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

Annotations already cover read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds useful context beyond annotations: it reads only the local catalog, has no upstream row counts or latest dates, and returns an error when the dataset_id does not exist.

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 English part is front-loaded and efficient, covering purpose, related parameters, scope, and error behavior in a few sentences. The description is doubled in Chinese, which is appropriate for a bilingual tool but reduces conciseness relative to a single-language equivalent.

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?

With one required parameter fully documented by the schema, an output schema present, and rich annotations, the description supplies the remaining context an agent needs: what is returned, how the returned field keys are used by dataset.get, that the catalog is local-only, and that missing IDs should be resolved via dataset.search.

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 100%, so the schema already documents the single dataset_id parameter with its origin and an example. The description reinforces that fields are keyed by the identifiers returned here and refers back to dataset.search for valid IDs, but it does not add syntax or format details beyond the schema.

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 a specific verb and resource: it shows one dataset's definition, including id, source, summary, tags, and field keys with Chinese descriptions. It distinguishes itself from siblings by noting that dataset.get's parameters use these field keys and that dataset.search should be used first when an id is missing.

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 clearly routes the agent: use dataset.search to find a dataset_id if it does not exist, and it distinguishes this metadata-only read from dataset.get by explaining that the returned field keys feed dataset.get's where, sort_by, fields, and match parameters. It also notes that it reads only the local catalog and has no row counts or dates, which implies when not to use it for data access, but it does not explicitly state to use dataset.get for data.

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