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refine_3d_model

Convert a preview 3D model into a production-ready asset with high polygon detail and PBR textures for game engines and AR.

Instructions

Refine a preview 3D model to production quality using Meshy AI.

Run this after generate_3d_model to get: • Higher polygon detail • PBR texture maps (base color, metallic, roughness, normal) • Production-ready GLB/FBX/OBJ files suitable for Unreal Engine, Unity, Blender, Three.js, or AR

Requires a completed preview task ID from generate_3d_model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
preview_task_idYes
texture_richnessNohigh
enable_pbrNo
wait_for_completionNo
Behavior3/5

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

No annotations provided, so description bears full burden. It discloses outputs (GLB/FBX/OBJ, PBR maps) and the prerequisite, but does not reveal potential behavioral traits like processing time, cost implications, or whether the original preview is affected.

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 front-loaded with the core statement, then uses bullet points for benefits, and concludes with a requirement. It is efficient but could be slightly more concise by integrating the parameter explanation.

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?

Given the tool has 4 parameters and no output schema or annotations, the description provides adequate context for basic usage but lacks depth on parameter behavior, error handling, and output specifics beyond file types.

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%. The description only explains the preview_task_id parameter; texture_richness, enable_pbr, and wait_for_completion are left undefined. Though parameter names are self-explanatory, the description should clarify their role, especially given the lack of schema descriptions.

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 clearly states the verb 'refine' and resource 'preview 3D model', distinguishing it from generate_3d_model and siblings like add_texture. It specifies the outcome: production quality with higher detail and PBR maps.

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?

Explicitly states 'Run this after generate_3d_model' and requires a completed preview task ID. Provides context on when to use, but does not mention when not to use or alternative tools like add_texture.

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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