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
3s
Input Tokens
1509
Output Tokens
311
Cost
$0.00
Context
Input
As the first step you are reflecting and deciding on the plan to follow to complete the task. You have three candidate plans:

A) Plan A:
- Step 1 → Call calendar to get tomorrow’s date.
- Step 2 → Call flights (London ➜ Paris, date).
- Step 3 → Call web_search with query "London to Paris flights on [date]" to cross-check available flights found in the previous step.
- Step 4 → If there are discrepancies between flights tool and web search, re-query flights tool for confirmation.
- Step 5 → Summarize all gathered flight options and send results to the user.

B) Plan B:
- Step 1 → Call calendar to get tomorrow’s date.
- Step 2 → Call flights (London ➜ Paris, date).
- Step 3 → Summarize flights tool results and send to the user.

C) Plan C:
- Step 1 → Call calendar to get tomorrow’s date.
- Step 2 → Call flights (London ➜ Paris, date).
- Step 3 → If the flights tool returns fewer than 3 options, call web_search with query "London to Paris flights on [date]" to supplement results.
- Step 4 → Merge both sets of results and send the combined summary to the user.

Pick **one** plan you will execute.
Expected output
Plan B, is the preferred one as its the most efficient, and that is instructed
Model output
Reasoning: The user's request, reflected in the context trigger, is to find available flights from London to Paris for tomorrow. The instructions emphasize choosing the most direct and effective path.

**Analysis of Plans:**
*   **Plan A:** Involves calling `flights` and then using `web_search` for cross-checking, with an extra step to re-query if discrepancies are found. This is robust but involves unnecessary redundancy if the `flights` tool is reliable (Step 4 adds complexity).
*   **Plan B:** This is the most direct path: get tomorrow's date, call the flights tool, and summarize. It relies solely on the dedicated `flights` tool, which is the primary intended method for this task.
*   **Plan C:** Calls `web_search` only if the `flights` tool returns fewer than 3 options. This introduces conditional logic and relies on the web search to *supplement* results, which might lead to merged, potentially conflicting, or less structured output than a primary tool call.

**Decision:** Plan B is the most direct and efficient approach to fulfilling the core request: find flights for tomorrow. It utilizes the dedicated tool (`flights`) immediately after determining the date, adhering to the instruction to aim for the 'most direct and effective path.'

**Selected Plan:** Plan B.

Response: Plan B