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Nws Get Observations

nws_get_observations
Read-only

Get current weather observations (actual measured conditions). Accepts coordinates (resolves nearest station automatically) or a station ID directly (e.g., "KSEA").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeNoLatitude for automatic station resolution. Use with longitude. Ignored if station_id is provided.
longitudeNoLongitude for automatic station resolution. Use with latitude. Ignored if station_id is provided.
station_idNoStation identifier directly (e.g., "KSEA", "KORD"). Use nws_find_stations to discover station IDs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
noticeNoGuidance when the latest observation is more than 2 hours old — data may not reflect current conditions.
stationNoStation ID that served the observation (e.g., "KSEA")
timeZoneNoStation time zone when known
dewpointCNoDewpoint in Celsius
stationIdNoObservation station ID
timestampNoObservation time (ISO 8601)
heatIndexCNoHeat index in Celsius
observedAtNoObservation timestamp (ISO 8601)
windChillCNoWind chill in Celsius
cloudLayersNoCloud layer information
stationNameNoStation name
visibilityMNoVisibility in meters
windGustKmhNoWind gust in km/h
temperatureCNoTemperature in Celsius
windSpeedKmhNoWind speed in km/h
textDescriptionNoConditions summary (e.g., "Mostly Cloudy")
windDirectionDegNoWind direction in degrees (0-360)
relativeHumidityPctNoRelative humidity in percent (0-100)
barometricPressurePaNoBarometric pressure in Pascals

TDQS

A4.2/5.0
Behavior4/5

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

ReadOnlyHint is true and the description does not contradict it (says 'get', a read operation). Beyond the annotation, it discloses a key behavior: automatic nearest-station resolution when coordinates are provided. This adds meaningful context beyond the schema and annotations, justifying a 4.

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?

A single sentence that front-loads the core purpose and then covers both input methods without any redundant words. Every phrase contributes value, and it is immediately scannable.

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?

For a simple read-only tool with a full output schema and 100% parameter documentation, the description covers the essential usage: giving coordinates or a station ID. It does not explicitly mention that station_id overrides coordinates (though the schema does) or that only one input method should be used, but that is covered structurally. Overall, an agent has enough to call it 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% and each parameter already has a clear description (e.g., latitude says 'for automatic station resolution'). The description adds no new parameter semantics beyond an example station ID and a pointer to nws_find_stations, which the schema already implies. Baseline 3 is appropriate when the schema fully documents parameters.

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 the specific verb 'Get' and resource 'current weather observations', with the parenthetical 'actual measured conditions' clearly differentiating from forecast tools. The description also names both input methods (coordinates and station ID), making its scope unambiguous.

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 implies when to use it (for current measured conditions rather than forecasts) and references nws_find_stations for station ID discovery, but does not explicitly contrast with sibling tools like nws_get_forecast or state when *not* to use it. The context is clear, but explicit alternatives are missing, so it falls short of a 5.

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

A4/5.0
Disambiguation4/5

Each tool targets a distinct data product (stations, forecast, observations, office discussion, zone forecast, alert types, alerts). Forecast-related tools are clearly differentiated by granularity and purpose, though get_forecast and get_zone_forecast could be confused by users unfamiliar with NWS terminology.

Naming Consistency5/5

All tool names follow the consistent pattern nws_verb_noun in snake_case (e.g., find_stations, get_forecast, list_alert_types). This makes the API highly predictable and easy to navigate.

Tool Count5/5

Seven tools is well within the ideal 3-15 range for a weather-focused server. Each tool covers a major NWS data category without unnecessary redundancy, making the set feel tight and purposeful.

Completeness4/5

The tool set covers the core weather workflow: station discovery, observations, forecasts, zone text, office discussions, and alert searching. Minor gaps like marine-specific products or radar imagery exist, but the essential weather information needs are well covered.