generate_3d_model

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

No annotations provided, so description carries full burden. Discloses that the initial output is a 'preview' and needs refinement for production-quality, implying a two-step generation process. Also states return formats (download links, thumbnail, video). Does not discuss rate limits or auth, but for a generation tool this is adequate.

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

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

Concise and well-structured: opens with purpose, lists return formats, enumerates use cases, and ends with workflow guidance. Every sentence adds value, no fluff.

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

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

Covers the main generation flow and output format but omits detailed behavior of 7 out of 8 parameters. No output schema and no annotations. The description is adequate for a high-level understanding but incomplete for full parameter guidance.

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

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

Schema description coverage is only 13% (only prompt has a description). Description adds value for prompt (specificity, example) but does not explain other parameters (art_style, negative_prompt, ai_model, topology, target_polycount, seed, wait_for_completion). With low coverage, description fails to compensate for missing parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 text using Meshy AI. Lists specific output formats (GLB, FBX, OBJ, USDZ, thumbnail, video) and diverse use cases (e-commerce, games, architecture). Distinguishes from sibling tools by mentioning refine_3d_model and add_texture as follow-up steps.

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

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

Provides explicit follow-up workflow: call refine_3d_model for production quality or add_texture for custom textures. Lists use cases to guide when to use. Does not explicitly mention when not to use, but the sibling differentiation is strong.

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