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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable behavioral context beyond annotations: the caveat about CID-9 derived data for 1992–1997, the non-comparability of groups g03 and g05, the nominal currency of 'value', and the default universe (csapaih) that excludes obstetric procedures, childbirth, and long-stay admissions. These are important data behaviors an agent should know.

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 concise, with the main purpose stated in the first sentence and caveats following. It is not overly verbose and front-loads the core function. The structure is logical: purpose, capability, then data caveats. It could be slightly more streamlined, but it is appropriately sized for the tool's complexity.

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 8 optional parameters, an output schema, and the annotations cover safety, the description is fairly complete. It explains the ranking criteria, the data caveats, and the default universe. It does not explicitly mention the output format (e.g., a table), but the presence of an output schema likely covers that. The description is sufficient for an agent to call the tool correctly, though it could mention potential edge cases or the direction of ranking (e.g., descending).

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 baseline is 3. The description does add some context, such as the meaning of the 'value' metric being nominal and the explanation of the 'universe' parameter's default behavior. However, it does not delve into other parameters like 'uf', 'sex', 'year', or 'limit' beyond what the schema already states. The added value is marginal, keeping the score at 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 states a clear verb ('Gera ranking') and resource ('dos 19 grupos CSAP'), and specifies the ranking criteria (number of hospitalizations, days, or value). It also adds an additional capability ('Identifica principais causas evitáveis'). The purpose is unambiguous and distinct from sibling tools like list_csap_groups or get_icsap, which focus on listing or retrieving data rather than ranking.

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 does not explicitly state when to use this tool versus alternatives or when not to use it. It provides context about the default universe and data caveats, but these are behavioral notes, not usage guidance. An agent might infer the use case from the name, but the description lacks explicit direction on when to prefer this over get_icsap or compare_icsap_trends.

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