Validates a 10- or 13-character ISBN. ISBN-10 uses weights 10..1 over 10 characters (last may be X, worth 10), sum mod 11 must be 0. ISBN-13 uses the same GTIN checksum as barcodes.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | identifier or value to check |
| Name | Required | Description | Default |
|---|---|---|---|
| valid | Yes | ||
| reason | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility. It discloses the checksum algorithms (ISBN-10 weights and modulo check, ISBN-13 GTIN check), which adds behavioral context beyond the schema. However, it does not mention error handling (e.g., what happens with non-numeric characters or incorrect length), return format, or side effects (though the tool is likely read-only). The presence of an output schema mitigates the need for return details, but lack of error behavior clarity leaves gaps.
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 extremely concise: two sentences. The first sentence states the core purpose, and the second provides the relevant algorithmic detail. No extraneous words, and all content is valuable. Information is front-loaded, making it easy for an agent to parse quickly.
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 a single parameter with full schema coverage and the existence of an output schema (so return values are covered elsewhere), the description is nearly complete. It explains the validation logic in detail. A minor gap is lack of specification on whether hyphens or case variations (e.g., lowercase 'x') are accepted, but the algorithm description implicitly assumes pure digit/X strings. Overall, it provides sufficient context for a validation tool.
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 input schema describes 'value' as an 'identifier or value to check' with 100% coverage. The description significantly enhances this by specifying that the value must be a 10- or 13-character ISBN, and explains the weighting and modulo logic. This adds critical validation constraints beyond the schema's generic string description.
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 explicitly states 'Validates a 10- or 13-character ISBN' with a specific verb (validates) and resource (ISBN), making the tool's purpose immediately clear. It also provides algorithmic details that distinguish it from sibling validation tools for other identifiers (EAN, IBAN, etc.).
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?
Usage is implied through the name and description but not explicitly stated. There is no 'when to use this vs alternatives' guidance, no exclusion criteria for invalid formats (e.g., hyphens), and no reference to sibling tools. The algorithm details provide enough context for an agent to infer the tool is for ISBN numbers, but explicit guidance is missing.
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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Each tool validates a completely distinct type of identifier (barcodes, IBANs, ISBNs, Luhn-based numbers, SWIFT/BIC codes, and EU VAT numbers). There is no overlap in purpose, and descriptions clearly differentiate the specific format and algorithm used.
All six tools follow an identical naming pattern: the lowercase identifier name followed by '_validate'. This consistent noun_verb structure makes it easy for an agent to predict the tool name for any identifier type.
With six tools covering the most common checksum-based identifiers (barcodes, IBANs, ISBNs, payment cards, SWIFT/BIC, EU VAT), the server is well-scoped. Each tool serves a clear purpose without unnecessary redundancy or excessive complexity.
The tool set covers the major standardized identifiers that rely on checksums or structural validation. While additional identifiers like VIN or SSN could be added, the current selection represents a natural and comprehensive set for a 'Checksum Validator' server.