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

3631

Output Tokens

249

Cost

$0.00

Context

Input

You need to list all open orders for a specific customer whose ID is `cust_42`. Which tool/method do you choose and what parameter object do you send?

Expected output

Use the **database** tool with parameters {"action": "list_orders", "customer_id": "cust_42"}.

Model output

Reasoning: I need to list all open orders for a specific customer with ID 'cust_42'. First, I examine the available tools from the context. The relevant tool is 'database' which has a method 'list_orders'. I look at the params_schema for the database tool: it's an object with required 'action' and conditional requirements based on action. For action 'list_orders', the schema requires 'action' and 'customer_id'. Since I have the customer ID, I can call the database tool with action 'list_orders' and customer_id 'cust_42'. I should follow the general rules: inspect first (I've examined the schema), plan the next atomic action (call list_orders), act (call tool), reflect, decide next. However, the task is only to choose the tool/method and specify the parameter object, not to execute the full cycle. I'll answer directly.

Response: I choose the 'database' tool with the 'list_orders' method. The parameter object I send is: {"action": "list_orders", "customer_id": "cust_42"}