Agents – fireworks/minimax-m2.1 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

Input Tokens

1314

Output Tokens

885

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: I need to assess this task's complexity based on the provided framework. Let me analyze the characteristics:

**Task Breakdown:**
- Total steps: 4 (we're at step 2 of 4)
- Step 1 completed: Get tomorrow's date using calendar tool
- Remaining steps: Use flights tool, compile and present results

**Tool Requirements:**
- 2 dedicated tools needed: calendar (already used) and flights
- Both tools are available and have clear, defined purposes
- Simple tool chaining without complex interdependencies

**Reasoning Level:**
- Minimal reasoning required: format date correctly, call flights tool, present results
- No complex decision-making or conditional logic
- No need to combine outputs from multiple tools (beyond basic chaining)

**Tool Failures/Edge Cases:**
- No missing data mentioned
- No fallback strategies required
- All tools status: available

**Comparison to Definitions:**
- Easy example given: "find tomorrow's date and query flights" - THIS TASK IS LITERALLY THAT
- Linear, sequential workflow
- Clear inputs and outputs for each tool
- No adaptive planning needed beyond the basic steps

Response: **Complexity Level: Easy**

**Why:**
This task maps directly to the "Easy" example provided: "find tomorrow's date and query flights."

**Supporting factors:**
1. **Clear steps**: The task follows a simple linear sequence - get date → search flights → present results
2. **Dedicated tools exist**: Both calendar and flights tools are available and purpose-built for this task
3. **Minimal reasoning**: Only needs to format the date correctly and pass it to the flights tool
4. **No tool failures or missing data**: All required tools are status "available"
5. **No coordination complexity**: Only chaining 2 tools in sequence, no complex output combination

The task is straightforward with well-defined inputs/outputs and no need for fallback strategies or adaptive planning.

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: I need to assess this task's complexity based on the provided framework. Let me analyze the characteristics: **Task Breakdown:** - Total steps: 4 (we're at step 2 of 4) - Step 1 completed: Get tomorrow's date using calendar tool - Remaining steps: Use flights tool, compile and present results **Tool Requirements:** - 2 dedicated tools needed: calendar (already used) and flights - Both tools are available and have clear, defined purposes - Simple tool chaining without complex interdependencies **Reasoning Level:** - Minimal reasoning required: format date correctly, call flights tool, present results - No complex decision-making or conditional logic - No need to combine outputs from multiple tools (beyond basic chaining) **Tool Failures/Edge Cases:** - No missing data mentioned - No fallback strategies required - All tools status: available **Comparison to Definitions:** - Easy example given: "find tomorrow's date and query flights" - THIS TASK IS LITERALLY THAT - Linear, sequential workflow - Clear inputs and outputs for each tool - No adaptive planning needed beyond the basic steps Response: **Complexity Level: Easy** **Why:** This task maps directly to the "Easy" example provided: "find tomorrow's date and query flights." **Supporting factors:** 1. **Clear steps**: The task follows a simple linear sequence - get date → search flights → present results 2. **Dedicated tools exist**: Both calendar and flights tools are available and purpose-built for this task 3. **Minimal reasoning**: Only needs to format the date correctly and pass it to the flights tool 4. **No tool failures or missing data**: All required tools are status "available" 5. **No coordination complexity**: Only chaining 2 tools in sequence, no complex output combination The task is straightforward with well-defined inputs/outputs and no need for fallback strategies or adaptive planning.