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SnowSure — Snow & Ski

by ai.snowsure

Season leaderboard by place

get_season_leaderboard
Read-onlyIdempotent

Rank resorts by how a season actually went, scoped to a place. This is the tool for "which resort had the most last season" — the single most common retrospective question agents ask. Scope by state or province (Maine, Montana, Wyoming, British Columbia, Hokkaido, Nagano, Valais, Tyrol), by country (Switzerland, Japan, Canada), or by region (north-america, europe, asia, oceania, south-america, or a colloquial range: alps, andes, rockies, scandinavia). Metrics: snow_days, total_cm, powder_days, bluebird_days, max_storm (biggest single 24h snowfall, with the date it fell), peak_depth, longest_dry_spell. Covers 30 seasons back to 1996, so it answers historical and multi-season questions too, not just last season. Season accepts 2025, "2025-26", 2026, or "last" and resolves them all to the same season. Backed by ERA5 reanalysis across the full season window, so figures cover the entire season rather than only the days SnowSure has been live. Use get_snow_history for ONE resort's own history, get_monthly_snow for typical month-by-month climatology, and get_snow_report or find_best_powder for conditions RIGHT NOW.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many resorts to return (default 10, max 50).
stateNoState, province or equivalent: Maine, Montana, British Columbia, Hokkaido, Valais, Tyrol.
metricNoWhat to rank by. max_storm = biggest single 24-hour snowfall of the season.
regionNonorth-america, europe, asia, oceania, south-america, or a colloquial range: alps, andes, rockies, scandinavia.
seasonNoSeason to rank. Accepts a year (2025), a label ("2025-26"), the ending year (2026), or "last"/"latest". Northern-hemisphere seasons are keyed on their starting year.
countryNoCountry name, e.g. Switzerland or Japan.
hemisphereNoNorthern (nh, default) or southern (sh) hemisphere season.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
markdownNoHuman-readable markdown summary of the tool result (may be omitted when structuredContent carries a typed payload; content[0].text always has the prose).

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the tool's safety profile is clear. The description adds useful behavioral context: the data source (ERA5 reanalysis), coverage (full season, not only live days), and historical range (back to 1996). There is no contradiction with annotations.

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 compact and well-structured, opening with a clear, front-loaded purpose statement. Every sentence adds value, and it avoids redundancy with the schema. The tooltip-style guidance is efficient.

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?

Given the tool has 7 optional parameters, an output schema, and full schema coverage, the description is quite complete. It explains scoping, metrics, season resolution, data provenance, and provides sibling alternatives. It is slightly verbose on the scoping list but still within reason.

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?

Schema description coverage is 100%, but the description adds significant value by explaining how season values resolve, clarifying the metric enum, and providing examples for region and state. It also discloses defaults (metric=total_cm, hemisphere=nh, season=latest, limit=10, worldwide). The only small gap is not detailing the limit parameter's behavior beyond the schema.

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 ranks resorts by a season metric, scoped to a place. It uses specific verbs ('rank', 'scope') and explicitly distinguishes the tool from siblings like get_snow_history, get_monthly_snow, and get_snow_report.

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?

The description explicitly says when to use this tool ('which <place> resort had the most <metric> last season'), and when not to, by naming alternatives: get_snow_history for one resort's history, get_monthly_snow for climatology, and get_snow_report for current conditions.

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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TDQS

A3.6/5.0
Disambiguation2/5

Multiple tool clusters have unclear boundaries: get_resort overlaps with get_resort_info and get_resort_photos, ask_snowdata competes with compare_resorts and the El Niño tools, and get_snow_history / get_season_leaderboard / get_insights cover similar retrospective ground. The descriptions try hard to route agents, but with 45 tools an agent will frequently have to choose between near-equivalent options.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern: get_resort_info, compare_resorts, find_best_powder, book_lodging, save_resort. Minor deviations like ask_snowdata and the very similar get_resort vs get_resort_info names prevent a 5, but overall the naming convention is predictable.

Tool Count2/5

45 tools is well above the 25+ threshold and puts a heavy selection burden on the agent. While the domain is broad, many tools are narrow variations on conditions, history, road data, or trip planning that could be consolidated or exposed as configurable parameters.

Completeness4/5

The toolkit covers an impressively wide lifecycle: resort discovery, photos, live conditions, forecasts, history, comparisons, passes, flights, lodging, road status, alerts, and user saved resorts. Minor gaps exist such as no lift-ticket booking, no lesson/rental booking, and flight search only produces links rather than a booking flow, but agents can generally complete core snow-trip workflows.

Resources