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Czech VAT (DPH) status check

check_vat

Authoritative plátce-DPH status from RZP register: payer yes/no, effective from, tax office, trade licences. Use before issuing/czech invoicing. Batch up to 20 IČOs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesIČOs or DIČs (CZ+10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  3. First observed

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description must carry the behavioral burden. It usefully notes the source is authoritative, enumerates the returned fields, and mentions batch capacity. However, it does not disclose potential failure modes, error behavior, or any limitations regarding invalid IČOs/DIČs, so the disclosure is only moderately complete.

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?

Three short sentences each add value: the data source/output, the use case, and the batch limit. The wording 'issuing/czech invoicing' is slightly awkward, but the description remains tight and readable.

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?

For a simple one-parameter lookup with no output schema, the description covers the essential context: source, output fields, intended use, and batch size. It lacks notes on error handling or authorization, but nothing critical is missing for basic invocation.

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 description coverage is 100% for the single parameter, which already explains 'IČOs or DIČs (CZ+10)'. The description repeats the batch limit already present as maxItems in the schema, adding no new parameter-level meaning beyond the schema.

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?

States a specific resource (RZP register), a concrete output set (payer yes/no, effective from, tax office, trade licences), and clearly differentiates from the sibling tools by focusing specifically on Czech VAT payer status rather than general entity lookup. Even the title adds a clarifying subclass ('Czech VAT (DPH) status check').

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

Usage Guidelines4/5

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

Gives explicit context for use: 'Use before issuing/czech invoicing.' This tells the agent when this lookup is relevant. It does not name alternative tools or state when not to use it, so it stops short of a 5, but the usage context is unambiguous.

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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