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.

Input Tokens

Output Tokens

Duration

Cost

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: The task is to find the cheapest flights from London to Paris for tomorrow and return the top 3 options. To achieve this, the following steps are necessary:

1. Determine the date for tomorrow. Since the flight is for tomorrow, I need to use the 'calendar' tool with the method 'get_tomorrow_date' to get the correct date in the required format for the flight search.
2. Once I have the date, I will use the 'flights' tool with the method 'search_flights' to find flights from London to Paris for that date. The parameters required are 'from_city', 'to_city', and 'date', and I can set 'max_results' to 3 to limit the output.
3. After retrieving the flight data, I will store the results in memory using the 'memory' tool's 'store_item' method with a clear key such as 'top_3_cheapest_flights_London_to_Paris'.

Therefore, the tools needed are:
- 'calendar' to get tomorrow's date
- 'flights' to search for the flights
- 'memory' to store the results

These tools will be used in sequence as per the chaining rule, and I will avoid redundant calls by storing and reusing data where necessary.

Response: To successfully complete the task, I will need to use the following tools: 
1. 'calendar' tool (to get tomorrow's date using 'get_tomorrow_date')
2. 'flights' tool (to search for flights using 'search_flights' with parameters: from_city='London', to_city='Paris', date=tomorrow, max_results=3)
3. 'memory' tool (to store the resulting flight options using 'store_item')