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wylieswanson

nws-weather-usgs-water-mcp

by wylieswanson

get_field_data

Read-onlyIdempotent

Retrieve discrete field measurements, metadata, channel measurements, or peaks from USGS water monitoring sites. Specify monitoring location and optional parameters like parameter code, time, or water year.

Instructions

Get discrete field measurements, metadata, channel measurements, or peaks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
timeNo
max_rowsNo
propertiesNo
water_yearNo
parameter_codeNo
monitoring_location_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description only adds the list of returned data types. It does not disclose important behaviors such as pagination (max_rows), performance considerations, or authentication requirements, which are essential for a tool with 7 parameters.

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 a single sentence with no wasted words. The verb 'Get' is front-loaded, and the entire content is directly about the tool's purpose. Every word earns its place.

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

Completeness2/5

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

Despite having 7 parameters, an output schema, and many siblings, the description is extremely minimal. It does not cover usage context, parameter interactions, or output shape. The agent would need additional knowledge to use this tool effectively.

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?

With 0% schema description coverage, the description must explain parameters. It implicitly adds meaning to 'kind' by listing its accepted values, but completely ignores the other 6 parameters (time, max_rows, properties, water_year, parameter_code, monitoring_location_id). The agent is left to infer their semantics from names and types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and the resource ('discrete field measurements, metadata, channel measurements, or peaks'), which matches the 'kind' enum. However, it does not differentiate this generic tool from more specific siblings like get_peak_flows or get_current_flow, which could cause confusion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusion criteria, leaving the agent to infer usage from the meaning of the 'kind' parameter alone.

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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