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consultar_aliquota_icms

Calculate ICMS interstate rates and DIFAL for NF-e between Brazilian states. Provide UF origin and destination to obtain the applicable rate per EC 87/2015 and Senate Resolution 22/1989.

Instructions

Consulta as alíquotas do ICMS para operações interestaduais entre contribuintes. Purpose: calcular o DIFAL (Diferencial de Alíquota) e a alíquota interestadual aplicável na emissão de NF-e, conforme EC 87/2015 e Res. Senado Federal nº 22/1989. Quando usar: ao emitir NF-e interestadual, calcular DIFAL ou verificar a carga tributária de operações entre estados. Comportamento offline: calcula a partir de tabelas em memória; não requer conexão. NOTA: não cobre a alíquota de 4% para bens importados (Resolução SF 13/2012). Parâmetros: siglas de UF em maiúsculo (ex: 'SP', 'MG', 'RJ').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uf_origemYesSigla da UF de origem (ex.: "SP", "MG", "GO").
uf_destinoYesSigla da UF de destino (ex.: "RJ", "BA", "CE").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.5.1

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well by disclosing offline behavior (in-memory tables, no connection) and a specific limitation (missing 4% import rate). It does not mention error handling or edge cases, but the output schema covers return structure, so this is sufficient.

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

Conciseness5/5

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

The description is well-structured with clear sections: purpose, usage, behavior, note, and parameter guidance. Every sentence provides necessary information without redundancy, and the core purpose is front-loaded.

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

Completeness5/5

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

Given the tool's simplicity and that an output schema exists, the description covers all necessary aspects: purpose, when to use, behavior, limitations, and parameter formatting. It is fully self-contained for an agent to invoke correctly.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by specifying that UF abbreviations must be uppercase (ex: 'SP', 'MG', 'RJ'), which is not explicit in the schema. This helps prevent invalid input.

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

Purpose5/5

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

The description clearly states the tool consults ICMS rates for interstate operations between taxpayers, explicitly naming the resource and scope. It distinguishes from siblings like consultar_aliquotas_importacao by specifying interestadual operations and DIFAL calculation.

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

Usage Guidelines5/5

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

It provides explicit when-to-use conditions: emitting interstate NF-e, calculating DIFAL, or checking tax burden between states. It also notes exclusions, such as not covering the 4% rate for imported goods, which guides against misuse.

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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