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Emendas parlamentares do Brasil

ranking_municipios

Ranking dos municípios que mais receberam emendas, no Brasil ou numa UF, por valor total e por habitante (municípios acima de 50 mil habitantes). Requer token pago.

Input Schema

NameRequiredDescriptionDefault
ufNoSigla da UF (ex.: SP) ou BR para o Brasil
tokenYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does disclose two important traits: the paid-token requirement and the 50k-population cutoff that silently excludes smaller municipalities. It says nothing about sorting direction, result limits, pagination, or what happens when an invalid UF or unpaid token is supplied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense sentence with the resource and the ranking criteria front-loaded and the token prerequisite at the end, so nothing feels padded. The population threshold is buried mid-sentence as a parenthetical, which slightly weakens scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter, read-only ranking tool with no output schema, the description conveys what is ranked and by which metrics, which is the essential context. It still leaves the shape of the returned ranking and its ordering unspecified, so an agent cannot predict the response structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%: the uf parameter is already documented in the schema as a UF abbreviation or BR for Brazil, and the description merely restates that scope. The undocumented token parameter is partly compensated by the sentence 'Requer token pago', which explains its purpose, but no format or acquisition path is given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and output: a ranking of municipalities that received the most emendas (amendments), nationally or within a UF, measured both by total value and per capita, restricted to municipalities above 50 thousand inhabitants. That is far more specific than the tool name alone and distinguishes it from siblings like resumo_municipio or buscar_municipio, though it does not explicitly contrast itself with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear prerequisite — a paid token is required — and explains that results can be scoped to Brazil or a single UF. It does not say when to prefer this ranking over the sibling tools buscar_municipio or resumo_municipio, so the routing decision is only implied.

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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