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Fusion360 MCP Server

Fusion360 MCP Server

by faust-machines
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Python
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Split Face

split_face

Split faces of a 3D body using a specified plane in Fusion 360. Use this tool to modify geometry by dividing faces for design adjustments or preparation for further modeling operations.

Instructions

Split faces of a body using a plane

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_name": "<body_name>"
    },
    "name": "split_face"
  }
}

Input Schema

NameRequiredDescriptionDefault
body_nameYes
face_indicesNoIndices of faces to split (default: all faces)
splitting_planeNoxy
extend_toolNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations indicate this is a mutable (readOnlyHint: false), non-idempotent, and non-destructive operation. The description adds minimal behavioral context beyond this, mentioning the splitting action but not detailing effects like how faces are modified, whether the operation is reversible, or any performance considerations. No contradiction with annotations exists.

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 a single, direct sentence with no wasted words, efficiently conveying the core action. It is appropriately sized for the tool's complexity and is front-loaded with essential information.

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

Completeness2/5

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

Given the tool's moderate complexity (4 parameters, low schema coverage, no output schema) and annotations that only cover basic hints, the description is insufficient. It lacks details on parameter meanings, expected outcomes, error conditions, or how it fits within the CAD modeling workflow, making it incomplete for effective agent use.

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 low (25%), with only 'face_indices' having a description. The tool description does not compensate by explaining parameters like 'body_name', 'splitting_plane', or 'extend_tool', leaving their semantics unclear beyond what the schema minimally provides (e.g., enums for 'splitting_plane').

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 action ('split') and target resource ('faces of a body') with the method ('using a plane'), making the purpose understandable. However, it doesn't explicitly differentiate this from sibling tools like 'split_body' or 'offset_faces', which might involve similar geometric operations on CAD bodies.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites (e.g., needing an existing body), exclusions, or comparisons to sibling tools like 'split_body' or 'offset_faces', leaving the agent to infer usage scenarios.

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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