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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so safety is covered. The description adds valuable behavioral context by specifying the returned fields (dataset code, name, last updated) and hinting at extensibility with 'and others', which goes beyond the structured 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?

Two sentences, front-loaded with purpose and examples, then return fields and usage. Every clause earns its place with no filler.

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 simple read-only listing tool with one optional parameter and no output schema, the description covers purpose, usage context, return content, and is consistent with annotations. Nothing essential 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?

The schema description coverage is 100% for the single optional 'query' parameter, so the schema already explains it as a filter on dataset names. The description adds no parameter-specific information beyond the schema, so 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 opens with a specific verb ('List') and a clear resource ('WHO Regional Office for Europe data collections'), enumerates concrete examples (HFA, mortality database, ENHIS, etc.), and differentiates from sibling tools like who_euro_countries and who_euro_search_measures by focusing on dataset discovery.

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 provides an explicit when-to-use statement: 'Use to see what European health data collections exist before searching indicators.' It does not name alternatives or give when-not-to-use conditions, but the context is clear enough to guide an agent.

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