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

1340

Output Tokens

223

Cost

$0.00

Context

Input

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

Expected output

We are on track

Model output

Reasoning: Step-by-step assessment:
1. User's request: Find available flights from London to Paris for tomorrow.
2. Past trajectory: Correctly identified need for tomorrow's date → Called calendar tool → Received '2025-05-29' (valid YYYY-MM-DD format).
3. Current cycle: 3, scratch pad indicates interpreting calendar result and deciding next action.
4. Remaining goals: Use 'flights' tool with London, Paris, 2025-05-29; then compile and present results.
5. Progress: Step 2 of 4 completed (date obtained). Flights tool is available and params match exactly (from_city: 'London', to_city: 'Paris', date: '2025-05-29').
6. No issues, errors, or deviations detected. Date format confirmed correct.
Conclusion: We are precisely on track. Next logical action is to call the 'flights' tool to proceed to step 3.

Response: On track