scale_entity

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

With no annotations, the description must cover behavioral traits. It describes input formats but does not disclose side effects (e.g., if scaling is destructive, permissions required, or return value). The tool likely mutates the entity, but this is not stated.

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?

Two sentences, front-loaded with the core action, then details. No unnecessary words.

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 covers parameter usage adequately but lacks information about return values, side effects, or constraints (e.g., positive scale values). Given the low complexity (3 params, no nested objects), it is partially complete but misses behavioral context.

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 100%, providing a baseline of 3. The description adds value by explaining the scale parameter can be a number or array for uniform/non-uniform scaling, which is partially in the schema but clarified here. The origin parameter is also described.

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 scales an entity, specifying two modes: uniform scaling with a single number and non-uniform scaling with an [x, y, z] array. This differentiates it from sibling tools like move_entity or rotate_entity.

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 explains how to use the tool (uniform vs non-uniform, optional origin) but does not explicitly state when to choose this tool over alternatives or any exclusions. Usage is implied through the parameter explanations.

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