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by io.github.rwaldman

luhn_validate

Run the Luhn checksum on a numeric string such as a payment-card-like identifier to verify the check digit before accepting or storing the value.

Use when:

  • Does this number pass a Luhn check?

  • Validate a payment-card-like identifier checksum

  • Verify a numeric ID that uses a Luhn check digit

Do not use when:

  • Charge a card, tokenize payments, or call a payment processor

  • Validate ISBNs (use isbn_validate) or UUIDs (use uuid_validate)

  • Look up currency metadata (use currency_lookup)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYesNumeric string to validate with Luhn

TDQS

A4.4/5.0
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 of behavioral disclosure. It clarifies that the tool is a pure validation step ('before accepting or storing the value'), implying no mutation or external side effects. However, it does not explicitly state the return type or how errors are handled, leaving a minor gap for a simple checksum function.

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?

The description is concise and well-structured: a leading sentence explains the core function, followed by bulleted use/do-not-use lists. Every sentence provides actionable guidance, and there is no redundant or vague wording.

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?

For a single-parameter validator with no output schema, the description covers purpose, usage context, and exclusions comprehensively. The only missing piece is an explicit statement of the return value (e.g., true/false), which would strengthen completeness given the absence of an output schema.

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 100% with one parameter 'value' described as 'Numeric string to validate with Luhn'. The description adds context about payment-card-like identifiers but does not introduce additional format requirements (e.g., digits only, length limits). Since the schema already documents the parameter adequately, the baseline of 3 applies.

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 uses a specific verb ('Run the Luhn checksum') and resource ('numeric string such as a payment-card-like identifier') and explains the purpose ('verify the check digit before accepting or storing the value'). It clearly distinguishes this tool from sibling validators like isbn_validate and uuid_validate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'Use when' and 'Do not use when' sections, naming alternative tools (isbn_validate, uuid_validate, currency_lookup) and excluding payment processing actions. This gives an agent unambiguous context for when to invoke this tool versus alternatives.

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

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct resource and action, with clear use cases and explicit 'Do not use when' guidance preventing confusion. For example, base64_decode and url_decode handle different encoding schemes, while timestamp_convert and timezone_convert address separate time operations.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern (e.g., base64_decode, country_lookup, uuid_validate). While verbs vary (decode, encode, lookup, validate, convert), the naming format is uniform and predictable.

Tool Count4/5

The 18-tool set is slightly above the typical 3-15 range, but the breadth is justified by the server's purpose as a general-purpose utility toolkit. Each tool earns its place, and the count does not feel overwhelming or redundant.

Completeness4/5

The toolkit covers encoding/decoding, validation, lookups, and conversions across common developer needs. Minor gaps exist, such as no UUID generation tool to complement uuid_validate, and no HTML entity encoding/decoding, but these are not critical omissions for the stated utility scope.

Resources