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

The annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior. The description adds useful context beyond annotations by explaining that candidates are declared coverage, not verified matches, and that downstream filters are not inferable from the original request.

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 front-loaded with the core purpose, followed by an important caveat about candidate quality and a concise next-step instruction. Every sentence carries useful information without repetition.

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?

For a two-parameter search tool with full schema coverage and rich annotations, the description provides the key caveat and follow-up path an agent needs. It does not describe result shape or pagination, but with no output schema this is a minor gap rather than a blocking omission.

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%, so both parameters are already documented. The description adds some meaning to the query parameter by giving examples of keywords or short task descriptions, but it does not explain the optional country parameter or add syntax 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: finding candidate DataScoop datasets from keywords or a task description. It also clarifies that results reflect declared coverage rather than verified matches. It is clear, but it does not explicitly distinguish itself from the sibling list_datasets tool.

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 gives a clear follow-up workflow: call get_dataset_schema, then query_dataset with explicit filters. It also warns that example filters are not inferred from the request. It does not state when not to use this tool or compare it directly with list_datasets.

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