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Forecast Verification Inputs — Record Quality Audit + Grouped Numeric Summary
x402
Forecast Verification Inputs — Record Quality Audit + Grouped Numeric Summary 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).
Runs a record quality audit and a grouped numeric summary on up to 200 rows of forecast_value/observed_value pairs, returning two analytical reports computed locally.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — Record quality audit + Grouped numeric summary: Record quality audit + Grouped numeric summary 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: (1) a record quality audit flagging issues such as nulls, out-of-range values, and duplicate row IDs across the submitted rows; and (2) a grouped numeric summary (counts, means, distributions) of forecast_value and observed_value broken down by station_group. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Weather station forecast data audit
“I have a CSV of 120 weather station readings with forecast and observed temperature values across two station groups — can you run a data quality audit on them and give me a grouped numeric summary by station group so I can spot any bad rows before I do my analysis?”
Pre-analysis validation of prediction records
“Before I hand off this forecast verification dataset to my model pipeline, can you check all 80 rows for quality issues and summarize the numeric distribution of forecast_value and observed_value grouped by station_group?”
Grouped summary for forecast review report
“I need to review forecast accuracy across group-a and group-b for October 2026 — here are 40 rows of forecast and observed values, can you audit them for data quality problems and give me a grouped numeric summary I can include in my report?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-005?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular forecast verification data (forecast vs observed pairs) and need both a data quality check and grouped descriptive statistics in a single API call at low cost. It is best suited for pre-analysis validation of weather or numeric prediction datasets grouped by a categorical field, where no live data lookup, external prediction, or professional assessment is needed. Avoid if you need real-time forecast data, model training, or more than 200 rows processed at once.
Side effects
- Empty rows array or missing required fields (row_id, date, forecast_value, observed_value) causes validation error
- Exceeding 200 rows returns an error about maxItems constraint
- Malformed date strings not matching YYYY-MM-DD pattern cause schema rejection
- Null values in forecast_value or observed_value are accepted but may reduce summary completeness
- Payment failure via x402 protocol prevents endpoint execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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