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Torify — Japan Locale APIs for AI Agents

by dev.torify

Invoice Number Format Validator [Torify namespace — official]

torify_invoice.validate
Read-onlyIdempotent

Validate Japanese qualified invoice number (T-number) format and check digit. T + 13 digits. 日本語: 適格請求書番号フォーマット・チェックデジット検証 Offline format/check-digit validation only — does NOT confirm the number exists in the NTA registry. To verify real registration, use invoice.verify. [Torify namespace — official]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberYesインボイス番号（例: T7000012050002）

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo番号種別
inputYes入力値
validYesフォーマットおよびチェックデジットが正しいか
formatYesバリデーション結果コード
checkDigitNoチェックデジット詳細
houjinBangouNoT を除いた13桁の法人番号部分

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds critical context: it performs offline validation only and does not confirm existence in the NTA registry. This avoids misinterpretation of the tool's scope.

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 two sentences, front-loaded with English, and includes a Japanese translation for completeness. No filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, clear purpose, and an output schema not shown but present), the description covers all necessary context: format, validation scope, and distinction from a sibling tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'number' has a description in the schema (example in Japanese), but the tool description adds the format 'T + 13 digits' and mentions check digit validation, adding meaning beyond the schema's example.

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 clearly states the tool validates Japanese qualified invoice number format and check digit, specifying the pattern 'T + 13 digits'. It further distinguishes from the sibling tool 'invoice.verify' by noting it does not check NTA registry existence.

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 explicitly states when to use this tool (offline format/check-digit validation) and when not to (use invoice.verify for real registration check). This provides clear guidance on 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

A3.7/5.0
Disambiguation1/5

The tool set contains exact duplicates for 10 tools (e.g., company.fullProfile and torify_company.fullProfile). An agent cannot distinguish between them, leading to confusion and potential misselection. The purpose of having both namespaced and non-namespaced versions is unclear.

Naming Consistency2/5

Naming is inconsistent: some tools use a dot-separated namespace (e.g., company.fullProfile), while others have a prefix (torify_company.fullProfile). Some tools lack the prefix (e.g., geo.geocode) while their duplicates have it (torify_geo.geocode). No consistent verb_noun pattern; naming conventions are mixed.

Tool Count2/5

With 24 tools, the count is high, and half are duplicates. The effective unique tool count is 12, which is reasonable for the domain, but the duplication inflates the count unnecessarily, making the surface seem bloated and confusing.

Completeness4/5

The tool set covers key Japanese locale operations: corporate lookup, invoice validation/verification, geocoding, postal lookup, name romanization, kanji conversion, law search, and wareki conversion. However, there are no tools for updating or deleting data, which is expected since these are read-only or verification APIs. Minor gaps like missing station/landmark geocoding are noted but acceptable.

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