Agents – gcp/gemini-3-pro-preview Task

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

11s

Input Tokens

1475

Output Tokens

850

Cost

$0.00

Context

Input

What is the complexity of this task?

Task complexity refers to how challenging a task is for the agent to complete, based on the number of steps required, the need for reasoning or coordination, and the availability of tools.

Examples:
- Easy: A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights).
- Medium: Several steps; requires combining many outputs from multiple tools (more than 4); moderate reasoning (e.g., summarize document changes across multiple files and generate a review).
- Complex: Many steps; adaptive planning; potential missing data or tool failures; fallback strategies required (e.g., plan a multi-leg trip with hotel, flight, visa checks, and dynamic adjustments).

Please select the appropriate complexity level for this task and explain why.

Expected output

This task is **easy**. It only requires determining tomorrow’s date and querying available flights — both of which have dedicated, reliable tools. There’s minimal reasoning

Model output

Reasoning: 1. **Analyze the User Request**: The user wants to find flights from London to Paris for tomorrow. 
2. **Review the Steps**: The agent has already retrieved the date ('2025-05-29') using the `calendar` tool. The remaining steps are to call the `flights` tool with this date and then present the results. This implies a total of roughly 3-4 steps.
3. **Evaluate Tool Availability**: Dedicated tools (`calendar` and `flights`) exist and are available for every part of the request.
4. **Assess Reasoning Level**: The logic is linear and sequential (Get Date -> Query Flights -> Return Answer). There is no need for complex synthesis of multiple documents or adaptive planning against failures.
5. **Compare with Complexity Definitions**: The task aligns perfectly with the 'Easy' definition provided: 'A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights)'.

Response: Easy

**Reasoning:**
This task fits the definition of **Easy** because:
1. **Clear, Linear Steps:** The trajectory involves a straightforward sequence: determine the date, query the flight database, and report the results. The progress indicates it is step 2 of 4, which is a small number of steps.
2. **Dedicated Tools:** The agent has access to specific tools (`calendar` and `flights`) that directly address the user's needs without requiring workarounds or general web searches.
3. **Minimal Reasoning:** The task does not require combining a large number of outputs or handling complex logical conditions; it is a direct information retrieval task.

What is the complexity of this task? Task complexity refers to how challenging a task is for the agent to complete, based on the number of steps required, the need for reasoning or coordination, and the availability of tools. Examples: - Easy: A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights). - Medium: Several steps; requires combining many outputs from multiple tools (more than 4); moderate reasoning (e.g., summarize document changes across multiple files and generate a review). - Complex: Many steps; adaptive planning; potential missing data or tool failures; fallback strategies required (e.g., plan a multi-leg trip with hotel, flight, visa checks, and dynamic adjustments). Please select the appropriate complexity level for this task and explain why.

Reasoning: 1. **Analyze the User Request**: The user wants to find flights from London to Paris for tomorrow. 2. **Review the Steps**: The agent has already retrieved the date ('2025-05-29') using the `calendar` tool. The remaining steps are to call the `flights` tool with this date and then present the results. This implies a total of roughly 3-4 steps. 3. **Evaluate Tool Availability**: Dedicated tools (`calendar` and `flights`) exist and are available for every part of the request. 4. **Assess Reasoning Level**: The logic is linear and sequential (Get Date -> Query Flights -> Return Answer). There is no need for complex synthesis of multiple documents or adaptive planning against failures. 5. **Compare with Complexity Definitions**: The task aligns perfectly with the 'Easy' definition provided: 'A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights)'. Response: Easy **Reasoning:** This task fits the definition of **Easy** because: 1. **Clear, Linear Steps:** The trajectory involves a straightforward sequence: determine the date, query the flight database, and report the results. The progress indicates it is step 2 of 4, which is a small number of steps. 2. **Dedicated Tools:** The agent has access to specific tools (`calendar` and `flights`) that directly address the user's needs without requiring workarounds or general web searches. 3. **Minimal Reasoning:** The task does not require combining a large number of outputs or handling complex logical conditions; it is a direct information retrieval task.