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

Annotations already signal safe read-only/idempotent behavior; the description adds non-obvious behaviors: rendering multiple angles, returning image frames plus a human-readable geometric summary, and accepting any public https .glb. No contradiction with annotations.

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?

The description is a single informative paragraph that front-loads the core value ('See a 3D model') and packs output, scope, and workflow into useful clauses. It is slightly wordy but every sentence contributes functional guidance.

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?

Combined with the rich schema, the description covers what the tool returns (frames, geometry, plain-language analysis), when to use it, and its input constraint (public https .glb). Without an output schema, this is sufficient for an agent to invoke and interpret the result; failure/error behavior is not described but is not critical for a read-only tool.

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?

All three params (glb_url, size, views) are fully described in the schema with defaults and enum options, so the description need not restate them. It only adds contextual examples rather than new parameter meaning, matching the baseline for high schema coverage.

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?

The description names a concrete action ('see/look at'), specifies the resource (a GLB via URL), and clarifies its purpose as visual/geometric inspection of generated models. This sets it apart from generation/modification siblings like mesh_forge and refine_model.

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?

It gives a clear usage window ('right after generating') and a concrete QA workflow ('is subject complete, is back finished... then regenerate naming the fault'), but it does not name alternative tools or explicit when-not-to-use cases.

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