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ROVE Snow Forecast

by com.rove-ski
OverviewDiscussionsAdmin

Search ROVE Ski Resorts, Regions & Passes

search
Read-onlyIdempotent

Run OpenAI-compatible full-text keyword search across ROVE ski resorts, regional hubs, and pass hubs to obtain canonical IDs for fetch; use search_resorts instead for structured pass/country/region catalog filtering. Read-only results use in for snowfall, F for temperature, and include canonicalUrl and observedAt.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search"
  }
}

Input Schema

NameRequiredDescriptionDefault
langNoOutput language: en or zh. Default en; untranslated upstream text is unavailable in English.
limitNoMaximum results returned. Default 20; full membership counts are reported separately.
queryYesKeyword or natural-language query of 1 to 200 characters. Required.

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description focuses usefully on behavior beyond them: result units ('in' for snowfall, 'F' for temperature) and returned fields ('canonicalUrl', 'observedAt'). It stops short of describing result ordering, relevance behavior, or pagination, and 'OpenAI-compatible' hints at backend semantics without explaining them.

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?

Two sentences, front-loaded with the verb and scope, then the alternative and return conventions. Dense but every clause carries information; 'OpenAI-compatible' is the only term of questionable value to an agent.

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

Completeness5/5

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

There is no output schema, and the description compensates by naming the key return fields and their units. For a simple three-parameter read tool, the agent has what it needs: what is searched, how to disambiguate from search_resorts, and what comes back.

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 (lang, limit, query) already carries a description, enum, and examples. The description adds no parameter-level meaning beyond the schema, so the baseline of 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?

States a specific verb and resource ('Run ... full-text keyword search across ROVE ski resorts, regional hubs, and pass hubs') and names the downstream purpose ('to obtain canonical IDs for fetch'). It also explicitly contrasts itself with search_resorts, so an agent can distinguish it from the nearest sibling 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?

Names the alternative and the condition that selects it: 'use search_resorts instead for structured pass/country/region catalog filtering.' The chaining hint toward 'fetch' tells the agent what to do with the results, which is the other common decision point.

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

All ROVE Snow Forecast toolsInspect
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