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

1263

Output Tokens

285

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: After carefully analyzing the context, I'll assess the current state of the task and determine if we are on track:

1. Task Origin: User requested flight information from London to Paris for tomorrow
2. Current Progress:
   - Date for tomorrow has been identified (2025-05-29) ✓
   - Tools available: calendar (used), flights (ready to use), web_search (available) ✓
   - Current cycle: 3
   - Remaining goals: 
     a) Use 'flights' tool to get available flights
     b) Compile and present results to user

3. Status Check:
   - All prerequisites are complete
   - Next logical step is to use the 'flights' tool
   - The process is methodical and following the planned trajectory
   - No unexpected blockers or issues detected

Conclusion: We are FULLY ON TRACK. The task is progressing systematically, with all initial steps completed successfully and the next action clear.

Response: ON TRACK - The task is progressing systematically with all initial steps completed. The next action is to use the flights tool to search for available flights from London to Paris for 2025-05-29.