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mcp-nfs-emissor

mcp-nfs-emissor

by fidsouzarv
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

Carregar CSV

carregar_csv
Read-only

Load a monthly Shopee CSV, filter valid orders with non-zero commission, and aggregate commissions per store ID to prepare for NFS-e issuance.

Instructions

Lê um CSV mensal da Shopee (respeitando aspas no campo Endereço do Vendedor), filtra pedidos com Status válido {Pendente, Concluído} e comissão ≠ 0, e AGREGA por ID da Loja somando a comissão. Retorna a lista de vendedores (uma futura NFS-e por loja) e as contagens do funil. NÃO emite nada.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "caminhoArquivo": "<caminhoArquivo>"
    },
    "name": "carregar_csv"
  }
}

Input Schema

NameRequiredDescriptionDefault
competenciaNoCompetência AAAA-MM (opcional).
caminhoArquivoYesCaminho do .csv em entradas/.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description confirms no emission, adding that it respects quotes in the address field, filters by status and commission, and aggregates. This provides useful behavioral context beyond the annotations, though it does not cover error conditions or file format details.

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?

The description is concise (two sentences) and front-loaded with the main action. It packs essential details without wordiness. Minor improvement could be clearer separation of input/output, but overall efficient.

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

Completeness4/5

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

Given the tool's complexity and the presence of full schema coverage and no output schema, the description covers the primary behavior, processing logic, and return values. It could mention error handling or format validation, but for a read-only data loading tool, it is sufficiently complete.

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 100% with descriptions for both parameters. The tool description does not add significant meaning beyond the schema; it mentions the month concept but does not directly link to the 'competencia' parameter. Baseline of 3 is appropriate.

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 reads a monthly CSV from Shopee, applies specific filters (valid status and non-zero commission), aggregates by store ID, and returns the list of sellers and funnel counts. It explicitly distinguishes itself from siblings by emphasizing it does not emit anything, making its purpose clear and unique among the sibling tools.

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?

The description implies the tool is used to load CSV data before emission, but it does not explicitly state when to use it versus alternatives, nor does it provide exclusions. The context from sibling tools helps, but the description itself lacks direct guidance on usage scenarios.

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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