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einvoicewiz

validate_einvoice

Validate a Factur-X / ZUGFeRD / XRechnung file (PDF or XML, base64) against EN 16931 + KOSIT + PDF/A (1 credit).

Returns the rule-level report {result:{status, errors[], warnings[], profile}, verify, credits_left}.
verify is set only when the file passed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
file_base64Yes

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses the credit cost (1 credit), the response shape, and the conditional behavior that verify is only set when validation passes. It could additionally mention failure modes or encoding details, but the key side effects and conditional outputs are covered.

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 dense sentences, front-loaded with purpose, followed by a concise return value description. Every sentence earns its place and no filler exists.

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?

The tool has only two simple parameters and no output schema, so the description appropriately explains the return structure and conditional verify field. It lacks explicit mention of expected base64 formatting or error behavior, but is otherwise sufficient for an agent 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?

Schema coverage is 0%, so the description must compensate. It clarifies that file_base64 is a PDF or XML base64 payload, which adds real meaning. However, it does not explain the api_key parameter at all, though the name and common SDK conventions make it somewhat inferable.

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 states a specific action ('Validate'), the exact resource types (Factur-X / ZUGFeRD / XRechnung files in PDF or XML base64), and the standards applied (EN 16931 + KOSIT + PDF/A). This distinguishes it from sibling tools like create_facturx_pdf, generate_einvoice_xml, and check_credits.

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 when to use the tool: when an existing e-invoice file needs validation. However, it does not explicitly state when not to use it, nor does it reference alternatives like which_format_do_i_need or lookup_certificate for related but different tasks.

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

A3.9/5.0
Disambiguation5/5

Each tool covers a distinct operation: credits, signup, format advice, XML generation, PDF/Factur-X generation, validation, and certificate lookup. Even generate_einvoice_xml and create_facturx_pdf are clearly differentiated by output format, so an agent should not misselect.

Naming Consistency4/5

Most tools follow a lowercase snake_case verb_noun pattern like check_credits, generate_einvoice_xml, and validate_einvoice. The exceptions are signup (no underscore) and which_format_do_i_need (question-style phrase), which present minor but noticeable deviations.

Tool Count5/5

Seven tools is well-scoped for an e-invoice API: each covers a meaningful step in the user journey from signup and credit checking to format selection, generation, validation, and verification. No tool feels redundant or unnecessary.

Completeness5/5

The tool set provides a coherent end-to-end workflow: onboard with signup, check credits, determine the required format, generate XML or create a Factur-X PDF, validate the result, and look up verification certificates. There are no obvious dead ends for an agent attempting to produce and verify an e-invoice.

Resources