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

Annotations already mark the operation as readOnly, idempotent, and non-destructive. The description adds non-redundant transparency about payment, lack of platform credentials, the non-confidential public nature of the data, and LGPD controller responsibility. It does not describe failure modes or return format, but the annotation layer already covers the safety profile.

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 front-loaded with the core purpose and then gives compact operational and legal context. It is a few sentences long, but each clause contributes non-obvious information about credentials, pricing, data sensitivity, and LGPD obligations.

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 simple parameterized query, the description covers purpose, access, cost, and data confidentiality well. However, with no output schema, it does not describe the returned data or common input validation requirements, leaving a notable gap for an agent deciding whether the tool's result satisfies a request.

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 description provides no explanation of the three required parameters (cnpj_prestador, numero_nota, codigo_verificacao), their formats, or how they relate. With 0% schema description coverage, the description was expected to compensate, but it leaves the parameter semantics entirely to the schema property names.

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 NFS-e information from the official Prefeitura SP Araçariguama source. It uses a specific action (consulta) and resource (NFS-e), and it is easily differentiated from the generic sibling tools like connect, marketplace, and report_bug.

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 gives clear operational context: the tool is an official-source lookup, needs no platform credentials, and is billed per query with prepaid credit. It does not explicitly name alternatives or exclusions, but the context makes the intended use case clear enough.

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