ML/AI trends
get_ml_trendsRead-onlyIdempotent
Fetch machine-learning trend datasets from SnowSure's API for powder-day rankings, bluebird predictions, model accuracy, and extended outlook. Use with dataset=catalog to explore endpoints.
Instructions
Fetch SnowSure-unique ML/AI trend datasets from the public REST API. Use for powder-day leaders, bluebird-day leaders, bluebird predictions, improving/stable/declining score pulse, per-model accuracy weights, daily SnowSure score component history, ML extended outlook (days 8–14), global forecast trust, and powder/bluebird event logs. Start with dataset=catalog. Prefer get_insights for narrative intelligence cards; use this for raw rankings and time series.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Lookback days for score_components (default 30, max 365). | |
| slug | No | Resort slug — required for score_components, vs_last_year, and season_stats; optional for extended_outlook (per-resort). | |
| limit | No | Max rows for leaderboards or snow_events (default 25, max 100). | |
| minCm | No | Minimum ML days 8–14 snow (cm) when dataset=extended_outlook leaderboard (default 0). | |
| stats | No | When dataset=snow_events, return season aggregates instead of events. | |
| resort | No | Resort slug filter when dataset=snow_events. | |
| dataset | Yes | Trend dataset to fetch. catalog lists all endpoints; powder_days / bluebird_days = season leaderboards; score_components needs slug. | |
| openOnly | No | When dataset=extended_outlook, filter to open resorts only (default true). | |
| eventType | No | Filter snow_events by event type. | |
| minSpread | No | Minimum 14d model spread (cm) when dataset=forecast_disagreement (default 5). |
Output Schema
TableJSON 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). |