retopologize

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

No annotations exist, so description carries full burden. It discloses async nature and polling requirement, but omits details on destructive behavior, permissions, rate limits, or impact on original model.

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?

Three concise sentences front-load the purpose, deliver key options, and mention async nature. No redundant or irrelevant text.

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 6 parameters and async behavior, the description is minimal. It does not explain output (e.g., returns task ID), constraints (originalTaskId must be a generated model), or handling of partial failures.

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 coverage is 100% with parameter descriptions. The description adds context only for the quad parameter (supports quad or triangle). No additional meaning for other parameters like originalTaskId, targetFaces, etc.

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?

Description clearly states the tool creates a lowpoly version of a generated 3D model, specifies quad or triangle output, and highlights asynchronous behavior. It effectively distinguishes from siblings like refine_model or convert_format through the async context.

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?

Description mentions using task_status for polling but does not explicitly state when to use this tool over alternatives (e.g., refine_model, segment_mesh). No exclusions or prerequisite guidance provided.

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