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by io.github.OneWave-AI
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Historical hurricane tracks (26 seasons)

get_hurricane_history
Read-onlyIdempotent

Search 26 completed seasons of NOAA NHC HURDAT2 best-track history (2000–2025), Atlantic and eastern/central Pacific. Includes tropical cyclones, not only hurricanes. Filter by basin, year range, name, storm ID, hurricane strength or recorded landfall. Paginated summaries by default; includeTrack=true returns UTC positions, sustained wind kt, pressure mb, status, special-event flags and 34/50/64 kt wind radii in nautical miles ordered NE, SE, SW, NW. Missing measurements are null. Landfall flags cover any coastline, not specifically the US. Finalized retrospective tracks are not forecasts; current 2026 advisories use get_hurricanes. Historical tracks alone do not measure local damage or future risk.

Units: sustained wind kt; pressure mb; coordinates degrees; UTC track timestamps; wind radii nautical miles ordered NE, SE, SW, NW. Missing measurements are null. Returns data and source/freshness metadata.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_hurricane_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover read-only, idempotent, non-destructive and open-world traits, and the description still adds substantial operational detail: paginated summaries by default, the exact payload returned when includeTrack=true (UTC positions, kt/mb units, status, special-event flags, 34/50/64 kt radii ordered NE/SE/SW/NW), null semantics for missing measurements, and source/freshness metadata in the response.

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?

Front-loaded with purpose, scope and the sibling disambiguation in the first sentence, then detail that earns its place. However, the unit/null conventions are stated twice — once inline in the includeTrack sentence and again in the closing 'Units:' paragraph — which is avoidable repetition.

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 no output schema, the description carries the burden of explaining return content and does so thoroughly: default summary shape, full track payload with field units and wind-radii ordering, null handling, plus source and freshness metadata. An agent has everything needed to call and interpret this tool.

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 0%, yet the description accounts for essentially every filter: basin, year range, name, storm ID, hurricane strength, landfall, and includeTrack, with limit/offset implied by 'paginated summaries by default'. It does not spell out the basin enum values or default values (all, 20, 2000–2025) that live only in the schema, leaving a small gap.

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 (search NOAA NHC HURDAT2 best-track history) with explicit scope: 26 seasons, 2000–2025, Atlantic and eastern/central Pacific. It also disambiguates from the sibling get_hurricanes by noting that current 2026 advisories live there, and clarifies that tropical cyclones are included, not only hurricanes.

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 names the alternative tool for current advisories (get_hurricanes) and sets expectations about what this tool is not for: it is finalized retrospective data, not forecasts, and does not measure local damage or future risk. It also warns that landfall flags cover any coastline, not just the US, which prevents a common misuse.

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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