Banco Central do Brasil (BCB): Cotações, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| data | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful context beyond that: no credentials needed, cost model (prepaid credit per query), data classification (non-confidential), and LGPD compliance responsibilities. These operational details help the agent set expectations.
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, front-loads the core purpose, and uses three additional sentences to add operational and legal context. The LGPD disclaimer could be considered slightly superfluous but does not harm clarity.
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?
Despite having a simple signature (one optional string parameter, no output schema), the description omits any explanation of the parameter's meaning or expected input. This is a critical gap that prevents an agent from invoking the tool correctly. The legal and payment details don't address invocation requirements.
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 has one parameter ('data') with 0% description coverage, and the description gives no explanation of what 'data' means or how to format it. With no parameter documentation, the description fails to compensate for the schema's lack of semantic detail, leaving the agent unable to determine valid input.
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 queries official Banco Central do Brasil exchange rates ('Cotações, consulta em fonte oficial'), using a specific verb ('consultar') and resource. It also distinguishes itself from the generic platform sibling tools (authenticate, connect, marketplace, etc.) by focusing on BCB data.
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 operational context: it queries an official source, requires no platform credentials, and is paid per query with prepaid credit. This helps an agent understand when to use it, though it doesn't explicitly mention when not to use it or name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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