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Torify — Japan Locale APIs for AI Agents

by dev.torify

Japan Address Geocoder

geo.geocode
Read-onlyIdempotent

Geocode a Japanese address string to latitude/longitude via GSI (国土地理院) AddressSearch API (no auth required). Address format only — landmark names and station names are not supported. 日本語: 住所形式のみ対応・ランドマーク名・駅名は非対応 Call this for real coordinates of a Japanese address — do not estimate lat/lng from memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesJapanese address string in address format (e.g. 東京都千代田区丸の内一丁目). Landmark/station names (e.g. 東京駅) are not supported. / 住所形式（例: 東京都千代田区丸の内一丁目）。ランドマーク名・駅名は非対応

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes緯度
lngYes経度
titleYes正規化住所
sourceYesデータソース
addressCodeYes住所コード

TDQS

A4.5/5.0
Behavior5/5

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

The description adds that no authentication is required, specifies the API source (GSI AddressSearch), and indicates output is lat/lng. These details go beyond annotations (readOnlyHint, openWorldHint, idempotentHint) and provide useful behavioral context for the agent.

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 with two sentences plus a bold callout, front-loading the key action and constraints. The Japanese translation 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?

For a simple geocoding tool with an output schema (not shown), the description covers input format, API source, auth, and usage guidance comprehensively. No gaps remain.

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?

The schema already covers the single parameter 'q' with a detailed description including format example, so the description adds reinforcement but no new syntactic information. Baseline 3 is appropriate due to high schema coverage.

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 geocodes Japanese addresses to lat/lng via a specific API, and explicitly excludes landmarks/stations. This distinguishes it from sibling tools like reverseGeocode or postal.lookup.

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?

It provides explicit guidance: call this for real coordinates, do not estimate from memory, and notes that only address format works. However, it does not explicitly mention when to use alternatives, leaving room for improvement.

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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