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ROVE Snow Forecast

by com.rove-ski
OverviewDiscussionsAdmin

Read Station-Verified Forecast Accuracy

get_accuracy
Read-onlyIdempotent

Read station-verified historical forecast accuracy for one ski resort or the 435-station backtest methodology; use get_forecast_confidence instead for uncertainty on the current upcoming forecast. Read-only results use in for snowfall, F for temperature, and include canonicalUrl and observedAt.

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": "get_accuracy"
  }
}

Input Schema

NameRequiredDescriptionDefault
langNoOutput language: en or zh. Default en; untranslated upstream text is unavailable in English.
resortNoOptional resort name, slug or resort: ID; omit for the 435-station methodology including 105 SNOTEL stations.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully carried. The description adds genuine value beyond that by disclosing output conventions (inches for snowfall, F for temperature, plus canonicalUrl and observedAt), which matters specifically because there is no output schema. It does not mention rate limits or dataset freshness/date coverage, keeping it short of a 5.

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?

Two sentences with zero filler: the primary capability leads, the disambiguation follows, and the output conventions close. Nothing is redundant and the most decision-relevant information is front-loaded.

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 two-optional-parameter, read-only tool with no output schema, the description covers purpose, routing, and the shape/units of returned values, which is the main gap an output schema would otherwise fill. Only minor elements such as the dataset's historical time span are unaddressed.

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 description coverage is 100%, with both `lang` and `resort` fully documented including the omit-to-get-methodology behavior and the 435-station/105-SNOTEL detail. The description's mention of 'one ski resort or the 435-station backtest methodology' largely restates the schema, adding no new syntax or format constraints, so the baseline 3 applies.

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 states a specific verb and resource (read station-verified historical forecast accuracy) and immediately scopes it to two modes: a single ski resort or the 435-station backtest methodology. It also names the sibling tool it must not be confused with (get_forecast_confidence), so an agent can discriminate without opening either schema.

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

Usage Guidelines5/5

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

It gives an explicit routing rule: use get_forecast_confidence instead when the question is uncertainty on the upcoming forecast. The two operating modes are also stated up front, and the schema clarifies that omitting `resort` selects the 435-station methodology, so when-to-use and when-not-to-use are both covered.

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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