Agents – novita/minimax-m2 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

14s

Input Tokens

1353

Output Tokens

779

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: Looking at the task and context, I need to evaluate the complexity of finding flights from London to Paris for tomorrow. The user has already determined tomorrow's date (2025-05-29) using the calendar tool, and the next step is simply to query the flights tool with the required parameters (from_city: London, to_city: Paris, date: 2025-05-29). This task has: 1) A small number of clear steps (determine date, search flights, present results), 2) Dedicated tools available (calendar and flights tools), 3) Minimal reasoning required - just matching parameters to tool requirements, 4) No need to combine outputs from multiple tools, 5) No complex planning or fallback strategies needed. This directly matches the definition of an 'Easy' task as provided in the examples: 'A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights).'

Response: Easy

This task fits the definition of 'Easy' complexity because it involves a small number of clear steps (determining the date and querying flights), has dedicated tools available (calendar and flights tools), and requires minimal reasoning. The task is straightforward - once tomorrow's date was determined, it's simply a matter of calling the flights tool with the appropriate parameters (London, Paris, 2025-05-29) and presenting the results. This matches the provided example of an Easy task: 'find tomorrow's date and query flights.'

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: Looking at the task and context, I need to evaluate the complexity of finding flights from London to Paris for tomorrow. The user has already determined tomorrow's date (2025-05-29) using the calendar tool, and the next step is simply to query the flights tool with the required parameters (from_city: London, to_city: Paris, date: 2025-05-29). This task has: 1) A small number of clear steps (determine date, search flights, present results), 2) Dedicated tools available (calendar and flights tools), 3) Minimal reasoning required - just matching parameters to tool requirements, 4) No need to combine outputs from multiple tools, 5) No complex planning or fallback strategies needed. This directly matches the definition of an 'Easy' task as provided in the examples: 'A small number of clear steps; dedicated tools exist; minimal reasoning needed (e.g., find tomorrow's date and query flights).' Response: Easy This task fits the definition of 'Easy' complexity because it involves a small number of clear steps (determining the date and querying flights), has dedicated tools available (calendar and flights tools), and requires minimal reasoning. The task is straightforward - once tomorrow's date was determined, it's simply a matter of calling the flights tool with the appropriate parameters (London, Paris, 2025-05-29) and presenting the results. This matches the provided example of an Easy task: 'find tomorrow's date and query flights.'