NOAA Climate Data

find_stations

Find NOAA weather stations in an area.

Returns a list of weather stations with their IDs, names, coordinates,
and active date ranges. Use the station IDs with get_climate_data.

Args:
    state: Two-letter US state abbreviation (e.g. 'CA', 'NY').
    county_fips: Five-digit county FIPS code (e.g. '36061' for Manhattan).
    dataset: Dataset ID to filter stations that have data in this dataset.
             Default is 'GHCND' (daily summaries).
    limit: Maximum number of stations to return (default 25, max 1000).

Input Schema

TableJSON Schema

Name	Required	Default
`limit`	No
`state`	No
`dataset`	No	GHCND
`county_fips`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses the return format (IDs, names, coordinates, active date ranges), the default dataset ('GHCND'), and the maximum limit (1000). It does not specify whether state or county_fips is required or how these filters interact, but for a read-only lookup tool, the coverage is solid.

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 front-loaded with the purpose, then provides return behavior and a concise, well-formatted Args section. Every sentence adds value and is structured for quick scanning.

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 four parameters, zero schema descriptions, and no annotations, the description covers all parameters and return behavior. The only notable gap is the lack of clarity on whether state and county_fips are required, optional, or mutually exclusive. For an otherwise thorough description, this is a minor but real omission.

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

Parameters5/5

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

The schema provides no property descriptions, so the description fully compensates. It explains each parameter with examples (e.g., 'CA', 'NY'; '36061' for Manhattan), specifies the dataset default, and clarifies the limit's maximum. This is exactly the level of detail needed for correct invocation.

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 opens with a specific verb and resource: 'Find NOAA weather stations in an area.' It clearly distinguishes this tool from siblings like get_climate_data and get_climate_normals by focusing on station discovery. The return fields are also summarized, reinforcing the tool's purpose.

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 explicitly states the downstream usage: 'Use the station IDs with get_climate_data.' This provides clear context for when to use the tool. However, it does not mention when not to use it or explicitly contrast it with get_climate_normals, so it falls just short of full guidance.

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

All NOAA Climate Data tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool has a distinct role: station discovery, historical data retrieval, and normals retrieval. The descriptions clearly differentiate the two data retrieval tools by their outputs and parameters. No overlap would cause misselection.

Naming Consistency5/5

All three tools follow a consistent verb_noun pattern with snake_case. The verbs find and get are both appropriate for retrieval actions and follow a clear convention.

Tool Count5/5

With only 3 tools, the server is tightly focused on its purpose. Each tool is necessary and the count is within the natural range for a small domain-specific server.

Completeness4/5

The core workflow of finding stations and retrieving climate data or normals is covered. Minor gaps include no tool for listing available datasets or data types, but the provided examples make the surface workable.

Resources

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