download_kaggle_dataset

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

With no annotations, the description carries the full burden and does disclose key behavioral traits: use of kagglehub, copying CSVs into datasets/, and authentication requirements. It does not mention overwrite behavior or error handling, but the main side effects are clearly stated.

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, front-loading the main action and then adding necessary prerequisites and an example. Every sentence serves a purpose with no fluff.

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 the tool's simplicity (one parameter) and the presence of an output schema, the description covers everything essential: purpose, side effect, authentication, and input format. Minor details like non-CSV handling are implicit in the phrase 'copy any CSVs', so no critical gaps remain.

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?

The input schema has no descriptions for the single 'dataset' parameter, so the description compensates by providing an example slug ('yasserh/titanic-dataset'), which clarifies the expected format. This gives meaningful guidance beyond the schema's bare parameter name.

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 dataset from Kaggle via kagglehub and copies CSVs into datasets/, using a specific verb and resource. It implicitly distinguishes from siblings like list_datasets and profile_dataset by focusing on the actual download and file-copy action.

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?

It provides clear context that Kaggle authentication is required and gives an example dataset slug format, helping the agent understand prerequisites and input format. However, it does not explicitly mention when to use this tool versus alternatives, though the purpose is obvious.

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