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Data Reconciliation — Adjacent Row Changes + Secondary-Measure Weighted Mean
x402
Data Reconciliation — Adjacent Row Changes + Secondary-Measure Weighted Mean 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).
Computes adjacent row changes and secondary-measure weighted mean analytics on up to 200 supplied data reconciliation records containing source and target totals.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean 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 analytical reports derived from the supplied rows: (1) adjacent row changes showing sequential differences between consecutive records, and (2) a secondary-measure weighted mean across the dataset. Both reports are computed locally using the provided source_total and target_total values with no external lookups.
Example use cases
Financial ledger source-target drift analysis
“I have a set of daily ledger reconciliation records for October 2026 across two business units, with source and target totals for each day. Can you compute the adjacent row changes and the target-weighted mean on the source_total field so I can see how the drift evolves day by day?”
Dataset group sequential change audit
“I need to audit my reconciliation dataset — I have 50 rows across three dataset groups with dates and source/target totals. Run the adjacent row changes report and the secondary-measure weighted mean on the target_total field so I can spot where values jump unexpectedly between rows.”
Quarterly reconciliation summary for two teams
“We're comparing source and target pipeline totals for Q4 across two teams, and I need both an adjacent row change analysis and a weighted mean summary using source_total as the secondary measure. Here are the 120 rows — can you generate both reports at once?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-159?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two specific offline analytics — adjacent row changes and secondary-measure weighted mean — on a batch of up to 200 reconciliation records with source and target totals, and you want both reports in a single paid call for $0.01 USDC. Prefer this over general-purpose analytics tools when working with structured reconciliation data in the specific schema format (row_id, dataset_group, date, source_total, target_total) and you need deterministic, local computation with no external data dependencies.
Side effects
- More than 200 rows submitted — request exceeds maxItems limit and will be rejected
- Missing required fields (row_id, dataset_group, date, source_total, target_total) causes validation failure
- Date strings not matching YYYY-MM-DD pattern result in schema validation errors
- Null values in source_total or target_total may affect weighted mean computation
- Invalid field enum value (not 'source_total' or 'target_total') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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