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

12s

Input Tokens

3032

Output Tokens

310

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: 1. I analyzed the task and understood that the user needs me to find the cheapest flights from London to Paris for tomorrow and return the top 3 options.
2. I planned my approach by deciding to use the 'calendar', 'flights', and 'memory' tools.
3. I executed the plan by first getting the current date using the 'calendar' tool, adding one day to it, and storing it in memory.
4. I used the 'flights' tool to search for flights with the updated date, filtered the results by price, sorted them by duration, and retrieved the cheapest three options.
5. I stored these options in memory using the 'memory' tool with clear keys.
6. I will return the top 3 options to the user.

Response: To successfully complete the task, I will need to use the 'flights' tool to search for flights from London to Paris for tomorrow. I will first store the current date using the 'calendar' tool and add one day to it, then I will use the 'flights' tool to search for flights with the updated date. I will filter the results by price, sort them by duration, and retrieve the cheapest three options. After that, I will store these options in memory using the 'memory' tool with clear keys. Finally, I will return the top 3 options.