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.

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.

Reasoning: The goal is to find available flights from London to Paris for tomorrow in the most direct yet reliable manner. • Plan A involves an automatic cross-check with web search every time, which adds extra calls even if the flights tool alone is sufficient—less efficient. • Plan B is the fastest (only one tool after calendar), but it could give an incomplete answer if the flights tool returns few options. • Plan C first tries the flights tool and only invokes a web search when it is likely needed (fewer than 3 results), striking a balance between efficiency and completeness. Given the instructions to be both effective and efficient, Plan C offers the best trade-off: minimal redundancy while still ensuring we can supplement data when necessary. Response: I will execute Plan C.

Agents

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