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

With no annotations, the description carries the full burden. It discloses the analysis scope (geometry-only, uncapped), accepted formats, URL handling (including zip unpacking first model), the base64 truncation caveat, and the local-file upload workaround. It does not mention response format or rate limits, but for a read-only analysis tool this is solid disclosure.

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 dense paragraph, front-loaded with the purpose and metrics. It includes practical usage details without unnecessary fluff. Slightly repetitive with the schema's model_url description, but overall every sentence earns its place.

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?

Given no output schema and no annotations, the description does well to explain what analysis outputs (metrics), input sources, fallback options, and limitations. It lacks an explicit summary of the return format or error behavior, but the listed metrics and scope make the tool's functionality reasonably complete for an agent to use.

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?

The input schema already has 100% property descriptions, so the baseline is 3. The description adds meaningful value by marking model_url as 'PREFERRED', explaining the base64 fallback size limit and truncation risk, and noting that filename is required with base64. This goes beyond what the schema provides.

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 uses a specific verb ('analyze') and resource ('3D model'), lists concrete metrics (bounding box, volume, triangle count, watertight/manifold, solidity), and explicitly distinguishes itself from printing-specific tools by emphasizing 'beyond 3D printing' and use cases like game-asset QC and AR/VR optimization. This clearly separates it from siblings like check_printability and validate_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?

The description gives clear guidance on when to use the tool ('useful BEYOND 3D printing') and lists specific use cases and accepted input types (URLs, zip files, direct links, etc.). However, it does not explicitly name alternative tools or state when NOT to use it, though the 'beyond printing' framing implies a distinction.

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