szamlazz_check_taxpayerLook up a Hungarian taxpayer in the NAV register by the first 8 digits of the tax number (the törzsszám): whether the number is valid, the taxpayer's name, VAT status and addresses. Számla Agent action-szamla_agent_taxpayer (data from the NAV Online Invoice platform).
| Name | Required | Description | Default |
|---|---|---|---|
| tax_number | Yes | The first 8 digits of the Hungarian tax number, e.g. 13421739. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description reinforces the safe-read nature while adding context the annotations cannot: the data originates from the NAV Online Invoice platform and the underlying Számla Agent action (action-szamla_agent_taxpayer). It does not cover failure behavior (does an unregistered number return a flag or an error?) or any rate limits.
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?
Two sentences, front-loaded with the operation and its return fields before the implementation detail. The trailing mention of the Számla Agent action name is marginally useful for traceability but is the least essential content.
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?
There is no output schema, so the description carries the burden of describing returns — and it does, naming validity, name, VAT status and addresses. It still omits what happens for an unknown tax number and whether all four fields are always returned, which is the one remaining gap for a lookup tool.
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?
Schema description coverage is 100% and the single parameter is fully documented (pattern ^\d{8}$, example given). The description adds only the Hungarian domain term 'törzsszám' for the same value, so it neither expands nor detracts from what the schema already carries — baseline 3.
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?
States a specific verb ('look up') and resource (a Hungarian taxpayer in the NAV register), and enumerates what the caller gets back: validity, name, VAT status and addresses. No sibling tool does anything remotely similar (all others are invoice/receipt operations), so it is trivially distinguishable.
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 makes the input constraint clear ('by the first 8 digits of the tax number') and identifies the data source, which implies the validation use case, but it never states when to reach for this tool versus something else or what to do when a number is not found. Usage is inferable rather than stated.
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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