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SnowSure — Snow & Ski

by ai.snowsure

El Niño rankings

get_elnino_rankings
Read-onlyIdempotent

Ranked El Niño ski resorts from SnowSure's 30-year fleet table. Filter by region (south-america, north-america, europe, asia, oceania) or tier (A prime / B favored / C ENSO-proof / D late bloomer / E timing play). Use for 'best El Niño resorts in Europe', 'where will it snow most in 2026-27', 'is El Niño good for the Alps'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNoOptional tier letter or label: A/prime, B/favored, C/enso-proof, D/late bloomer, E/timing.
limitNoHow many resorts to return (default 10, max 50).
regionNoOptional region: south-america, north-america, europe, asia, oceania, or colloquial (andes, alps, japan, rockies).

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

A4.3/5.0
Behavior4/5

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

With readOnlyHint=true and idempotentHint=true annotations already establishing a safe read profile, the description adds meaningful context: the data source (SnowSure's fleet table), the 30-year window, and the tier semantics (A prime / B favored / C ENSO-proof / D late bloomer / E timing play). No annotation contradiction.

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?

Three tight sentences: first states the result, second details filters, third gives usage examples. Every clause adds value, with no fluff.

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?

For a simple read-only filter tool with 0 required params, a present output schema, strong annotations, and 100% schema coverage, the description fully complements the available context. Nothing material is missing.

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% with tier, limit, and region all documented, so the baseline is 3. The description reinforces region values and explains tier letters, but adds little beyond the schema's own descriptions.

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?

"Ranked El Niño ski resorts from SnowSure's 30-year fleet table" uses a specific verb+resource pair followed by the exact filter dimensions (region, tier). This clearly distinguishes it from siblings like get_elnino_signal or get_regional_summary.

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 'Use for' clause gives concrete example queries ('best El Niño resorts in Europe', 'is El Niño good for the Alps'), making when to use the tool very clear. It lacks explicit when-not-to-use guidance or named alternatives, but the usage context is unambiguous.

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