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
44s
Input Tokens
1467
Output Tokens
520
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: Let me analyze the three candidate plans to determine which one is most appropriate for finding flight information from London to Paris for tomorrow.

Plan A involves:
1. Getting tomorrow's date from calendar
2. Using the flights tool
3. Cross-checking with web search
4. Re-querying if there are discrepancies
5. Summarizing all results

This plan seems overly complex and could lead to unnecessary API calls. Cross-checking every result with web search and potentially re-querying creates redundancy without clear benefit.

Plan B involves:
1. Getting tomorrow's date from calendar
2. Using the flights tool
3. Summarizing and sending results

This is the most straightforward approach. Since we have a dedicated flights tool that is specifically designed for finding available flights, this should be our primary and potentially only source. It's direct and efficient.

Plan C involves:
1. Getting tomorrow's date from calendar
2. Using the flights tool
3. Only using web search if fewer than 3 options are returned
4. Merging results if needed

This plan provides a good balance - it relies primarily on the specialized flights tool but has a fallback mechanism if the results are limited. This ensures comprehensive results without unnecessary redundancy.

Considering the user's request is straightforward ("find information about available flights from London to Paris for tomorrow"), and we have a dedicated flights tool available, Plan B is the most efficient approach. The flights tool should provide comprehensive flight information, and adding web search would likely just duplicate the same information rather than add value. Plan B follows the principle of using the most direct and effective path as mentioned in the instructions.

Response: I will execute **Plan B**.

This plan is the most efficient and direct approach because:
1. We have a dedicated flights tool specifically designed for finding available flights
2. The user's request is straightforward - they need flight information from London to Paris for tomorrow
3. The flights tool should provide comprehensive results without needing web search verification
4. This approach avoids unnecessary API calls and potential redundancy
5. It follows the instruction to "aim for the most direct and effective path"