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Data Reconciliation — Base-100 Series + Secondary-Measure Weighted Mean
x402
Data Reconciliation — Base-100 Series + 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 a base-100 indexed time series and a secondary-measure weighted mean for supplied source/target reconciliation data rows, returning two analytical reports in one call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Base-100 series + Secondary-measure weighted mean: Base-100 series + 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 for the supplied rows: (1) a base-100 indexed time series rebased at the specified base_index row for the chosen field, and (2) a secondary-measure weighted mean across the dataset. Both reports are computed locally from the supplied data with no external lookups. Up to 200 rows are supported per call.
Example use cases
Monthly revenue reconciliation indexing
“I have 12 months of source and target revenue totals for two business units — can you run a base-100 series starting from January plus a weighted mean report on all the rows? Source values range from 50000 to 120000 and target values from 48000 to 115000, grouped by unit-A and unit-B.”
Multi-group inventory discrepancy analysis
“Compare my warehouse source counts vs target counts across 3 inventory groups from 2025-01-01 to 2025-03-31 — I want a base-100 index and a weighted mean so I can see where the biggest drift is. Use source_total as the field and start the base at row index 0.”
Quarterly budget vs actuals normalization
“I need to normalize my quarterly budget vs actuals data to a base-100 series and get the secondary-measure weighted mean — there are 8 rows across two departments from 2025-Q1 to 2025-Q4, source_total is the budget and target_total is actuals.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-166?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured reconciliation data with source and target totals and need both a base-100 indexed time series and a weighted mean computed in a single call without any external data lookups. It is well-suited for financial, inventory, or operational reconciliation scenarios with up to 200 rows grouped across multiple dataset groups. Prefer this over generic statistics APIs when you specifically need the base-100 rebasing plus weighted mean combination on pre-supplied row data.
Side effects
- Missing required fields (row_id, dataset_group, date, source_total, target_total) cause validation errors
- More than 200 rows submitted returns an error
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- base_index out of range (≥ number of rows) causes computation failure
- Null values in source_total or target_total may affect weighted mean accuracy
- Payment not attached or insufficient USDC causes 402 rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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