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

Asses the current state and decide if we are on track or not

Expected output

We are on track

Model output

Reasoning: 1) Verify trigger and intent: The trigger_type is user_request asking for available flights London->Paris for tomorrow. This matches the remaining goals.
2) Validate previous tool output: Calendar tool returned '2025-05-29'. Confirmed this is in YYYY-MM-DD format required by the flights tool. Date is valid and ready to use.
3) Check tool availability and requirements: The 'flights' tool is available and requires from_city, to_city, date. We have all three pieces: from_city='London', to_city='Paris', date='2025-05-29'.
4) Progress evaluation: Progress shows Step 2 of 4; the next logical step is to call the flights tool to retrieve flight options. No blocking issues detected in the context.
5) Potential caveats: 'London' can map to multiple airports (LHR, LGW, STN, LTN, LCY). If the user has a preferred airport, cabin class, number of passengers, or time window, we should ask. Otherwise proceed with a broad search for all London airports or default to city-level search.
6) Conclusion: Given the available data and tools, we are on track to complete the task. The most direct next action is to call the flights tool with the confirmed date and cities, store results in working memory, then compile and present the findings to the user.

Response: Assessment: On track.
Next action (recommended): Call the 'flights' tool with parameters {from_city: "London", to_city: "Paris", date: "2025-05-29"}, store the flight search results in working memory, then summarize and present available options to the user. Note: if the user has airport, time, or passenger preferences, ask a quick clarifying question before searching; otherwise proceed with a city-level search covering all London airports.