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texture_model

Generate or regenerate textures for 3D models using text prompts, style images, or image prompts. Supports PBR materials, baking, and compression.

Instructions

Generate or regenerate textures for an existing model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pbrNoEnable PBR materials
bakeNoBake generated textures
inputYesTask ID, model URL, or file token to texture
modelNoOptional texture model version
textureNoEnable texture generation
compressNoCompress model geometry
partNamesNoSpecific segmented part names to texture
styleImageNoStyle image URL or file token for texture generation
textPromptNoText prompt for texture generation
imagePromptNoImage prompt URL or file token for texture generation
textureSeedNoOptional seed for texture generation
textureQualityNoTexture quality: standard, detailed, or extreme
textureAlignmentNoTexture alignment priority: original_image or geometry

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
taskIdYes
Behavior2/5

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

No annotations are present, so the description must fully disclose behavior. It only states 'generate or regenerate', omitting any details about whether textures are overwritten, required permissions, or asynchronous behavior. This is insufficient for a mutation tool.

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

Conciseness3/5

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

The description is a single concise sentence, but it lacks sufficient detail to be useful. While front-loaded, it does not fully earn its place given the tool's complexity.

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 complexity of the tool (13 parameters, no annotations) and the presence of an output schema, the description is incomplete. It fails to explain how the input 'input' works, the possible outputs, or any prerequisites.

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?

All 13 parameters have descriptions in the schema, so the description adds no additional meaning. The schema already covers semantics adequately, resulting in a baseline score of 3.

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 generates or regenerates textures for an existing model, which differentiates it from many sibling tools that handle other 3D operations. However, it could be more specific about the types of textures and what 'regenerate' entails.

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 like 'stylize' or 'image_to_3d'. With 30 sibling tools, the absence of usage context forces the agent to infer from names alone.

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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