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minimax_agent_task

Execute a complete coding task autonomously: reads files, writes code, runs tests, and debugs in a loop until finished.

Instructions

Execute a complete coding task autonomously. MiniMax AI will read files, write code, run tests, and debug in an autonomous loop until the task is complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesFull description of the task for the agent to complete
workingDirectoryYesAbsolute path to the working directory for file operations
modelNoModel override (default: MINIMAX_DEFAULT_MODEL env var, typically M2.7)
maxIterationsNoMaximum agent loop iterations (default: 25)
systemPromptNoCustom system prompt for the agent
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries the full burden. It discloses autonomous loop behavior ('reads files, writes code, runs tests, and debug') and mentions the maxIterations parameter. However, it does not cover potential side effects (file modifications), resource consumption, or what happens on failure beyond 'until complete'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. The first sentence states the core purpose, and the second provides essential details (autonomous loop, actions). It is front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main loop behavior but omits return format or status reporting. With no output schema, the agent cannot infer what the tool returns. For a complex tool like this, more contextual completeness is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds no extra semantic value beyond the schema's parameter descriptions. For example, 'task' in description matches schema, no additional context for parameters like 'model' or 'systemPrompt'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool's purpose: 'Execute a complete coding task autonomously' and details activities like reading files, writing code, running tests, and debugging. This clearly distinguishes it from siblings such as minimax_chat (conversation) and minimax_generate_code (code generation without full loop).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., minimax_plan for planning-only, minimax_generate_code for code-only). The description implies it is for full coding tasks but does not specify exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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