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

With no annotations, the description carries the full burden. It discloses the data source (NPPES registry crossed with Census) and the ranking methodology (deficit vs metro area, poverty, geographic isolation, federal HPSA). However, it does not specify the response format, the definition of 'casi cero', or potential edge cases like empty results, leaving some behavioral ambiguity.

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 two sentences, tightly packed with key information: what is returned, how it is ordered, and the data provenance. No filler or repetition; the unique-dataset claim is the only slightly promotional element but still informative.

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 tool with two parameters, no output schema, and no annotations, the description explains the core function and sorting logic. However, it leaves out expected output fields (e.g., municipality name, risk score, provider counts) and does not clarify the threshold for 'casi cero', making it less complete for an agent trying to interpret results.

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 input schema already provides descriptions for both parameters (especialidad and limite), covering 100% of the schema. The description adds no additional parameter-level detail beyond the title's mention of 'por especialidad', so it does not exceed 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 clearly states the tool returns municipalities in Puerto Rico with zero or near-zero providers of a medical specialty, sorted by a specific risk score rather than alphabetically. This specific content and the 'único dataset de este tipo para PR' claim distinguish it clearly from sibling tools like buscar_negocio or eventos_proximos.

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 the tool is for finding medical specialty deserts in Puerto Rico but provides no explicit guidance on when to use it versus alternatives. Sibling tools cover different domains (business search, recalls, citable data, local demand, events), so the use case is contextually distinct, but no exclusions or alternatives are named.

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