Xenition

Create a 3D model

create_3d_model

Generate a 3D model (glTF/GLB) in the user's Xenition workspace from a text prompt or a reference image. Starts generation and returns immediately; an interactive inline preview fills in as it renders (~30-60s, longer for 'realistic'), plus a link to open, edit, and export it (GLB/STL/OBJ) in Xenition. Use when the user asks for a 3D model, mesh, or asset. Best for a single object.

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": {
      "prompt": "<prompt>"
    },
    "name": "create_3d_model"
  }
}

Input Schema

Name	Required	Description
`title`	No	optional title for the saved model; defaults to the prompt
`prompt`	Yes	what the 3D model should be — a single object works best (e.g. 'a low-poly wooden sailboat')
`quality`	No	'draft' (default, fast) or 'realistic' (higher fidelity, slower — a few minutes)
`imageUrl`	No	optional URL of a reference image to turn into 3D (image-to-3D); when set the prompt guides the conversion

Output Schema

Name	Required	Description	Default
`error`	No
`jobId`	No
`title`	No
`glbUrl`	No
`prompt`	No
`status`	Yes
`openUrl`	No
`quality`	No
`artifactId`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 3, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Goes well beyond the annotations by disclosing the async contract ('starts generation and returns immediately'), render timing (~30-60s, longer for 'realistic'), an inline preview that fills in progressively, and a follow-up link for open/edit/export. None of this is available from the readOnly/destructive/openWorld hints, and it materially changes how an agent should sequence the call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Front-loaded with the core action and scoped well; every sentence carries information. The second sentence is somewhat dense, packing async behavior, timing, preview, and export link into one clause chain, but nothing is truly wasteful.

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?

With an output schema present, return values need not be described, and the description covers purpose, async lifecycle, timing, and usage context. It could be slightly more complete by noting whether/how to poll via the sibling check_3d_model, but overall it is sufficient to invoke correctly.

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 documents prompt, imageUrl, quality, and title with examples. The description only restates the prompt/imageUrl relationship ('from a text prompt or a reference image') and the 'single object' guidance, adding little over structured fields, so the baseline of 3 applies.

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?

States a specific verb and resource ('Generate a 3D model (glTF/GLB)') from a text prompt or reference image, and names output formats (GLB/STL/OBJ). This clearly distinguishes it from sibling media tools like create_image, create_video, or create_diagram without needing to open the schema.

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?

Provides explicit when-to-use triggers ('when the user asks for a 3D model, mesh, or asset') and a scoping hint ('Best for a single object'). It gives clear context but stops short of naming alternatives or exclusions, e.g. when 2D output (create_image) would be preferred.

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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