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California river gauge catalog

list_california_rivers
Read-onlyIdempotent

List configured California river gauge IDs and source references. Use get_california_river for observations and local forecast; stage is local gauge height, not navigation depth.

Units: ft, kt, s, F, mi; directions FROM. Returns data and source/freshness metadata.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_california_rivers"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lowered. The description adds 'returns data and source/freshness metadata' and a units/direction key, which is genuine added context, but the unit list (kt, F, mi) looks like boilerplate for a gauge-ID catalog and no pagination/limit behavior is disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the resource definition, followed by routing and a compact units/metadata line. Every sentence is short, though the kt/F/mi units feel extraneous to a gauge-ID list rather than earned content.

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

Completeness3/5

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

With no output schema the description does describe the return surface ('data and source/freshness metadata'), which is helpful. But the q filter parameter is left unexplained, and there's no indication of result size or shape, leaving a gap for an agent trying to invoke it correctly.

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?

There is one input parameter (a nested query.q string) at 0% schema description coverage, and the description never mentions it or any search/filter semantics. Unlike the zero-parameter baseline of 4, this leaves the only parameter entirely undocumented in both structured and prose fields.

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 a specific verb (List) and resource (configured California river gauge IDs and source references), and explicitly differentiates itself from the close sibling get_california_river, which it names as the tool for observations and forecast. The 'stage is local gauge height, not navigation depth' note sharpens the resource being cataloged.

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?

It routes the agent explicitly: use get_california_river for observations and local forecast, implying this tool is the catalog/index step. However it never states the reverse condition (when to call this list tool first), so it's clear context without a full when/when-not pair.

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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