Pre-check an e-invoice (XRechnung UBL or CII XML) against the priority EN 16931 / XRechnung rules incl. cent-exact totals recalculation. Findings carry official rule IDs. A pre-check, not the official KoSIT validation. 10 credits, requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| xml | Yes | Invoice XML, max 2 MB |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the tool's non-official status, credit cost, API key requirement, and the nature of findings (with rule IDs). This goes beyond the schema and gives essential operational context, though it does not detail the exact output structure or error handling.
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?
The description is two sentences, front-loaded with purpose, and includes critical extras (credits, API key, official status) without any fluff. Every word earns its place, achieving high information density in a compact form.
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?
The tool has one parameter and no output schema, so the description must explain results. It mentions findings with rule IDs, which gives a useful hint. The description is largely complete for a validation tool, though a brief mention of the output format or success/failure behavior would make it more complete.
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 coverage is 100% because the only parameter (xml) is described. The description adds value by specifying the accepted formats (UBL or CII XML), which is beyond the schema's simple 'Invoice XML' description. No additional parameter detail is needed.
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?
The description clearly states the tool's action: pre-checking an e-invoice against specific rules. It names the resource (XRechnung UBL or CII XML) and distinguishes itself from siblings (extract_invoice, generate_xrechnung) by emphasizing it is a validation/pre-check tool.
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 gives clear context: it is a pre-check, not the official KoSIT validation. It also mentions credits and API key requirements, implying usage requires authorization. However, it does not explicitly name alternative tools for when one should not use this tool, despite having relevant siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: extraction, generation, and validation of e-invoices. There is no overlap in functionality, making it easy for an agent to select the right tool.
All tool names follow the verb_noun pattern (extract_invoice, generate_xrechnung, validate_invoice), which is consistent and predictable. The naming clearly indicates the action and the object.
With 3 tools, the server is well-scoped for its purpose of processing e-invoices. The count is neither too thin nor too heavy, covering the essential operations without redundancy.
The tool set covers the full lifecycle of e-invoice processing: creation (generate), extraction (extract), and validation (validate). There are no obvious dead ends or missing critical operations for the stated domain.