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Data Reconciliation — Adjacent Row Changes + Two-Measure Correlation
x402
Data Reconciliation — Adjacent Row Changes + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Analyzes supplied data reconciliation records (source_total vs target_total) by computing adjacent row-over-row changes and the correlation between the two measures, returning two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied data reconciliation records (source_total, target_total). 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 independent analytical reports: (1) an adjacent row changes report showing sequential deltas between consecutive rows for the selected field, and (2) a two-measure correlation report quantifying the statistical relationship between source_total and target_total across the supplied dataset. Processing is performed entirely using local analytical engines with no external lookups.
Example use cases
Finance team reconciliation audit
“I have a month's worth of daily reconciliation records with source_total and target_total for two dataset groups — can you compute the adjacent row changes and the correlation between the two measures so I can see where source and target drift apart?”
ETL pipeline discrepancy check
“After our ETL run I have 120 rows of source_total vs target_total figures by date and pipeline group. Can you run adjacent row-over-row change detection and correlation analysis on those so I can spot any systematic drift?”
Reporting period variance review
“We have quarter-end reconciliation data across four dataset groups — about 180 rows total. Please analyze adjacent row changes and the correlation between source_total and target_total so we can prepare our variance commentary.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-158?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both adjacent row-change analysis and two-measure correlation in a single call for reconciliation data with source_total and target_total fields. It is purpose-built for data reconciliation workflows (not general time series or arbitrary numeric columns) and provides two bundled reports efficiently at low cost. Prefer it over single-report endpoints when you need both analyses simultaneously, and over general statistical tools when your data conforms to the row_id/date/dataset_group/source_total/target_total schema.
Side effects
- Exceeding 200 rows causes rejection — keep input to maxItems:200
- Missing required fields (row_id, date, dataset_group, source_total, target_total) will cause validation errors
- Dates not matching YYYY-MM-DD format will fail pattern validation
- Numeric values outside ±1,000,000,000,000 will be rejected
- Fewer than 2 rows may produce degenerate or undefined correlation results
- Null values in source_total or target_total may affect correlation calculation quality
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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