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

The annotations already provide read-only, idempotent, and non-destructive signals, so the description only needs to add operational context. It adds clarity around immutable version_id, the meaning of publisher, and the precise boundary of the response, though it does not cover failure or auth behavior—minor for a metadata read.

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 dense and front-loads the output contents, then adds the publisher clarification, parameter example, and sibling routing. It is long but every sentence carries new information; a bullet list could improve scannability, but there is no real waste.

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?

There is no output schema, but the description enumerates the key response fields, names the excluded fields and where to get them, and explains how to use returned identifiers with downstream tools. For a single-parameter read operation, this is complete enough for an agent to invoke it successfully.

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 description must compensate for the single slug parameter. The concrete example, kden-metar-hourly, combined with the overview context, makes it clear that slug is the dataset identifier, though it does not fully explain where the slug comes from or how to resolve it.

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 exactly what this tool returns: an overview for one dataset, including tables and their key metadata, while explicitly excluding schema details. It clearly differentiates the tool from get_table_schema by naming which fields belong to that sibling, so an agent can select it without opening 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 gives explicit routing guidance: use get_table_schema when column types, descriptions, units, or published profiles are needed, and use the returned table id with get_table_schema, sample_rows, and query_table. It does not, however, explain when get_dataset should be chosen over the similarly named get_my_dataset or get_table siblings.

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