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

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to restate safety. It adds value by listing exactly what the read returns, which goes beyond the annotation metadata and helps the agent set expectations for the response.

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 a single, efficient sentence that front-loads the action and resource, then concisely lists the content areas returned. Every phrase earns its place and there is no redundant 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?

Given the tool is a simple single-parameter read operation with a full output schema and strong annotations, the description is largely complete. It could slightly improve by mentioning that the slug should come from list_datasets, but that is a minor gap and likely inferable from the sibling tool set.

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 only parameter, slug, is already fully documented in the schema with a minLength and an example, so schema description coverage is 100%. The tool description adds no new meaning about slug beyond implying it identifies the dataset, which is the expected baseline when the schema carries the parameter details.

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?

Description clearly states the verb 'Read' plus the resource 'one dataset' and enumerates the returned content: description, contents, full column schema, method notes, FAQs, and download URL. This distinguishes get_dataset from list_datasets and other get_* siblings because it is explicitly about fetching a single dataset's full record.

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 makes the basic use case obvious: use this when you need the full details of one known dataset. However, it does not mention when not to use it or point to alternatives like list_datasets for discovering dataset slugs, so selection guidance is mostly implied rather than explicit.

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