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
16s
Input Tokens
1132
Output Tokens
608
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. **Understanding the Task and Context**:
       - The user's original request was to find flights from London to Paris for 'tomorrow'.
       - The current date was resolved in a prior cycle using the `calendar` tool, which returned `'2025-05-29'` as tomorrow's date.
       - The trajectory shows progress: the date is confirmed, and the next logical step is to query the `flights` tool with the resolved date and cities.

    2. **Assessing Current State**:
       - **Progress So Far**:
         - Step 1 (resolve date) is complete. The date `'2025-05-29'` is confirmed and matches the `flights` tool's required format (`YYYY-MM-DD`).
         - Step 2 (planned: query `flights` tool) is pending execution.
       - **Remaining Goals**:
         - Use the `flights` tool with parameters: `from_city='London'`, `to_city='Paris'`, `date='2025-05-29'`.
         - Compile and present the flight results to the user.
       - **Tools Available**:
         - `flights` tool is available and ready for use with the correct parameters.
         - No blockers or missing information detected.

    3. **On-Track Evaluation**:
       - The plan is **on track**. The trajectory aligns with the user's request, and all prerequisites for the next action (querying flights) are satisfied.
       - No deviations or errors are observed. The next action is clear and directly advances the goal.

    4. **Next Steps**:
       - Proceed to **Cycle 4** to execute the `flights` tool with the resolved parameters.
       - After receiving flight data, compile it into a user-friendly summary (e.g., list of flights with times, prices, or carriers).
       - Present the results to the user in the subsequent cycle.
    

Response: 
    **Assessment**: The task is **on track**.
    **Current Status**:
    - Tomorrow's date (`2025-05-29`) is confirmed.
    - Next action: Query the `flights` tool for London → Paris on `2025-05-29`.
    - No obstacles detected; all tools and parameters are ready.

    **Next Steps**:
    1. Execute the `flights` tool with:
       ```json
       {"from_city": "London", "to_city": "Paris", "date": "2025-05-29"}
       ```
    2. Store the flight results in working memory.
    3. Present the compiled flight options to the user in the following cycle.