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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds valuable behavioral context beyond annotations: payment model (prepaid credit), legal data control (LGPD), and confirmation that data is not confidential. This enriches the agent's understanding without contradiction.

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 compact paragraph, conveying all essential context without redundancy. While it includes legal disclaimers (LGPD), these are relevant to data handling and are not excessive. It is well-structured and front-loaded with the core purpose.

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?

With five undocumented parameters and no output schema, the description must compensate by explaining input/output behavior, pagination, or result format. It fails to do so, leaving significant gaps for an AI agent. The legal and payment context is helpful but does not address the operational details needed for correct invocation.

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 (query, pagina, processo, tipo_pesquisa, interessado_remetente). With a high parameter count and no documentation, the agent has no guidance on required formats, semantics, or relationships, making this dimension critically deficient.

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 consults CADE processes from official Brazilian sources, using a specific verb ('consulta') and resource ('Processos'). It distinguishes itself from sibling utilities by specifying the domain and official nature, leaving no ambiguity about its function.

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 for use: it queries official data, requires prepaid credit, and does not need platform credentials. However, it does not explicitly mention when to avoid this tool or suggest alternatives, though the sibling list (authenticate, marketplace, etc.) makes its niche apparent. No exclusions are stated, so it falls short of a 5.

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