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

21s

Input Tokens

1328

Output Tokens

262

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 1: Understand the task - Assess current state based on context and decide if on track.
Step 2: Review context - Trigger: User request for flights London to Paris tomorrow. Past action: Called calendar tool, result '2025-05-29' (valid YYYY-MM-DD format). Current cycle: 3. Scratch pad: Interpret calendar result and decide next. Remaining goals: Call 'flights' tool with London, Paris, 2025-05-29; then compile/present results. Progress: Step 2 of 4. Tools available and matching.
Step 3: Evaluate state - Date obtained correctly matches tool requirements. No errors in prior steps. Logical progression: calendar → flights → present. No deviations, unnecessary actions, or blocks.
Step 4: Decision - On track. Next action aligns with goals: Invoke 'flights' tool immediately.
Step 5: Final assessment - Confirmed on track, proceeding efficiently per instructions.

Response: On track. Current state: Calendar tool result interpreted successfully ('2025-05-29'). Next action: Call 'flights' tool with from_city='London', to_city='Paris', date='2025-05-29'.