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gen_tripo_multiview_to_model

Generate a 3D model from four-view reference images by submitting them as a Tripo multiview-to-model task.

Instructions

Submit a Tripo multiview_to_model task from ordered front/left/back/right images.

KB: see knowledge_base/31_GENERATIVE_CONTENT_PIPELINE.md#tripo-task-family Example: gen_tripo_multiview_to_model(images=[{"image_url":"https://example.com/front.png"},{"image_url":"https://example.com/left.png"}], confirm_spend=True)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pbrNo
quadNo
imagesNo
textureNo
auto_sizeNo
face_limitNo
model_seedNo
session_nameNodefault
texture_seedNo
confirm_spendNo
model_versionNo
generate_partsNo
smart_low_polyNo
texture_qualityNo
geometry_qualityNostandard
original_task_idNo
texture_alignmentNooriginal_image

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only says 'Submit a ... task' and includes confirm_spend=True in the example, hinting at a paid/credit-consuming operation, but it does not disclose async behavior, task IDs, polling requirements, credit costs, or what happens after submission.

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?

The description is short and front-loaded: purpose first, then a KB pointer, then a concrete callable example. The example is helpful, though it shows only two images while the text says front/left/back/right, so it is slightly inconsistent.

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 17 parameters, 0% schema coverage, no annotations, and only a minimal description, this is under-specified for correct invocation. An output schema exists so return values are covered, but the description only partially handles the input contract and leaves much to the KB reference.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It does add useful semantics via the example, showing images as an array of objects with 'image_url' and confirming the order matters. But 17 parameters exist and only images and confirm_spend are illustrated; most optional settings like pbr, quad, texture_quality, seeds, and model_version are left unexplained.

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 and resource: 'Submit a Tripo multiview_to_model task from ordered front/left/back/right images.' This clearly distinguishes it from sibling tools like gen_tripo_text_to_model and gen_tripo_image_to_model by naming the input modality and ordering requirement.

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 clearly implies when to use this tool: when you have ordered front/left/back/right images. The KB reference points to the broader tripo-task-family, which likely contains further guidance. However, it does not explicitly exclude alternatives such as gen_tripo_image_to_model for single-image inputs.

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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