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Torify — Japan Locale APIs for AI Agents

by dev.torify

Invoice Number NTA Verification [Torify namespace — official]

torify_invoice.verify
Read-onlyIdempotent

Verify invoice number registration against NTA public registry API. Returns registrant name, address, and registration date. Requires INVOICE_APP_ID (free, apply via NTA). 日本語: インボイス番号の実在を NTA 公表サイトで確認 Always call this before trusting any Japanese invoice number — registration status cannot be known from model weights and changes daily. For offline format checks only, use invoice.validate. [Torify namespace — official]

Input Schema

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes入力値
sourceYesデータソース
cancelDateNo取消日（nullの場合は未取消）
disclaimerNo国税庁利用規約に基づく免責表示
registeredYes登録されているか
registrantNameNo登録事業者名
registrationDateNo登録日
registrantAddressNo登録事業者住所

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds requirement for INVOICE_APP_ID, which is important behavioral context for invoking the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is relatively compact with essential info including bilingual note. The final parenthetical '[Torify namespace — official]' could be redundant but does not significantly harm.

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?

Covers purpose, usage context, required credential, return data, and alternatives. With output schema present, return information is sufficient.

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% for the single 'number' parameter with example. Description does not add extra meaning beyond the schema, so 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?

Description states 'Verify invoice number registration against NTA public registry API' and specifies return data (registrant name, address, date). Distinguishes from sibling 'invoice.validate' for offline format checks.

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?

Explicitly says 'Always call this before trusting any Japanese invoice number' and explains why (status changes daily). Provides alternative tool for offline checks.

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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