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

1m 3s

Input Tokens

1496

Output Tokens

590

Cost

$0.01

Context

Input

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?

Expected output

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

Model output

Reasoning: According to the provided instructions, Rule 3 states: 'Always store meaningful results in memory using the memory tool. This means after every tool call, you store the results in memory.' Since the previous action was a tool call to 'flights.search_flights' which returned 6 available flights, the immediate next step must be to store these results using 'memory.store_item' before proceeding to filter them by price.

Response: The next tool I will call is `memory.store_item`. I will do this because Rule 3 of my instructions explicitly requires me to store the results in memory immediately after every tool call. I need to store the 6 flights returned by `flights.search_flights` before moving on to filter and sort them.