Get a dataset's distributions

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds useful extras beyond those: distributions each have their own format, licence, and download URL, licences can differ within a dataset, and the agent should read the licence field before reuse. It also reveals consistency with get_dataset. It does not go further into rate limits or error behavior, but the annotations lower that burden.

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 front-loaded with the main action, then uses a short positioning sentence, a licence caveat, a sibling note, and a compact Args list. Every sentence contributes either selection guidance, parameter semantics, or a behavioral warning; there is no low-value filler.

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 two-parameter read-only retrieval tool with an output schema, the description supplies the missing context: what a distribution contains, the licence warning, the source of dataset_id, the meaning of language, and the relationship to get_dataset. An agent has enough to decide when to call it and how to invoke it correctly.

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?

With 0% schema description coverage, the Args section carries the semantic load and succeeds: dataset_id is explained as coming from search_catalog or list_datasets, and language is defined as controlling titles and descriptions. This meaningfully compensates for the schema's absent descriptions and complements the enum/pattern constraints already present.

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 opens with a specific verb and resource: 'Get the downloadable files and access URLs for a dataset.' It also differentiates itself from the close sibling get_dataset by noting that get_dataset returns the same distributions 'alongside the rest of the record,' so an agent can distinguish the two without inspecting schemas.

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 frames the tool as 'the «where do I actually get the data» tool' and names get_dataset as the alternative that returns these distributions with the full record, giving clear selection context. It does not, however, state an explicit when-to-use/when-not-to-use rule such as 'use this when you only need distributions; use get_dataset when you need the full record.'

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