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

Annotations already convey readOnly, idempotent, open-world, and non-destructive behavior. The description adds useful additions: it specifies the INE data source, the measured metric, the returned period/source/license, and the exclusion set. No contradiction with 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?

Three short sentences, each earning their place: core purpose, exclusions, and required parameters. The key information is front-loaded and there is 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?

The tool is simple and safely annotated, and the description covers purpose, output metadata, exclusions, and required inputs. Minor omissions like alternative routing and explicit locale behavior are not significant enough to lower the score further.

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 0%, so the description must compensate; it does so partly by stating that both district and municipality are required slugs. The locale parameter is left to its enum/default in the schema, which is sufficient, and the slug pattern is clarified by the word 'slugs' plus the schema pattern.

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 names a specific verb ('Read'), resource ('INE median completed dwelling sale value per m2'), and scope ('Portuguese municipality'), plus the returned metadata. The negative clause ('Not asking prices, rents, a valuation or forecast') further disambiguates it from property-focused siblings like get_property and search_properties.

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?

It gives clear context: use this for municipal median sale statistics, not for asking prices, rents, valuations, or forecasts. It does not explicitly name a sibling tool as the alternative, so routing between tools is implied rather than explicit.

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