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

Input Tokens

1224

Output Tokens

338

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: As AgentX, I will first identify the tools needed to complete the task. The task is to find the cheapest flights from London to Paris for tomorrow and return the top 3 options.

1. **Analyze**: I need to use the 'flights' tool to search, filter, and retrieve flight information.
2. **Plan**: I will use the 'get_tomorrow_date' method of the 'calendar' tool to get the specific date for tomorrow.
3. **Act**: I will call the 'search_flights' method of the 'flights' tool with the parameters 'from_city' as 'London', 'to_city' as 'Paris', and 'date' as the tomorrow's date from the 'calendar' tool.
4. **Reflect**: After getting the flight options, I will filter the cheapest options and select the top 3.
5. **Decide next action**: Store the top 3 cheapest flight options in the 'memory' tool using the 'store_item' method for future use.

Following these steps, I will be able to complete the task systematically and ensure that I follow the instructions and rules provided.

Response: To find the cheapest flights from London to Paris for tomorrow and return the top 3 options, I will use the 'flights' tool with the 'calendar' tool to get the specific date for tomorrow, filter the cheapest options, and select the top 3.