grid_fill

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

With no annotations, the description discloses the return type as a confirmation dict and gives parameter ranges. Yet it lacks details about prerequisites (e.g., needing a closed edge loop selected), side effects, or required modes, making transparency moderate.

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 concise, with a clear front-loaded purpose, followed by a brief comparison and a well-structured argument list. Every sentence is necessary and efficient.

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 annotations and no output schema details (only mention of a confirmation dict), the description adequately covers the parameters but omits operation prerequisites and mode requirements. It is moderately complete for a tool with moderate complexity.

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 schema has 0% description coverage, so the description compensates by explaining each parameter: object_name as the mesh object, span as column count with range, offset as alignment offset with range. This adds substantial semantic value beyond the bare schema.

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 clearly states the tool fills a closed edge loop with a grid of quads, creating clean quad topology. It explicitly differentiates itself from the sibling fill_faces by claiming better topology maintenance.

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 provides a direct comparison to fill_faces, indicating when this tool is preferable for topology quality. However, it does not list other alternatives or specify when not to use it.

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