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get_station_alerts

Read-onlyIdempotent

Live JMA river flood forecasts and landslide alerts affecting a station's prefecture — NOT general weather warnings. Ask by station name in Japanese (新宿) or romaji (Shinjuku). Prefecture-level match (station master is Greater Tokyo). Relay of official JMA facts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
station_nameYesStation name in Japanese (新宿) or romaji (Shinjuku).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of alerts.
staleNoTrue if stale.
alertsNoJMA alerts affecting the prefecture.
stationNoResolved station.
disclaimerNoRelay disclaimer.
fetched_atNoWhen the snapshot was fetched.
attributionNoData source(s), license and provenance — an object, or an array of sources.

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds that it is a 'relay of official JMA facts' and that the match is prefecture-level. This adds some context but does not disclose behavioral traits beyond what annotations provide. Thus, baseline 3 is appropriate.

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 very concise: two sentences and a clarifying note. Front-loaded with key purpose, then input specifications. No wasted words.

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?

With one parameter, full schema coverage, and an output schema present, the description provides sufficient context: it explains what alerts are returned (floods and landslides), the matching method (prefecture-level), and a real-world example ('station master is Greater Tokyo'). Complete for the complexity.

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% for the single parameter, so the schema already documents it. The description adds value by specifying the accepted formats ('Japanese (新宿) or romaji (Shinjuku)') and explaining the prefecture-level match. This goes beyond the schema's description.

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 provides 'Live JMA river flood forecasts and landslide alerts' and explicitly distinguishes from 'general weather warnings'. It specifies input format (station name in Japanese or romaji) and scope (prefecture-level). This is a specific verb+resource with clear differentiation.

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 clearly indicates when NOT to use it (not for general weather warnings) and provides context for use ('Ask by station name... Prefecture-level match'). However, it does not explicitly mention alternatives like get_active_alerts or get_station_hazard, so it lacks explicit exclusion 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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TDQS

A4.1/5.0
Disambiguation2/5

Several tools have overlapping purposes: get_active_alerts and get_station_alerts both return JMA flood/landslide alerts, differing only by input type. Similarly, get_municipality_context and get_station_context expose the same underlying data via different resolvers, and get_station_context already includes hazard categories that get_station_hazard duplicates in more detail. These overlaps make it difficult for an agent to know which tool to select for a given query.

Naming Consistency4/5

Most tools follow a clear 'get_' prefix (e.g., get_toilet_by_station, get_train_status), which is consistent. However, 'station_search' and 'ping' break the pattern, and the role-split text references a non-existent 'search_ramen' tool. The dominant convention is clear, but the exceptions introduce minor inconsistency.

Tool Count4/5

With 10 tools, the count is within a reasonable range for the server's broad scope (station info, toilet accessibility, hazards, alerts, train status). However, the redundancy between municipality_context/station_context and actives_alerts/station_alerts means not every tool earns a unique place, making the set slightly over-provisioned. Still, it is not excessively large.

Completeness3/5

The server covers the main info-retrieval needs for toilets, station hazards, alerts, and train status. However, station_search explicitly tells agents to 'search_ramen' for ramen details, yet that tool is not provided, creating a clear dead end. Also, the domain is broader than the server name suggests, and some peripheral data (e.g., detailed ramen profiles) is only partially surfaced.

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