ENTIA Entity Verification

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

Annotations already provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable context about the data source being official government data (not scraped/estimated), the time coverage (2009-2026), and data volume (40.3 million acts from 3.4 million companies). This goes beyond what annotations provide without contradicting them.

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 efficiently structured with three focused sentences: first states purpose and scope, second lists return fields, third clarifies data source and quality. Every sentence adds value with zero wasted words, and key information is front-loaded.

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, 100% schema coverage, and an output schema exists, the description provides excellent context. It covers data source, time range, data volume, return fields, and data quality assurances, making it complete for this search tool without needing to explain return values.

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%, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline score of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

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 BORME registry for mercantile acts with specific verb ('Search') and resource ('BORME'). It distinguishes from siblings by specifying it returns comprehensive company data rather than focusing on specific act types like 'borme_new_constitutions' or verifying professionals like 'verify_dentist'.

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 clear context about the data source (official government data, 2009-2026 coverage, 40.3 million acts) which helps understand when to use it. However, it doesn't explicitly state when to choose this tool versus alternatives like 'search_entities' or 'entity_lookup' that might overlap in functionality.

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