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

With no annotations provided, the description carries the transparency burden and discloses key side effects: uploaded GLB is immutable, published edits go to the review queue, and the live version remains until approval. It does not mention auth failures, rate limits, or other error conditions, but the core behavior is well covered.

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 two concise sentences with no filler or redundancy. It efficiently communicates the main action and the most important constraints.

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?

The description provides enough context for an agent to understand the main workflow, including the review queue behavior for published assets. It does not explicitly state whether unspecified fields are left unchanged or describe the return value, but these are not blocking gaps.

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 only 25%, and the description does little to explain individual parameters beyond their generic names. aiModel and category have some schema-level descriptions, but tags, summary, description, aiGenerated, and slug are left largely to inference.

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 a distinct operation: editing metadata of the user's own assets. It also differentiates the tool by emphasizing that the GLB cannot be changed and that published edits go through review, which helps separate it from upload/create tools.

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 implies when to use this tool: for metadata-only edits. It also provides an important exclusion by stating the GLB can never be changed, though it does not explicitly name sibling tools such as submit_asset_from_url for comparison.

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