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

10s

Input Tokens

1249

Output Tokens

547

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: 1. The user's goal is to find flights from London to Paris for tomorrow. 2. Step 1 (determining tomorrow's date via calendar tool) was completed successfully, yielding '2025-05-29'. 3. Current cycle (3) requires using the 'flights' tool with parameters: from_city='London', to_city='Paris', date='2025-05-29'. 4. All required parameters are available and match the tool's schema. 5. Progress is at Step 2/4, with remaining steps being flight search and result compilation. 6. No errors or blockers detected in trajectory. 7. Next action is clearly defined and aligns with the plan.

Response: On track. The calendar tool successfully provided tomorrow's date (2025-05-29). Next step is to execute the 'flights' tool with London, Paris, and 2025-05-29. All parameters are validated and tools are available. Proceeding as planned.