Dataset lookup

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds the meaningful constraint that only 'published' datasets are returned, but it says nothing about authorization scope or behavior for unpublished/nonexistent datasets. A 3 reflects modest added value over the annotations.

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?

One compact sentence, front-loaded with the returned attributes, with no redundant or filler text. Every word carries information.

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 an output schema present, the description need not explain return values, and annotations cover safety semantics, so a short scope statement is nearly sufficient. It could still note lookup-by-domain+table behavior or failure behavior, which is the only gap.

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% – both domain and table are documented with examples in the schema. The description adds no additional parameter meaning (e.g., format constraints or domain scoping rules), so the schema does the heavy lifting and the baseline 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 description names the concrete return payload (schema, ownership, policy tags) and scopes it to 'one published dataset', so the agent knows exactly what it retrieves. It does not, however, distinguish itself from siblings such as find_datasets or resolve_lf_tag, which a reader must infer.

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?

There is no statement of when to use this tool versus alternatives like find_datasets (search) or list_domains. The phrase 'one published dataset' hints at a targeted lookup, but no exclusions or prerequisites are given.

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