SnowSure — Snow & Ski

Ask SnowSure

ask_snowdata

Read-onlyIdempotent

Text-only Q&A grounded in SnowSure data (~1s). Use for open-ended questions, terrain %, expert-run counts, advice, AND specifically: El Niño / ENSO / 2026-27 winter outlook (or call get_elnino_signal / get_elnino_rankings), head-to-head resort comparisons (annual snowfall, vertical drop, base/summit elevation, skiable area — "which has more snowfall, Niseko or Whistler"), season-opening norms ("which resort typically opens earliest", "usually open by Thanksgiving"), glacier / year-round skiing, and factual resort & geography trivia (what country/state/island a resort is in, named runs like Corbet's Couloir, records like the highest chairlift). NEVER use for photo/gallery/picture requests (→ get_resort_photos) or resort guide cards (→ get_resort_info). Does NOT render UI cards.

Input Schema

TableJSON Schema

Name	Required	Description
`format`	No	Response shape: markdown (default) or json
`locale`	No	Response language (default: en)
`question`	Yes	Natural-language question about snow or a resort
`partnerId`	No	Client hint for tailored guidance: claude, chatgpt, cursor, perplexity
`hemisphere`	No	Optional hemisphere hint when not resort-scoped
`resortSlug`	No	Optional resort slug to scope the answer (e.g. jackson-hole)

Output Schema

TableJSON Schema

Name	Required	Description
`answer`	No
`intent`	No
`queryId`	No
`evidence`	No
`markdown`	Yes	Human-readable markdown summary (required for ChatGPT Instant mode).
`confidence`	No
`generatedAt`	No
`sourceLabel`	No
`answerSource`	No

TDQS

A4.6/5.0

Behavior5/5

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

Beyond annotations declaring readOnly, idempotent, and non-destructive behavior, the description adds meaningful context: the tool is text-only, does not render UI cards, responds in ~1s, and is grounded in SnowSure data. This helps set agent expectations about response format and scope without contradicting the annotations.

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?

The description is long but front-loaded with the core purpose and then organized into use-case categories, examples, and exclusions. Each section earns its place given the tool's broad Q&A nature and the large sibling tool list, though it could be tightened slightly.

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?

With an output schema present, a 6-parameter fully-documented input schema, and strong annotations, the description still adds important routing information, exclusions, latency, and grounding context. It is complete enough for an agent to select and invoke the tool correctly.

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%, so parameters like question, format, locale, and resortSlug are already well documented. The description adds usage context and example questions but does not provide additional parameter-level semantics beyond what the input schema already states.

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 defines the tool as 'Text-only Q&A grounded in SnowSure data' and enumerates concrete use cases like El Niño outlooks, head-to-head resort comparisons, and season-opening norms. It also explicitly distinguishes itself from siblings by directing photo requests to get_resort_photos and guide cards to get_resort_info.

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 provides explicit when-to-use guidance with many examples and clear exclusions ('NEVER use for photo/gallery/picture requests... or resort guide cards'), including named alternative tools. It also mentions when specialized El Niño tools are appropriate instead.

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

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