Retrieves the avatar's body measurements in millimeters for pattern drafting. Uses CLO's measurement API, cached data, or mesh approximation to provide accurate sizing.
Body measurements (mm) of the avatar in the scene, used for drafting. Source: CLO's measurement API (needs the Avatar Editor opened once per session in CLO), a cache, or an approximation from the avatar mesh.
| Name | Required | Description | Default |
|---|---|---|---|
| refresh | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains that measurements can come from CLO's measurement API, a cache, or an approximation from the mesh, and mentions the prerequisite of opening the Avatar Editor. It does not explain the effect of the 'refresh' parameter, which is a notable gap, but the disclosed sourcing behavior is valuable.
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 a single, dense sentence that front-loads the core purpose and then adds the source and prerequisite. Every clause contributes meaning, and there is no redundancy or filler.
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 purpose, units, source, and a prerequisite, which is a solid baseline. However, the behavior of the 'refresh' parameter is unexplained, and since there is no output schema, the return shape is also unspecified. For a one-parameter tool this is not severely incomplete, but meaningful gaps remain.
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?
The sole parameter 'refresh' is not mentioned in the description, and schema description coverage is 0%. The schema's title and default provide only minimal meaning, and the description does not clarify when refresh should be true or what happens when it is set. Given the low coverage, the description should have compensated but does not.
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 identifies the resource ('body measurements of the avatar in the scene'), the unit (mm), and the purpose ('used for drafting'). It lacks an explicit imperative verb like 'get' or 'returns', and does not explicitly differentiate from siblings, but the resource and scope are specific enough that an agent can infer the tool's purpose.
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 gives clear context: the measurements are used for drafting and may require the Avatar Editor to have been opened once per session. It does not explicitly name alternatives or exclusions, but the use case is stated well enough to guide selection among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.