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hellstein-dev

fusion-mcp

appearance_assign

Assigns a library appearance to a body, face, or occurrence by copying it into the design. Use it to change how a part looks without altering its physical material.

Instructions

Assign an appearance to a body, a face or an occurrence. A library appearance is copied into the design first (the library is never changed). A component has no appearance: assign it to its bodies or to an occurrence. Changes only the look, not the physical material (see material_assign).

Returns {"target", "appearance": {"id", "name", "library": "design"}, "previous": {...} | null, "copied": bool}.

Example: appearance_assign(target="", appearance="").

Input Schema

NameRequiredDescriptionDefault
targetYesRef of a body, a face or an occurrence (not a component)
libraryNoLibrary name or id to resolve an ambiguous name
appearanceYesAppearance id from appearance_list (preferred) or exact name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does well: library appearances are copied into the design, the source library is never changed, and the operation affects only visual appearance. It also discloses the return shape including previous and copied. It does not explain failure behavior or permissions, which keeps it below 5.

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 description is compact and front-loaded: purpose first, caveats second, return shape third, and an example last. Every sentence contributes useful information and no space is wasted.

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

Completeness5/5

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

For a mutation tool with no annotations and no output schema, the description is unusually complete. It covers allowed targets, the component restriction, the library-copy behavior, the distinction from material assignment, and the return structure, leaving little an agent needs to infer before calling it.

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 description coverage is 100%, so the schema already explains target, library, and appearance. The description adds a usage example and reinforces that appearance should come from appearance_list, but it does not add new meaning beyond the schema, especially for the library parameter. Baseline 3 is appropriate.

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

Purpose5/5

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

The first sentence gives a specific verb and resource: assign an appearance to a body, face, or occurrence. It distinguishes the tool from material_assign by stating that it changes only the look, not the physical material. The target scope is clearly bounded.

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

Usage Guidelines4/5

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

The description gives clear usage context: components have no appearance, so assignment must go to bodies or an occurrence, and material assignment is explicitly routed to material_assign. It does not compare against appearance_set_color or otherwise enumerate all sibling alternatives, so it stops short of a full 5.

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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