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minimax_plan

Generate a structured JSON implementation plan for coding tasks using MiniMax AI, reducing token usage.

Instructions

Generate a structured implementation plan as JSON using MiniMax AI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesDescription of the task to plan
codebaseContextNoContext about the codebase
modelNoModel override (default: MINIMAX_DEFAULT_MODEL env var, typically M2.7)
Behavior2/5

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

No annotations are present, so the description must fully disclose behavioral traits. It fails to mention whether the plan is purely text-based, any constraints (e.g., token limits, speed), or side effects like modifications to the codebase. The description is too terse for a tool with zero annotation coverage.

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

Conciseness4/5

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

The description is a single concise sentence with no wasted words. However, it could include more essential information (e.g., output format, usage note) without becoming verbose.

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

Completeness2/5

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

No output schema exists, so the description should describe the structure of the generated plan. It does not, leaving agents uninformed about return values. For a planning tool, this is a significant gap.

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 the input schema already describes all three parameters (task, codebaseContext, model). The description adds no additional meaning beyond 'Generate...plan as JSON', which aligns with the task parameter but does not augment parameter understanding. Baseline of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool generates a structured implementation plan as JSON, using a specific verb (Generate) and resource (implementation plan). It is distinguishable from siblings like minimax_generate_code, which focuses on code generation, but the description could be more explicit about what kind of plan is produced.

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 is provided on when to use this tool versus alternatives such as minimax_generate_code or minimax_chat. The description lacks context about prerequisites, typical use cases, or exclusions.

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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