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Render e-invoice as HTML

render_invoice_html

Human-readable invoice document (HTML, A4 print layout) from the XML, in the requested language.

Input Schema

NameRequiredDescriptionDefault
langNoLabel language, default en
contentNoInvoice XML (UBL, CII, XRechnung, Peppol BIS, ZUGFeRD/Factur-X XML, KSeF FA(3)) as text
content_base64NoA ZUGFeRD / Factur-X PDF (or any invoice file) as base64, when the invoice is not plain XML

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / lang / enum
      Previous value: -[
      -  "en",
      -  "de",
      -  "fr",
      -  "pl",
      -  "nl",
      -  "hr"
      -]New value: +[
      +  "en",
      +  "de",
      +  "fr",
      +  "pl",
      +  "nl",
      +  "hr",
      +  "es"
      +]
  2. Changed1 schema field changed
    • changedInput schema / properties / lang / enum
      Previous value: -[
      -  "en",
      -  "de",
      -  "fr",
      -  "pl",
      -  "nl"
      -]New value: +[
      +  "en",
      +  "de",
      +  "fr",
      +  "pl",
      +  "nl",
      +  "hr"
      +]
  3. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that the output is a human-readable HTML A4 document and that language is selectable, but says nothing about whether the operation is side-effect-free, deterministic, or how large/multi-page invoices are handled. Adequate but incomplete for an unannotated tool.

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?

A single front-loaded sentence with no filler; the output format and language qualifier are the most decision-relevant facts and come first. Nothing is wasted.

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

Completeness3/5

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

No output schema exists, and the description does cover the return type (HTML document), which is the main thing. However, required parameters is 0 while the tool needs either content or content_base64 to function; the description never states this mutual dependency, leaving a real gap for correct 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%, so the schema already documents lang, content, and content_base64 fully; the baseline is 3. The phrase 'in the requested language' only echoes the lang parameter and adds no format or default detail beyond the schema's 'default en'.

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

Purpose4/5

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

The description states the resource (human-readable invoice document) and the output format (HTML, A4 print layout) produced from XML, which clearly separates it from the sibling render_invoice_pdf. The verb is implicit rather than stated ('Render' only appears in the name/title), so it falls just short of a fully self-contained verb+resource statement.

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?

Usage is only implied: an agent can infer 'use this when you want an HTML/A4 rendering of an invoice'. No explicit when-to-use, when-not-to-use, or named alternative (e.g. render_invoice_pdf) is given, so the routing decision is left to inference.

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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