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.

100
Duration
1m 24s
Input Tokens
1264
Output Tokens
484
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: Let me analyze the current state step by step:

1. **Original request**: User wants flight information from London to Paris for tomorrow

2. **Progress so far**:
   - Cycle 1: User made the request
   - Cycle 2: Calendar tool was called to determine tomorrow's date
   - Current (Cycle 3): Calendar tool returned '2025-05-29' as tomorrow's date

3. **Current position**: We're at step 2 of 4 according to the scratch pad. We have successfully obtained tomorrow's date (2025-05-29) from the calendar tool.

4. **Next required action**: According to the scratch pad, the next goal is to use the 'flights' tool with:
   - from_city: London
   - to_city: Paris  
   - date: 2025-05-29

5. **Assessment**: We are ON TRACK because:
   - We've successfully completed the first necessary step (getting tomorrow's date)
   - We have the correct date format (YYYY-MM-DD) that matches the flights tool requirements
   - We have a clear next action planned (calling the flights tool)
   - We're following a logical sequence toward fulfilling the user's request
   - No errors or blockers have been encountered

Response: Yes, we are ON TRACK. The agent has successfully:
1. Understood the user's request for flight information from London to Paris for tomorrow
2. Properly called the calendar tool to determine tomorrow's date (2025-05-29)
3. Received and interpreted the calendar tool result correctly
4. Has a clear plan for the next action: calling the flights tool with the correct parameters (from_city: London, to_city: Paris, date: 2025-05-29)

The trajectory shows logical progression with no errors or deviations from the goal. The agent is at step 2 of 4 and ready to proceed with the flight search.