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nludd25
by nludd25

import_generated_asset_hunyuan

Import a Hunyuan3D-generated 3D asset into Blender using its result file URL. Provide the object name and a .glb (or .zip/.obj) URL to place the generated model in the scene.

Instructions

Import the asset generated by Hunyuan3D after the generation task is completed.

Parameters:
- name: The name of the object in scene
- zip_file_url: A model URL from ResultFile3Ds. Prefer a .glb URL when available; .zip/.obj URLs still work as a fallback.

Return if the asset has been imported successfully.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
zip_file_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the import action and the return value ('Return if the asset has been imported successfully'), but it doesn't mention side effects like whether the asset replaces an existing object, whether it requires a prior generation task, or any failure modes. The return statement is vague ('if' could mean a boolean or an error).

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 compact and front-loaded with the main purpose, followed by parameter details and a return note. Every sentence earns its place, though the 'Return if...' line is slightly awkward and could be clearer.

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

Completeness3/5

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

For a 2-parameter tool with no output schema and no annotations, the description covers the core usage: what to pass and what to expect. However, it lacks context on prerequisites (e.g., must have a completed Hunyuan3D generation task), error handling, and what 'imported successfully' means in terms of return value. The sibling 'import_generated_asset' suggests there may be a generic version, and the description doesn't clarify why an agent would choose this Hunyuan-specific one.

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 description coverage is 0%, so the description must compensate. It does: it explains 'name' is the object name in the scene and 'zip_file_url' is a model URL from ResultFile3Ds with format preferences. This adds meaning beyond the bare schema titles, though it could be more explicit about the exact format expected for 'name'.

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 tool imports an asset generated by Hunyuan3D after generation completes, with a specific verb ('Import') and resource ('asset generated by Hunyuan3D'). It distinguishes itself from the sibling 'import_generated_asset' by naming the Hunyuan3D source, though it doesn't explicitly contrast with that sibling.

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 gives clear context: use after the generation task is completed, and it specifies the zip_file_url should come from ResultFile3Ds, preferring .glb URLs with .zip/.obj as fallback. It doesn't explicitly say when not to use it or name alternatives, but the context is sufficient for an agent to select it appropriately among siblings.

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