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

With no annotations provided, the description carries the transparency burden. It discloses important behavioral details: the URL is SSRF-checked, downloads are capped at 10MB, the first row is the header, and special columns are recognized. It does not describe error handling or response formats, but it covers key operational constraints well.

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 concise and front-loaded. The first sentence states the core purpose, and each subsequent sentence adds essential operational detail without unnecessary 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?

Despite no annotations or output schema, the description provides solid contextual coverage: when to use it, URL requirements, size limits, CSV header behavior, and special column handling. It could mention auth expectations or failure modes, but it is sufficient for an agent to correctly select and invoke the tool.

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 coverage is only 33%, but the description adds significant semantics beyond the schema: it explains the URL must be public http(s), that the server fetches the CSV directly, and that expected_output/actual_output columns have special treatment. It does not elaborate on 'name' or 'tag_names', but those are largely inferable from context.

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's purpose: 'Create a dataset by downloading CSV from a URL instead of inlining it.' This uses a specific verb and resource, and explicitly contrasts with the inline creation approach, effectively distinguishing it from sibling datasets_create.

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 gives explicit guidance: 'Use this for large datasets' and contrasts with 'instead of inlining it,' which points toward the alternative tool. It clearly conveys the intended use case, though it does not explicitly name the sibling tool or state when *not* to use this tool.

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