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cmendezs

mcp-facturacion-electronica-es

es__generate_qr_verifactu

Generate the mandatory VERI*FACTU QR code (HAC/1177/2024) as a base64 PNG, encoding the AEAT verification URL for Spanish electronic invoices.

Instructions

Genera el código QR obligatorio VERI*FACTU (HAC/1177/2024 Art. 10) como PNG en base64. Encodes la URL de verificación de la AEAT: https://www2.agenciatributaria.gob.es/wlpl/TIKE-CONT/ValidarQR?...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nifYesNIF del emisor.
invoice_numberYesNumSerieFactura.
invoice_dateYesFechaExpedicionFactura en YYYY-MM-DD.
total_amountYesImporteTotal de la factura (con IVA incluido).
size_pxNoTamaño del QR en píxeles (por defecto: 200).
Behavior3/5

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

With no annotations, the description bears the full burden. It states that the tool generates a QR code as base64 PNG and encodes a URL, but it does not disclose whether it is a pure function with no side effects, its idempotency, or any limitations (e.g., output format details). The truncation of the URL reduces transparency.

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?

The description is extremely concise with two sentences, front-loading the core purpose and output format. Every word serves a purpose, making it efficient for an AI agent to parse quickly.

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?

While the description covers the basic purpose and output, it lacks details about the return format (base64 string is mentioned but not explained), the exact URL structure, and whether any side effects or network calls occur. For a tool with no output schema, this is adequate but not comprehensive.

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 input schema has 100% coverage with clear descriptions for all 5 parameters. The description adds minimal extra meaning beyond the schema, only noting that the output encodes the verification URL. This meets the baseline for high coverage.

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 identifies the tool's purpose: generating the mandatory VERI*FACTU QR code as a base64 PNG encoding a specific AEAT verification URL. It is distinct from sibling tools like es__generate_verifactu_record and es__submit_verifactu_to_aeat, which handle record generation or submission.

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 when a VERI*FACTU QR code is needed, but it does not explicitly state when to use it versus alternatives, nor does it provide any prerequisites or exclusion criteria. Context signals show sibling tools for related tasks, but no guidance is given.

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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