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generate_model

Turn a text description into a 3D model using AI (Meshy) or OpenSCAD. Ideal for creating custom objects without templates or images.

Instructions

Generate a 3D model from a text prompt via external AI API (Meshy/etc).

        Pass ``material`` when the user has named one ("print this in
        TPU") — it steers the design-intelligence prompt enrichment
        toward that material's constraints.  It is a design hint, not a
        slicing setting; leave it empty when the material is undecided.

        Start here if user has no template/image — just a text description.
        For image-based generation, use ``generate_model_from_image``.
        For parametric templates (local, no AI API needed), use ``generate_from_template``.
        To also slice + upload in one step, use ``generate_and_print``.

        **EXPERIMENTAL:** AI-generated 3D models are experimental and may not
        be suitable for printing without manual review.  Generated geometry
        can have thin walls, non-manifold faces, floating islands, or
        dimensions that exceed printer build volume.  3D printers are delicate
        hardware — always validate the generated mesh before printing.

        **When possible, prefer downloading proven community models from
        marketplaces** (Thingiverse, MyMiniFactory) over generating new ones.
        Use generation for custom/unique objects only.

        Submits a generation job to the specified provider and returns a
        job ID for status tracking.  Use ``generation_status`` to poll for
        completion, then ``download_generated_model`` to retrieve the file.

        **Prompt tips for Meshy (text-to-3D AI):**
        - Describe the physical object clearly: shape, size, purpose.
        - Include material cues: "wooden", "metallic", "smooth plastic".
        - Specify printability: "solid base", "no overhangs", "flat bottom".
        - Keep prompts under 200 words for best results (max 600 chars).
        - Good example: "A phone stand with a curved cradle, flat rectangular
          base, and angled back support. Smooth plastic surface."
        - Bad example: "make me something cool" (too vague).

        **For OpenSCAD**, the prompt must be valid OpenSCAD code.  The job
        completes synchronously and the result is immediately available.

        Args:
            prompt: Text description (or OpenSCAD code for ``openscad``).
            provider: Generation backend — ``"meshy"`` (cloud AI) or
                ``"openscad"`` (local parametric).  Default: ``"meshy"``.
            format: Desired output format (``"stl"``).  Default: ``"stl"``.
            style: Optional style hint (``"realistic"`` or ``"sculpture"``
                for Meshy).  Ignored by OpenSCAD.
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNo
formatNostl
promptYes
materialNo
providerNomeshy
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: experimental nature, risks (non-printable geometry), workflow (submit job, poll, download), and provider differences (Meshy vs OpenSCAD).

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?

Well-structured with sections, bullet points, and front-loaded summary. Some verbosity in prompt examples, but generally efficient and easy to scan.

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?

Given the tool's complexity and no output schema, the description covers all essential aspects: purpose, when to use, workflow, risks, parameter details, and provider-specific notes. Complete and self-contained.

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

Parameters5/5

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

Schema coverage is 0%, but the description thoroughly explains all 5 parameters: prompt (text or OpenSCAD), provider (meshy/openscad), format (stl), style (optional, ignored by OpenSCAD), and material (design hint). Includes prompt tips.

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?

Clearly states the tool generates a 3D model from a text prompt via external AI API. Distinguishes from sibling tools by explicitly naming alternatives for image-based generation, parametric templates, and combined slice+upload.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool (text description, no template/image) and when to use alternatives. Provides guidance on the 'material' parameter and OpenSCAD prompt requirements.

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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