SnowSure — Snow & Ski

SnowSure insights

get_insights

Read-onlyIdempotent

Get categorized SnowSure intelligence insights (not just snow totals). The last_season category is the one to reach for on retrospective questions — how a finished season compared to its 5yr norm, who led it, where the models were trustworthy. Also covers model accuracy by region, longest dry spell, and trend pulse. Insights are hemisphere-scoped narrative cards; when the question names a specific state, province, country or region and wants a ranked list, use get_season_leaderboard instead. Filter by category or insightType=intelligence to skip simple leaderboards.

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_insights"
  }
}

Input Schema

Name	Required	Description
`scope`	No	snapshot = one hemisphere; global = both hemispheres.
`category`	No	Single insight category id from list_insight_categories. Omit to return all categories.
`hemisphere`	No	Northern (nh) or southern (sh) hemisphere. Defaults to nh.
`insightType`	No	data = leaderboards only; intelligence = analysis cards (recommended).

Output Schema

Name	Required	Description	Default
`markdown`	No	Human-readable markdown summary of the tool result (may be omitted when structuredContent carries a typed payload; content[0].text always has the prose).

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedJul 2, 2026

changedOutput schema / properties / markdown / description

Previous value: -"Human-readable markdown summary of the tool result."New value: +"Human-readable markdown summary of the tool result (may be omitted when structuredContent carries a typed payload; content[0].text always has the prose)."

removedOutput schema / required
```
Removed value: -[
-  "markdown"
-]
```

First observedJun 19, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, read-only operation. The description adds valuable context: insights are narrative cards, hemisphere-scoped, and the last_season category provides comparisons to a 5yr norm. This enriches the agent's understanding of output behavior beyond what annotations provide.

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 four sentences, no filler. It front-loads the core purpose in the first sentence, then provides category-specific advice and sibling differentiation. Every sentence earns its place, making it very efficient for an agent to parse.

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?

Given the tool has an output schema (so return structure is documented elsewhere) and 4 optional enums, the description covers usage intent, scope (hemisphere-scoped), differentiation from a key sibling, and category-specific tips. It doesn't repeat schema details and is fully adequate for the agent to decide when and how to invoke this tool.

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

Parameters4/5

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

With 100% schema description coverage, the baseline is 3. The description adds meaning by explaining when to use specific parameters: e.g., 'last_season category is the one to reach for on retrospective questions' and 'Filter by category or insightType=intelligence to skip simple leaderboards.' This helps the agent decide which parameter values to pick for different intents.

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 clearly states the tool retrieves 'categorized SnowSure intelligence insights (not just snow totals)' and distinguishes itself from siblings by explicitly saying when to use get_season_leaderboard instead. It lists specific categories (last_season, model accuracy, dry spell) and describes the output format as 'hemisphere-scoped narrative cards', leaving no ambiguity about what the tool does.

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 provides explicit guidance: 'when the question names a specific state, province, country or region and wants a ranked list, use get_season_leaderboard instead.' It also recommends using insightType=intelligence to skip leaderboards and suggests the last_season category for retrospective questions. It could be improved by noting other sibling tools to avoid, but the guidance given is clear and actionable.

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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