download_generated_model

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

With no annotations provided, the description carries the burden of behavioral disclosure. It mentions downloading to a directory and optional validation, but does not clarify whether validation is destructive, if multiple downloads are allowed, or what side effects occur. This is adequate but not thorough.

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 structured with Args, is clear, and avoids redundancy. It could be slightly more concise, but the current length is appropriate. No unnecessary information.

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 or output schema, the description covers parameters but omits return value, error scenarios, and clarification of the optional validation step. It is adequate for a simple download but leaves gaps for an AI agent to fully understand behavior.

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%, so the description fully compensates by explaining each parameter: job_id (ID of completed job), provider (meshy or openscad), output_path (directory with default). This adds essential meaning beyond schema titles.

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 downloads a completed generated model and optionally validates it. It uses specific verbs and resource ('download completed generated model'), but does not explicitly distinguish from sibling tools like 'preview_generated_model' or 'download_model'.

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 usage by mentioning 'completed generated job' and requiring job_id. However, it does not provide explicit guidance on when to use this tool versus alternatives, such as when to preview instead of download, or prerequisites like ensuring job completion.

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