toolforte

VAT Number Format Check

check_vat_number_format

Read-onlyIdempotent

Check the format of an EU/GB/CH VAT number (syntax only, no VIES registration lookup). Supported country prefixes: AT, BE, BG, CY, CZ, DE, DK, EE, EL, ES, FI, FR, HR, HU, IE, IT, LT, LU, LV, MT, NL, PL, PT, RO, SE, SI, SK, GB, CH.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`vatNumber`	Yes	VAT number, e.g. NL123456789B01

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No
`input`	No
`result`	No	The result, when it is not an object
`country`	No
`normalized`	No
`validFormat`	No

Schema Changelog

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

Changed1 schema field changedSep 5, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "country": {
+      "type": "string"
+    },
+    "input": {
+      "type": "string"
+    },
+    "normalized": {
+      "type": "string"
+    },
+    "note": {
+      "type": "string"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "validFormat": {
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds meaningful behavioral context by stating the check is syntax-only and does no VIES lookup, and by listing the supported country prefixes. No contradictions with annotations were found.

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?

Two sentences carry all essential information: the operation, the limitation, and the full supported-prefix list. Nothing is wasted, and the key boundary (no VIES lookup) 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?

For a simple one-parameter, read-only validation tool with full schema coverage and an output schema present, the description is complete. It provides the scope, constraints, and supported values an agent needs to invoke the tool correctly.

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?

The schema fully documents the vatNumber parameter with an example, so the baseline is 3. The description adds useful context about accepted country prefixes but does not provide additional format-level details beyond what the schema example already shows.

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 states a specific verb and resource: checking the format of EU/GB/CH VAT numbers. It clearly distinguishes itself from a VIES registration lookup and enumerates supported country prefixes, making its scope unambiguous relative to siblings like validate_email and calculate_vat.

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?

The description explicitly limits the tool to syntax-only validation and notes that it does not perform VIES registration lookup, giving clear guidance on what it should and should not be used for. It does not explicitly name alternative tools, but the context is sufficient for an agent to choose correctly.

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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TDQS

A3.8/5.0

Disambiguation5/5

Every tool targets a distinct resource or action, and the detailed descriptions clearly separate near neighbors like generate_test_bsn versus generate_brp_test_data, read_page versus url_screenshot versus url_to_pdf, and image_compress/convert/resize. Even with 40 tools, there is no real boundary-blurring overlap.

Naming Consistency3/5

All names are snake_case and readable, but the set mixes conventions: verb_noun (generate_*, validate_*), noun_verb (pdf_merge, image_resize), conversion-style names (csv_to_json, html_to_pdf), and bare nouns (base64, qr_code_png). The groups are recognizable, but there is no single predictable pattern.

Tool Count2/5

Forty tools is an oversized surface for an agent to consider on every call, well above the point where tool selection cost starts to hurt. The broad purpose explains the count, but many one-off utilities could be grouped or exposed selectively.

Completeness3/5

The server covers many domains—encoding, Dutch test data, image/PDF handling, memory, and workflows—but several categories are partial: there are no reverse conversions like json_to_csv or html_to_markdown, no PDF text extraction, and no workflow create/update/delete tools. Agents can work around some gaps, but notable operations are missing.

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