fusion-reconstruct-mcp

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fusion_shell

Create a hollow shell from a solid body by specifying wall thickness and direction. Remove selected face indices to leave openings, producing containers like open-top boxes.

Instructions

Hollow out a solid body into a shell. Pass remove_face_indices (from fusion_get_body_info's face_index, matched by its normal/point_on_face_mm) to leave those faces open - e.g. remove the top face of a box to turn it into an open-top container. Omit for a fully closed hollow shell. direction: "inside" | "outside" | "both" - which way the wall thickness is measured from the original surface.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "body_id": "<body_id>",
      "thickness_mm": "<thickness_mm>"
    },
    "name": "fusion_shell"
  }
}

Input Schema

Name	Required	Default
`body_id`	Yes
`direction`	No	inside
`thickness_mm`	Yes
`remove_face_indices`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 21, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It explains the mutation (hollowing), the effect of remove_face_indices and direction, and provides an example. It does not explicitly state permanent modification or lack of undo, but the verb 'hollow out' makes this evident.

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 about 80 words, front-loaded with the primary action, then detailed parameter guidance. Every sentence provides value; no redundancy or fluff.

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 moderate-complexity modeling tool with no output schema, the description adequately covers the operation, parameters, and a concrete example. It does not mention return values or error cases, but these are less critical for a body-modifying operation.

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?

Schema coverage is 0%, so the description must compensate. It adds essential meaning to remove_face_indices (origin and matching method) and direction (inside/outside/both semantics). body_id and thickness_mm remain self-explanatory from their names.

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 description uses a specific verb+resource ('Hollow out a solid body into a shell') that clearly distinguishes this from sibling modeling tools like extrusion or fillet. The scope is unambiguous and the example reinforces its purpose.

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?

It provides clear when-to-use guidance: passing remove_face_indices to open faces versus omitting for a closed shell. It references how to obtain face indices from fusion_get_body_info, but does not explicitly compare with alternatives or state when not to use this tool.

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