MCP CNPJ Intelligence

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: returns active companies only, returns a list sorted by quantity (descending), and returns UF (state) codes with company counts. However, it doesn't mention potential limitations like data freshness, source constraints, or error conditions.

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 well-structured with clear sections (purpose, usage guidelines, return format). Each sentence adds value: the first states the core function, the second provides use cases, the third details the return format. No wasted words, and information is front-loaded appropriately.

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 zero-parameter tool with no output schema, the description provides good completeness: it explains what the tool does, when to use it, and what it returns. However, without annotations or output schema, it could benefit from more detail about return format (e.g., exact field names, data types) or any constraints on the data.

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 tool has 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist, earning a baseline 4. It focuses instead on what the tool returns and when to use it.

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: 'Retorna QUANTIDADE de empresas por estado brasileiro' (Returns QUANTITY of companies per Brazilian state). It specifies both the verb (returns) and resource (companies per state), and distinguishes itself from siblings like 'estatisticas_por_cnae' by focusing on state-level statistics rather than industry classification.

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 includes a 'QUANDO USAR' section with two clear use cases: market analysis by region and prioritizing states for expansion. This provides good contextual guidance, though it doesn't explicitly state when NOT to use this tool or name specific alternatives among siblings.

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