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Torify — Japan Locale APIs for AI Agents

Japanese Corporate Number Lookup

houjin.lookup
Read-onlyIdempotent

Look up Japanese corporate number (法人番号, 13 digits) → company name, address, kind, and status via NTA official API. 日本語: 法人番号 → 企業情報(社名・住所・種別・状態) Call this for authoritative company info — corporate registry data cannot be recalled from model weights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberYes法人番号(13桁の数字、例: 7000012050002)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo法人種別
nameYes法人名
nameEnNo法人名(英語)
sourceYesデータソース
statusYes法人状態
addressYes住所
nameKanaNo法人名(フリガナ)
lastUpdatedNo最終更新日
houjinBangouYes法人番号(13桁)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds that the tool uses the NTA official API (external dependency) and provides authoritative data not available from model weights, enriching the behavioral context 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 extremely concise: two sentences plus a bold usage note. Front-loaded with action and output, then critical guidance. No redundancy or filler.

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?

For a single-parameter lookup tool with full schema coverage, annotations, and an output schema, the description fully covers the purpose, source, and usage context. It explains the output fields and warns about model weight limitations, making it complete.

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% with a Japanese description of the number parameter. The tool description adds the English equivalent ('13 digits') and reinforces the format, providing extra clarity for bilingual users beyond the schema alone.

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?

Description clearly states the tool looks up a Japanese corporate number (13 digits) and returns company name, address, kind, and status via the official NTA API. It distinguishes itself from siblings like company.fullProfile by focusing specifically on corporate number lookups.

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

Usage Guidelines4/5

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

The description explicitly says 'Call this for authoritative company info' and warns that corporate registry data cannot be recalled from model weights, providing clear when-to-use guidance. It does not explicitly mention alternatives but the purpose is sufficiently distinct.

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.