feedback-quality

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

With no annotations, the description carries the full burden, but it only adds 'read-only' and a list of metric areas. It does not disclose behavior around validation gates, export profile checks, budgets, LOD rules, or what the tool returns. This is minimal transparency for a complex analysis tool.

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, front-loaded sentence with a clear metric list and a read-only qualifier. Every word earns its place, and there is no fluff or repetition.

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?

Despite high complexity (18 parameters, no output schema, no annotations), the description provides only a high-level overview. It omits how the many validation parameters are used, what the output format will be, and how this relates to sibling tools like feedback-readiness or io-profile_validate.

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 0% across 18 parameters, and the description does not compensate by explaining any of them. It only names high-level metric categories; the 18 parameters dealing with budgets, LOD ratios, export profiles, collision requirements, and validation gates are entirely unaddressed.

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 provides objective quality metrics for a mesh, listing specific metric categories (topology, UVs, orientation, symmetry, proportion, scale, readiness). It is more specific than the tool name and broadly distinguishes from visual feedback siblings like feedback-capture or feedback-lookdev, though it does not explicitly name alternatives.

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?

No guidance is provided for when to use this tool versus the many related feedback-* and io-profile_validate siblings. The description implies it is for objective mesh quality measurement, but there are no explicit usage conditions, exclusions, or alternative recommendations.

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