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

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the safety profile is free. The description adds two things the annotations do not: a deterministic ordering (newest first) and a hard output obligation — carry the returned notice and source line into any answer, plus the disclaimer that results are not tax/legal/investment advice. That is real behavioral context.

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 substantive content (versions, ordering, fields) is correctly front-loaded, but every sentence is stated two or three times — Chinese, English, then the disclaimer repeated in both — roughly tripling the length without adding information. A bilingual audience justifies some duplication, not this much.

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 no output schema, the description carries the burden of describing results, and it does list the returned fields and their ordering. It stays vague on the actual shape (what a 'column' entry looks like, whether version lists are bounded), which is a minor gap for a one-parameter read 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 100% and the single parameter's schema text already explains that the id comes from list_datasets and supplies two worked examples. The description adds nothing on top of that, so the baseline of 3 applies.

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 opening clause states a concrete resource and scope — one dataset plus all of its versions, newest first — and enumerates the payload (date, row count, columns, content hash). That is enough for an agent to distinguish it from get_dataset_rows (rows) and list_datasets (the catalogue) even though those siblings are never named.

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?

Usage is only implied: you call it to inspect a dataset's version history. The description never states when to prefer this over get_dataset_rows or list_datasets, and gives no prerequisites or exclusions. An agent must infer the routing from the return-value summary alone.

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