ENTIA Entity Verification

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, establishing this as a safe, repeatable read operation. The description adds valuable context about data scope (6 regions, 70K+ centers), specific regional coverage details, and official government data sources, which helps the agent understand result limitations and reliability.

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 appropriately sized and front-loaded with the core purpose. The regional breakdown with specific counts adds useful detail without being excessive. Every sentence contributes to understanding the tool's scope and data sources.

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?

Given the tool has comprehensive annotations (readOnly, non-destructive, idempotent), 100% schema coverage, and an output schema exists, the description provides excellent contextual completeness. It covers geographic scope, data sources, and scale, which are crucial for understanding what this search tool can and cannot do.

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?

With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description doesn't add parameter-specific information beyond what's in the schema, but it provides context about the data being searched (healthcare centers across specific Spanish regions) which helps interpret parameter values.

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 clearly states the tool searches Spain's official healthcare center registries, specifying the verb 'search' and resource 'healthcare centers'. It distinguishes from siblings by focusing on comprehensive healthcare facility data across multiple autonomous communities, unlike more specialized tools like search_dental_clinics_cataluna or search_pharmacies.

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 usage context by listing the 6 covered autonomous communities and data sources, suggesting this is the tool for broad healthcare center searches across those regions. However, it doesn't explicitly state when to use this versus alternatives like search_dental_clinics_cataluna or search_pharmacies, nor does it provide exclusion criteria.

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