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List EONET Event Categories

eonet.events.categories
Read-onlyIdempotent

List all available natural event categories in the NASA EONET system with their IDs, titles, and descriptions. Returns all 13 categories: drought, dustHaze, earthquakes, floods, landslides, manmade, seaLakeIce, severeStorms, snow, tempExtremes, volcanoes, waterColor, wildfires. Use category IDs as the "category" filter in eonet.events.list and as the "category_id" parameter in eonet.events.layers. No auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoReserved for future use. Currently EONET returns English-only category names and descriptions.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the specific list of categories and the fact that it returns IDs/titles/descriptions, which is useful but not extensive behavioral detail. There is no contradiction 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 three sentences, no filler, and front-loads the purpose before listing categories and usage. Every sentence 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?

Given the tool's simplicity, the description covers everything an agent needs: what it returns (13 categories with IDs, titles, descriptions), how to use the output (as filters in sibling tools), and the lack of auth. An output schema exists, so return format details need not be repeated. The description is complete.

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 provides 100% coverage for the single optional 'locale' parameter, including its reserved-for-future-use note. The description does not add any additional meaning about the parameter beyond the schema, so the baseline of 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 states a clear verb ('List') and a specific resource ('all available natural event categories in the NASA EONET system'). It enumerates the exact 13 categories and distinguishes itself from sibling tools by naming eonet.events.list and eonet.events.layers as consumers of its output.

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?

It explicitly explains when to use this tool: to get category IDs for filtering in eonet.events.list and eonet.events.layers. It also notes that no authentication is required, giving clear context for usage without leaving anything to inference.

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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