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jdalbright

NASA MCP

by jdalbright

nasa_earth_events

Find current or recent natural events from NASA EONET, including storms, wildfires, volcanoes, floods, and more. Retrieve coordinates and source links for tracking.

Instructions

Find current or recent natural events from NASA EONET, including storms, wildfires, volcanoes, floods, sea/lake ice, dust, drought, and landslides. Returns latest coordinates and source links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxNoOptional [west, north, east, south] bounding box.
daysNo
limitNo
statusNoopen
categoryNoOptional EONET category ID, such as wildfires, severeStorms, volcanoes, floods, or seaLakeIce.
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavior disclosure. It adds value by stating that the tool returns 'latest coordinates and source links' and implies a time filter ('current or recent'), but it does not mention default values like days=14, status='open', or pagination behavior. For a simple read-only tool, this is adequate but not rich.

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 sentences, front-loaded with the core purpose and followed by a concise statement about return data. Every word adds value, with no repetition of schema defaults or other filler, making it an ideal size.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (5 optional parameters, no output schema), the description is mostly complete: it states the source (NASA EONET), what it returns (coordinates, links), and the event categories. It omits some details like default day range or status filtering, but those are present in the schema defaults, so the description is sufficient for selection and basic invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (40%), yet the description adds little to explain parameters. It repeats category examples already present in the schema (e.g., 'wildfires, severeStorms') but does not clarify 'days', 'limit', 'status', or 'bbox' beyond what the schema defaults provide. The description should compensate for low schema coverage but does not.

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's purpose with a specific verb ('Find') and resource (NASA EONET natural events), then lists explicit categories (storms, wildfires, volcanoes) that distinguish it from sibling tools like nasa_apod or nasa_power_daily. It also notes the output includes coordinates and source links, leaving no ambiguity about what the tool does.

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 provides clear context for when to use the tool by specifying it returns current or recent natural events and enumerating the event types covered. However, it does not explicitly name alternatives or state when not to use this tool, though the sibling tools are clearly different enough that the intended use case is evident.

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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