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Gachi Data API — Japan Station & Accessibility Data

get_public_toilet_by_city

Read-onlyIdempotent

List public toilets in a Japanese municipality, with wheelchair / baby-seat / ostomate flags, address and coordinates. Covers 612 municipalities nationwide (large cities capped at the top 50 results). Municipality names accept Japanese (e.g. 那覇市, 渋谷区); prefixing the prefecture improves accuracy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesMunicipality name in Japanese (e.g. 那覇市, 渋谷区, 上天草市). Prefix the prefecture for accuracy.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoResolved municipality.
noteNoHuman-readable note.
countNoToilets returned.
errorNoSet when nothing was found.
toiletsNoPublic toilets with wheelchair / baby-seat / ostomate flags, address and coordinates.
attributionNoData source(s), license and provenance — an object, or an array of sources.

TDQS

A4.5/5.0
Behavior5/5

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

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. Beyond that, the description discloses important behavioral details: nationwide coverage of 612 municipalities, a cap of 50 results for large cities, and locale-specific input handling. These add meaningful context and are consistent with annotations.

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 tight sentences that front-load the primary purpose and then efficiently cover important scope and usage details. Every sentence provides value, with zero 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 read-only tool with an output schema and rich annotations, the description is complete. It covers the resource, return fields, geographical scope, result limits, and input-language nuance. No return-format explanation is needed because the output schema exists.

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 description for 'city' already covers the meaning, examples, and the prefecture-prefix tip, so the tool description largely repeats this information. It adds no new parameter-level semantic detail beyond what the schema provides, so baseline 3 is appropriate.

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 action and resource: 'List public toilets in a Japanese municipality' and enumerates the data returned (wheelchair / baby-seat / ostomate flags, address, coordinates). It distinguishes from sibling get_toilet_by_station by focusing on municipality-level 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?

The description gives clear context for when to use the tool (municipality-level query) and practical guidance on input format ('Municipality names accept Japanese... prefixing the prefecture improves accuracy'). It does not explicitly name alternatives such as get_toilet_by_station, but the city versus station distinction is implicit.

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

A4.3/5.0
Disambiguation3/5

Several tools overlap in function: get_active_alerts and get_station_alerts both return the same JMA alerts but with different input types, and get_municipality_context and get_station_context provide identical municipality data. However, the descriptions clarify the input differences, and other tools like get_toilet_by_city vs get_toilet_by_station are distinct enough.

Naming Consistency4/5

Most tools follow a consistent 'get_<noun>' pattern (get_active_alerts, get_municipality_context), but 'ping' and 'station_search' deviate from this convention. Still, the naming is largely predictable and readable.

Tool Count5/5

With 10 tools, the server is well-scoped for its purpose of station and accessibility data. Each tool serves a distinct function within the domain, and the count is within the ideal 3-15 range.

Completeness4/5

The tool surface covers the core workflows: discovery (station_search), station details (context, hazard, toilet), live alerts, and train status. Minor gaps exist such as the lack of a direct station info tool or the mention of 'search_ramen' which is not actually provided, but these are not critical.