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ttiimmaacc

mcp-for-clo3d

by ttiimmaacc

get_arrangement_points

Retrieve the avatar's arrangement points in a CLO3D scene to enable pattern placement. Use these points to position patterns accurately on the avatar.

Instructions

List the avatar's arrangement points (needs an avatar in the scene) for place_pattern.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It discloses a prerequisite (avatar presence) and the read-like nature of 'list', but it does not specify what happens if the precondition fails, the exact return format, or any side effects. The prerequisite disclosure is useful, but more behavioral detail would be expected 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.

Conciseness5/5

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

The entire description is a single, front-loaded sentence that conveys the action, a prerequisite, and the intended use case with no filler. Every clause adds value, making it an excellent example of concise writing.

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

Completeness4/5

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

For a zero-parameter tool with no output schema, the description covers the essential elements: what it does, a key prerequisite, and its purpose. It could mention the return value (a list of points) explicitly, but that is strongly implied by 'list' and the context, so it is adequate for the tool's simplicity.

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

Parameters4/5

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

The tool has zero parameters and the schema is empty, so the baseline is 4. The description does not need to add parameter semantics, and it correctly avoids inventing any.

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 verb 'list' and the resource 'avatar's arrangement points', with an explicit purpose ('for place_pattern'). It distinguishes from potential siblings like get_arrangement_list by scoping to the avatar and the placement use case, though it doesn't name an alternative directly.

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

Usage Guidelines3/5

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

It provides a clear precondition ('needs an avatar in the scene') and an implied usage context ('for place_pattern'), but it does not explicitly contrast with alternatives like get_arrangement_list or state when not to use it. The guidance is present but not fully explicit.

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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