model_download

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

Annotations declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, so the description carries some burden. The description adds useful behavioral context: it downloads a file to a local path, and the filename parameter description explains the selection behavior ('Omit to prefer best.pt, then the first available file'). However, it doesn't disclose what happens if the file already exists without overwrite=true, or whether the download is resumable. The overwrite parameter is documented in the schema, so the description doesn't need to repeat it. The description adds value beyond annotations by clarifying the file selection behavior.

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 sentence that front-loads the core action (download weight file to local path) and then lists the accepted reference formats. Every word earns its place. The filename parameter description is also concise and informative. 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?

For a download tool with 5 parameters, 100% schema coverage, and no output schema, the description is fairly complete. It explains the reference formats, the filename selection behavior, and the local destination. The main gap is that it doesn't state what happens on overwrite=false when the file exists, but that's a minor edge case. The tool is a straightforward file download, and the description covers the essential decision points.

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 already documents all 5 parameters. The description adds value by clarifying the relationship between model, project, and filename: it explains that slug requires project, and that filename does not set the local output filename. This goes beyond the schema descriptions. However, the description doesn't add much beyond what the schema already provides for output_path and overwrite. Baseline 3 for high coverage, plus the added clarification about slug/project and filename behavior, justifies a 4.

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 states a specific verb ('Download'), a specific resource ('a trained model's weight file'), and the destination ('to an explicit local path'). It also enumerates the three accepted reference formats (owner/project/model, ul:// URI, or slug with a project), which distinguishes it from sibling tools like models_get or model_predict. This is a clear, specific statement of what the tool does.

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: when you need to download a model's weight file to a local path. It does not explicitly name alternatives or state when not to use it, but the context of sibling tools (models_get, model_predict, model_plots) makes the use case fairly clear. The description could be improved by explicitly saying 'use models_get to inspect model metadata instead' or similar, but the core usage context is present.

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