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Forecast Verification Inputs — String Normalisation + Keyed Dataset Comparison
x402
Forecast Verification Inputs — String Normalisation + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Normalises strings and performs keyed dataset comparison across two sets of forecast verification records (forecast_value vs observed_value), producing 2 analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison 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 per call: (1) a string normalisation report standardising station_group labels across the submitted rows, and (2) a keyed dataset comparison report pairing forecast_value against observed_value by row_id and date, highlighting discrepancies between the two supplied datasets. No external data is fetched; analysis is performed entirely on the supplied rows (up to 200).
Example use cases
Weather station forecast accuracy audit
“I need to compare my weather forecast values against actual observed values for stations group-a and group-b across October 2026 — here are two datasets with row IDs and dates, can you normalise the station group strings and do a keyed comparison to show me where my forecasts diverged from observations?”
Dual-model forecast validation
“I ran two different forecasting models and I have their outputs alongside observed measurements for the same 150 station-days. Can you normalise the labels and run a keyed dataset comparison on both sets of records so I can see which model was more accurate?”
Historical forecast verification reporting
“We have forecast_value and observed_value pairs for 80 rows across multiple station groups from last quarter — please normalise the station group names and compare the two datasets by key so we get both verification reports for our accuracy review.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and keyed dataset comparison in a single call for forecast-vs-observed tabular data, have up to 200 rows, and want two structured reports without any live data lookup or external model inference. It is cost-effective at $0.01 USDC for 2 reports. Prefer alternatives if you need real-time forecast retrieval, more than 200 rows, or professional meteorological assessment.
Side effects
- Missing required fields (row_id, date, forecast_value, observed_value) returns validation error
- More than 200 rows in either array exceeds the batch limit
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Null values in both forecast_value and observed_value may produce incomplete comparison results
- Empty rows array (minItems:1 not met) returns schema error
- Payment failure (insufficient USDC) prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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