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Forecast Verification Inputs — Numeric Row Ordering + Daily Sum Series
x402
Forecast Verification Inputs — Numeric Row Ordering + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Computes numeric row ordering and a daily sum series for up to 200 rows of forecast/observed value pairs, returning two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — Numeric row ordering + Daily sum series: Numeric row ordering + Daily sum series for supplied forecast verification inputs records (forecast_value, observed_value). 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
Two analytical reports derived from the supplied rows: (1) a numeric row ordering that ranks records by the chosen field (forecast_value or observed_value), and (2) a daily sum series that aggregates the chosen field's values by date. No external data is fetched; all computation is local to the engine.
Example use cases
Weather station forecast accuracy ranking
“I have daily forecast and observed temperature readings from two station groups across 30 days. Can you rank all the rows by forecast_value and also give me a daily sum series so I can see how aggregate forecasts compare to observations over time?”
Daily sum aggregation for observed precipitation
“Here are 150 rows of precipitation forecast verification records with row IDs, station groups, dates, forecast values, and observed values. I need the numeric row ordering and daily sum series for the observed_value field — please run both reports.”
Quality review of model output vs actuals
“We're validating a new weather model and I need to review its output. I have 80 verification records from various station groups. Can you produce a row ordering and daily sum series for the forecast_value column so I can spot anomalies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-114?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular forecast verification data (forecast vs observed pairs) and need both a ranked row ordering and a daily sum time series in a single call without any external lookup or live prediction. It is especially useful for batch offline analysis of weather model outputs up to 200 rows, where the two bundled reports provide complementary views of the same dataset at a low flat cost.
Side effects
- More than 200 rows submitted — request exceeds max row limit
- Missing required fields (row_id, date, forecast_value, or observed_value) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Null values in the selected field may affect sum and ordering outputs
- Empty rows array (minItems:1 not met) results in schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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