kaggle_download_dataset

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

Annotations provide readOnlyHint=false and destructiveHint=false, but the description adds valuable behavioral context: 'isolated work dir', 'zip auto-extracted with a zip-slip guard', and 'Returns local paths + metadata'. No contradictions with annotations.

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?

Single sentence, front-loaded with the essential action and key details. No extraneous 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 the presence of an output schema (not shown), the description covers the main purpose and safety behavior. However, it omits details about the isolated work dir's lifetime and cleanup, which could be relevant for usage.

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 must compensate. It hints at 'single file' (file param) and 'zip auto-extracted' (unzip param), but does not explicitly explain each parameter's purpose or constraints. Minimal meaning added beyond schema field names.

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 verb 'Download', the resource 'dataset (or single file)', and key actions like auto-extraction and zip-slip guard, distinguishing it from sibling tools like kaggle_download_competition_files.

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 for downloading datasets but does not explicitly state when to use this tool versus alternatives like kaggle_download_competition_files or kaggle_download_model. No exclusions or when-not guidance is provided.

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