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Glama

jma_get_tsunami

Retrieves recent Japan Meteorological Agency tsunami warnings, advisories, and forecasts, showing active status, affected coastal areas, expected wave heights and arrival times, and source earthquakes.

Instructions

Tsunami warnings, advisories and forecasts (津波警報・注意報・予報) from the Japan Meteorological Agency (JMA). Returns the latest bulletin for each recent tsunami-related event, newest first, with: whether it is still in effect; its highest level (major_warning 大津波警報 > warning 津波警報 > advisory 津波注意報 > forecast 津波予報, i.e. slight sea-level change with no damage expected); coastal forecast areas grouped by category with expected maximum height in metres and first-wave arrival time (JST); observed tsunami heights if any; and the source earthquake (which may be far from Japan). any_warning_in_effect=false means no tsunami warning or advisory is active now.

Input Schema

NameRequiredDescriptionDefault
limitNoHow many recent events to return (default 3).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden well. It discloses ordering (newest first), event grouping, active-status semantics, severity hierarchy, coastal forecast structure, observed heights, and source earthquake linkage. It stops short of describing error or no-event behavior, but covers the important output semantics thoroughly.

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?

The description is dense but front-loaded: the resource and source appear immediately, followed by return structure and severity interpretation. Some parenthetical detail makes it long, but most of it earns its place by explaining non-obvious return semantics.

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?

There is no output schema, so the description must explain return values, and it does: active status, highest level hierarchy, grouped coastal areas, expected heights, arrival times, observations, and source earthquake. For a one-parameter read tool, this is complete enough to call and interpret correctly.

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%, so the schema already documents the single limit parameter, including default and min/max. The description does not add parameter-specific meaning beyond saying results are recent events, 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?

States a specific verb and resource: returns JMA tsunami warnings, advisories and forecasts. It clearly distinguishes this from sibling tools like jma_get_warnings and jma_get_forecast by naming the exact hazard type and bulletin contents.

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 this tool is appropriate: retrieving latest tsunami bulletins and interpreting whether any warning is active. It does not explicitly name alternatives or exclusions, but the hazard-specific scope makes usage unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.