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Forecast Verification Inputs — Exact Row Deduplication + Category Frequencies
x402
Forecast Verification Inputs — Exact Row Deduplication + Category Frequencies 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).
Deduplicates forecast verification rows and computes category-level frequency distributions for supplied forecast_value/observed_value records, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — Exact row deduplication + Category frequencies: Exact row deduplication + Category frequencies 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
Returns two reports: (1) a deduplicated version of the input rows with exact duplicate records removed, and (2) frequency counts per category (station_group) across the supplied dataset — all computed locally without external lookups.
Example use cases
Clean duplicate weather station records
“I've got 150 forecast verification rows from multiple weather stations and I suspect there are exact duplicates — can you deduplicate them and tell me how frequently each station group appears? Stations include group-a and group-b with dates from 2026-10-01 through 2026-12-31 and paired forecast and observed values.”
Category frequency audit for forecast dataset
“For my forecast verification dataset with rows like row_id, station_group, date, forecast_value, and observed_value, can you run an exact deduplication and give me the category frequency breakdown per station group so I know how many records belong to each category?”
Pre-analysis data quality check on forecast inputs
“Before I run my verification model, can you check my 80 forecast observation rows for exact duplicates and compute how often each station group shows up? The rows have fields: row_id, station_group like 'northeast-1' or 'southwest-3', date in YYYY-MM-DD format, plus forecast_value and observed_value numbers.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-041?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local deduplication and category frequency analysis on forecast verification data (up to 200 rows) without requiring live prediction, external data enrichment, or professional meteorological assessment. Ideal for data cleaning pipelines before model ingestion or audit workflows where you need both a clean row set and a grouped count summary in a single low-cost call.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, forecast_value, observed_value) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern will fail schema validation
- Numeric values outside the allowed range (-1e12 to 1e12) will be rejected
- Empty rows array (minItems: 1 not satisfied) will return an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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