flight results.

These steps ensure that the task is completed efficiently and the results are stored for future use.

Response: To successfully complete the task, the following tools will be used:
1. **Calendar Tool** to retrieve tomorrow's date.
2. **Flights Tool** to search for and filter flights based on the user's request.
3. **Memory Tool** to store the flight results for future reference.