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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context: it's a paid service (prepaid credits), hosted by the platform (no platform credentials needed), and the data is not confidential (same as available to citizens). It also mentions LGPD compliance and data controller responsibilities, which is important behavioral context for a data query tool.

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 a single paragraph of three sentences, which is concise and front-loaded with the core purpose. It packs a lot of information efficiently, though it could be slightly more structured with bullet points for the payment and LGPD details. No wasted words.

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 5 parameters, no output schema, and no parameter documentation, the description should provide more guidance on how to use the tool. It covers the business context (payment, hosting, data source) but lacks technical usage details like parameter requirements or expected response format. The annotations help with safety, but the description doesn't fully compensate for the missing parameter semantics.

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%, and the description does not explain any of the five parameters (email, senha, tipo_login, pkcs12_cert, pkcs12_pass). The parameter names are in Portuguese and suggest authentication credentials, but the description doesn't clarify their roles, which ones are required, or how they relate to the login type. With zero coverage and no compensation, this is a significant gap.

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's purpose: 'Consulta de Informações da Conta' (Account Information Query) for Registradores (ARISP), consulting an official source. It distinguishes from siblings by specifying the domain (registradores) and the action (consult account info), though it doesn't explicitly contrast with other tools.

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: it's a paid query using prepaid credits, hosted by the platform, and intended for consulting official Brazilian sources. However, it doesn't explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites beyond the payment model.

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