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

1156

Output Tokens

733

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 assess the current state by analyzing the trajectory and progress:

1. **Progress Tracking**: Step 2 of 4 is completed (interpret tool result and decide next action). The calendar tool successfully returned '2025-05-29', which is tomorrow's date.

2. **Remaining Steps**: We have 2 steps left - use the flights tool and compile/present results.

3. **Trajectory Analysis**:
   - Step 1 (Determine date): COMPLETE ✓
   - Step 2 (Interpret and decide): COMPLETE ✓
   - Step 3 (Execute flight search): Ready to proceed
   - Step 4 (Compile results): Pending

4. **Resource Check**: All required tools are available (calendar, flights, web_search). The flights tool requires from_city, to_city, and date - we have all this information.

5. **No Issues Detected**: The workflow is following the planned sequence without deviations, errors, or blockers.

**Conclusion**: We are ON TRACK. The next logical step is to call the flights tool with from_city='London', to_city='Paris', and date='2025-05-29'.

Response: ON TRACK

**Assessment Details:**
- **Current Position**: Step 2 of 4 completed
- **Next Action**: Proceed to Step 3 - call the flights tool with London to Paris for 2025-05-29
- **No blockers or issues**
- **Workflow is following the planned trajectory**

The date (2025-05-29) has been confirmed and formatted correctly for the flights tool. Ready to execute the flight search to proceed to the next step.