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

Annotations only mark readOnlyHint false and destructiveHint false; the description adds genuinely useful behavioral context: the operation is paid and priced by model size, it creates a new version rather than overwriting, it is asynchronous (poll get_lowpoly_job), and only one job per model is allowed at a time. It does not cover error/failure conditions, but the added disclosures are substantial.

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 four short sentences with no filler. Cost, core action, output behavior, and concurrency constraint are all front-loaded, and every sentence adds information the agent needs.

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?

For an async, paid, side-effectful operation, the description covers the critical non-obvious facts: polling, per-model concurrency, and version creation. The output schema and complete parameter schema are present, so return values and parameters are handled. The main gap is explicit routing among the many start_lowpoly_* siblings.

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 100%, so the schema carries the parameter documentation burden and the baseline is 3. The description adds little param-specific meaning beyond context like 'one job per model,' which touches asset_id indirectly. It does not need to compensate for schema gaps because there are none.

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 and resource: 'Change an existing Low-Poly model,' which clearly sets this apart from creation tools like start_lowpoly_generate. The outcome 'saved as a new version' further pins down its purpose as a revision operation, not an animation, split, or rerig.

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 phrase 'existing Low-Poly model' and 'saved as a new version' imply the revision use case, and 'Poll get_lowpoly_job(task_id)' gives the correct follow-up. However, it does not explicitly say when to use this over sibling tools like recolor_lowpoly_model, start_lowpoly_rerig, or start_lowpoly_generate, nor does it state exclusions.

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