dropcoin-invoice

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

With no annotations provided, the description carries the full burden. It discloses cost (5 credits), authentication requirement (API key), accepted input formats, and behavior for PDFs (embedded XML is pulled from the PDF). This provides meaningful behavioral context beyond the schema, though it does not cover failure modes or output format details.

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 concise sentences that pack substantial information: purpose, accepted inputs, output type, parameter exclusivity, cost, and auth requirement. There is no filler or unnecessary repetition of schema content.

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?

For a tool with two parameters and no output schema, the description covers the essential context: what it does, what inputs it accepts, how it processes PDFs, and usage constraints. It does not describe error handling or sample response structure, but the output is clearly summarized as structured JSON with specified fields, making the description largely 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 description coverage is only 50%; the xml parameter has no schema description. The description compensates by explaining that xml represents XRechnung UBL/CII XML and pdfBase64 is for ZUGFeRD/Factur-X PDF, and by enforcing the mutual exclusivity constraint. The pdfBase64 max size is already in the schema, but the format mapping adds value.

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 uses a specific verb ('Extract') and a clear resource ('structured JSON... from an e-invoice'), listing concrete data components (parties, lines, totals, payment data). It also differentiates itself from siblings by focusing on extraction rather than generation or validation.

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 clearly indicates when to use the tool: when you need to extract data from an XRechnung XML or ZUGFeRD/Factur-X PDF. It also states the critical usage constraint 'Send exactly one of xml / pdfBase64.' However, it does not explicitly mention when not to use it or compare to the sibling tools by name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden. It discloses that totals, VAT, and rounding are computed server-side, plus credit cost and API key requirement. It does not mention output format or error handling, but the given behavioral details are valuable.

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: first states purpose, second lists mandatory inputs and cost. Every sentence adds value, front-loaded with the core action, and there is no redundant content.

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?

Given the tool's complexity (10 params, nested objects, no output schema), the description covers purpose, required fields, key subfields, server-side computation, and cost/auth. It could additionally mention the output format or optional parameters, but it is still sufficient for an agent to select and invoke the tool correctly.

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 low (20%, only issueDate and buyerReference descriptions). The description compensates by specifying mandatory fields and breaking down subfields for lines (name, quantity, unitPrice, vatRate) and sellerContact (name/phone/email), which is not present in the schema.

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 a specific verb 'Generate' with a specific resource 'German XRechnung 3.0 e-invoice' and format details (UBL 2.1, EN 16931). It distinguishes from siblings 'extract_invoice' and 'validate_invoice' by implying a creation action.

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 clearly implies the tool is for creating an XRechnung from JSON, contrasting with extraction and validation siblings. While it doesn't explicitly name alternatives or exclusions, the context is strong enough that a user would know when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.