WinkelFactuur

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

Annotations are empty, so the description carries the full burden of behavioral disclosure. It adds value by stating that category names must be Dutch, and it reveals an important fallback behavior: unknown or missing categories return a list of known categories and suggest a retry. This goes beyond what the input schema conveys.

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 compact and front-loaded: the first sentence states the core purpose, then the following sentences address category-language requirements and the unknown-category retry behavior. Every sentence earns its place with no filler or repetition.

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 low-complexity calculation tool with no output schema, the description explains the main return contents and the important edge-case behavior. It is complete enough for an agent to call the tool correctly, though it does not describe response format in detail.

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 100%, so the schema already explains all parameters clearly. The description reinforces that category values are Dutch, but it does not add material semantics beyond the schema for price, subcategory, or fulfilment_type.

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 ('Work out'), names the exact resource (bol.com sale commission), and lists the concrete outputs: commission percentage, fixed fee, and seller proceeds. This clearly distinguishes it from the sibling tools calculate_vat and validate_iban.

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 implies when to use the tool through its clear focus on bol.com commission, but it never explicitly states when to choose this tool over its siblings or when not to use it. It does provide indirect usage guidance by explaining how to handle unknown or missing categories.

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?

Even without annotations, the description reveals non-obvious behavior: rates follow the destination country, reverse charge depends on a VIES-valid buyer VAT number, and exports outside the EU are zero-rated. It also notes reduced rates when a category is supplied, giving an agent a solid model of how the calculation will behave.

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?

Two tight paragraphs with the core purpose and differentiating legal cases front-loaded. No filler or repetition of parameter names.

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 six-parameter tax calculation with no annotations and no output schema, the description provides most needed context: inputs, applicable rules, and special cases. The only notable gap is not describing the response shape (e.g., VAT amount vs. rate breakdown), but the tool's intent makes the output largely predictable.

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?

All six parameters are fully described in the input schema (100% coverage), so the description only needs to add value beyond that. It does by tying combinations of parameters to legal scenarios (OSS, reverse charge, exports) and noting that category selects reduced rates.

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 opens with a specific verb and resource ('Calculate EU VAT') and immediately narrows scope with 'destination-country principle' and 'cross-border or domestic sale.' It also enumerates distinct scenarios (OSS, B2B reverse charge, zero-rated exports), making it easy to distinguish from sibling tools like bol_commission and validate_iban.

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?

It gives clear invocation context: use for cross-border or domestic e-commerce sales subject to EU VAT, and it flags the edge cases where sellers commonly err. It does not explicitly say 'don't use for X' or name alternatives, but the sibling domains are so different that the absence of exclusions is not costly.

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, the description carries the behavioral burden. It clearly discloses what the tool does and does not check, including the structural scope and limitations. It stops short of describing the exact return format or error behavior, but 'report whether' gives a reasonable indication.

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 compact, front-loads the core purpose in the first sentence, and uses the second paragraph to add practical context and limitations. Every sentence contributes useful information with no redundancy.

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 simple one-parameter validation tool, the description covers what is validated, when to use it, and what it deliberately does not do. There is no output schema, so an explicit return contract would improve completeness, but 'report whether' is sufficient for an agent to invoke it 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?

The schema already provides 100% coverage for the single 'iban' parameter, including normalization behavior for spaces, dots, and dashes. The description adds only a minor clarification that IBAN is a bank account number, so the schema carries the semantic weight.

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 ('Validate') with a clear resource (IBAN) and defines exactly what validation covers: check digits and country-specific length. It clearly distinguishes this from the unrelated sibling tools (bol_commission, calculate_vat) and from account existence or ownership checks.

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?

It explicitly states when to use the tool: before sending a payment or invoice, to catch transposed or missing digits. It also gives an explicit when-not: it does not check whether the account exists or who owns it, which prevents misuse.

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