rescale_model

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

With no annotations, the description carries full burden. It discloses that the file is modified in-place and clarifies the effect of each parameter group. It could improve by mentioning the return value or error handling, but it is still transparent about core behavior.

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

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

The description is well-structured with markdown headings, bullet points, and inline code formatting. It is concise yet conveys all necessary information, prioritized at the front.

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

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

The description thoroughly covers input parameters and behavior. However, it does not describe the tool's output (e.g., success/error, new file, or side effects beyond modifying in-place). Given no output schema, this is a minor gap, but overall it is fairly complete.

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

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

Schema coverage is 0%, so the description fully compensates. It explains each parameter's role (target_height_mm, scale_factor, max_dimension_mm, scale_x/y/z), default behaviors, and constraints (e.g., omitted axes default to 1.0). The docstring is detailed and actionable.

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

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

The description clearly states the tool: 'Rescale an STL model to meet dimensional targets.' It explains two distinct scaling modes (uniform and per-axis) and provides specific parameter groups, distinguishing it from siblings like 'scale_mesh_to_fit' by covering multiple scaling strategies.

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

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

The description identifies when the tool is useful (wrong size, mismatch with build volume) and explicitly states that uniform and per-axis options cannot be combined. However, it does not name alternative sibling tools or specify when NOT to use it, leaving some ambiguity.

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