list_datasets

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so safety is covered. The description adds only that filtering and count-capping are supported, and it does not explain what the result set looks like (names only? with attributes?) or how the 'server limit' truncation manifests.

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?

Two short sentences, front-loaded with the resource and the qualifier scoping, then the optional capabilities. Nothing is redundant, though the second sentence is a feature list rather than guidance.

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 should say what a returned dataset entry contains and how truncation/pagination surfaces, and it doesn't. It says enough to invoke the tool but leaves the result shape and any limit behavior implicit.

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%, and every parameter the description mentions (hlq, pattern, dsorg, maxResults) is documented in more detail in the schema, including the enum meanings. The description adds no syntax or interaction detail beyond that baseline.

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?

States a specific verb+resource (list catalog datasets) and the scoping mechanism (high-level qualifier plus optional pattern), which is more concrete than the bare name. It does not, however, distinguish itself from the sibling search_dataset, so an agent can't tell from the description which of the two to pick.

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 search_dataset, search_members, or get_dataset_info, and no prerequisites or exclusions. The only hint is that it enumerates by qualifier, which the reader must infer is the difference from the search tools.

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