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Snow Observations — Record Quality Audit + Date-by-Category Pivot
x402
Snow Observations — Record Quality Audit + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Runs two local analytical reports on supplied snow observation records: a record quality audit and a date-by-category pivot for snow_depth_cm or snowfall_cm fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Snow observations — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied snow observations records (snow_depth_cm, snowfall_cm). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two reports: (1) a record quality audit identifying issues such as missing values, malformed rows, or anomalies in the supplied snow observation records; (2) a date-by-category pivot table aggregating the selected snow metric (snow_depth_cm or snowfall_cm) across dates and station groups. Both reports are computed locally with no external lookups.
Example use cases
Winter station data quality check
“I have 80 rows of snow observation data from our weather stations with fields row_id, station_group, date, snow_depth_cm, and snowfall_cm. Can you audit the record quality and also give me a date-by-category pivot on snowfall_cm so I can see how readings break down across station groups over time?”
Seasonal snowfall dataset validation
“We collected snowfall measurements across three monitoring groups for October and November — about 150 rows total. Please run a quality audit on the records and generate a date-by-category pivot for snow_depth_cm so we can spot gaps or outliers by group and date.”
Pre-analysis snow data sanity check
“Before I load this snow observation dataset into our model, can you audit the data quality and pivot the snow_depth_cm values by date and station_group? I've got around 30 rows with row_id, station_group, date, snow_depth_cm, and snowfall_cm fields.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-09-017?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a date-by-category pivot on snow observation records (snow_depth_cm and/or snowfall_cm) in a single call, with up to 200 rows, at minimal cost. It is ideal when no live data lookup, forecasting, or external data enrichment is needed — only local analytical computation on data you supply. Prefer alternatives if you need more than 200 rows, live weather data, or different output report types.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, station_group, date, snow_depth_cm, or snowfall_cm) cause row-level errors
- Invalid date format (not YYYY-MM-DD) triggers validation failure
- Empty rows array returns an error
- Invalid field enum value causes report generation failure
- Payment of 0.01 USDC not provided or rejected blocks execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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