crehq_dataset_categories

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

With no annotations, the description carries the full burden. It discloses that the tool returns categories with counts and presents itself as a 'quick map', indicating a lightweight read-only operation. It does not mention potential limitations like pagination, but for this simple listing tool it is adequately transparent.

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 a single sentence, front-loaded with the primary action ('List all dataset categories with counts'), and contains no redundant or filler text. Every word contributes to understanding.

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 zero-parameter, no-output-schema tool, the description provides a clear indication of what is returned (categories with counts) and context (organization across verticals). It could be more explicit about what counts represent, but overall it is sufficiently complete for the tool's simplicity.

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?

The tool has zero parameters, so schema coverage is effectively 100% and the baseline is 4. The description adds value by framing the output as a 'quick map' with counts, which clarifies the nature of the returned data beyond the empty 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 uses a specific verb "List" and resource "dataset categories" with counts, clearly distinguishing from sibling tools like crehq_datasets_list which list datasets themselves. The added context of a 'quick map' of organization across verticals further clarifies purpose.

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 implies use when needing a high-level overview of dataset categories rather than specific datasets or locations, but does not explicitly name alternatives or when-not-to-use scenarios. The 'quick map' phrasing gives clear context without formal exclusions.

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