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Torify — Japan Locale APIs for AI Agents

Company Full Profile (Corporate + Invoice) [Torify namespace — official]

torify_company.fullProfile
Read-onlyIdempotent

One-call composite: 13-digit corporate number (法人番号) → company name, address, kind, status (NTA 法人番号 API) + optional invoice registration check (NTA 適格請求書 API). 日本語: 法人番号 1 つで法人情報とインボイス登録状態を同時取得。Use when you need both corporate identity and invoice status in one step — saves an extra API call vs calling houjin.lookup + invoice.verify separately. Note: government agencies (e.g. NTA itself) often return invoiceStatus.registered=false — this is correct per Japanese tax law. [Torify namespace — official]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberYes法人番号(13桁の数字、例: 1180301018771)
verify_invoiceNotrue のとき対応するT番号(T+法人番号)のインボイス登録状態も確認する(デフォルト: false)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo法人種別
nameYes法人名
nameEnNo法人名(英語)
statusYes法人状態
addressYes住所
sourcesYesデータソース一覧
nameKanaNo法人名(フリガナ)
confidenceYes信頼度スコア(0〜0.99)
verified_atYes確認日時(ISO 8601)
houjinBangouYes法人番号(13桁)
invoiceStatusNoインボイス登録状態(verify_invoice=true のときのみ)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

The description adds valuable behavioral context beyond annotations: it notes the correct behavior for government agencies regarding invoice status. Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and the description complements without contradiction.

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, placing the core purpose first, followed by usage guidance and a special note. Every sentence adds value without redundancy.

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 composite nature of the tool, the description covers the key aspects: input requirements, output components, optionality, and a tax-law nuance. Combined with annotations and output schema, it provides a complete picture.

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?

Schema coverage is 100%, providing baseline 3. The description adds meaning by clarifying the 'number' parameter as '13-digit corporate number' and the 'verify_invoice' parameter as 'optional invoice registration check', slightly enhancing understanding beyond schema.

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's purpose: combining corporate profile lookup and optional invoice verification in one call. It explicitly mentions the data sources (NTA APIs) and distinguishes itself from sibling tools like houjin.lookup and invoice.verify.

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 advises when to use this tool ('when you need both corporate identity and invoice status in one step') and highlights the efficiency gain over separate calls. It also provides a caveat about government agencies, offering clear guidance.

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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