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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds context beyond those annotations by indicating the result scope (dataset counts and portal pages) and the data source, which helps an agent understand what to expect from the call. No contradiction exists.

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, front-loaded sentence that wastes no words. It states the operation, the target entities, the scope, and the output content efficiently.

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 rich annotations, a fully documented parameter schema, and a description that specifies return content, the tool is largely complete for correct invocation. It could improve by mentioning pagination behavior or explicitly routing to sibling search tools, but nothing critical is missing.

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%, with page, query, and page_size each documented. The tool description does not add parameter-level detail beyond the schema, but because the schema is complete, this is acceptable and matches the 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?

The description uses a specific verb ('List or search') and clearly identifies the resource: organizations publishing open data on dados.gov.pt. It differentiates from dataset-focused sibling tools by emphasizing organizational scope and enumerates returned content (dataset counts, portal pages).

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 makes its subject clear, so an agent can infer it is the right tool for organizational lookups rather than dataset searches. However, it does not explicitly mention sibling alternatives like search_datasets or state when not to use this tool, leaving usage guidance implicit.

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