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Data Reconciliation — Base-100 Series + Keyed Dataset Comparison
x402
Data Reconciliation — Base-100 Series + Keyed Dataset Comparison 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 keyed dataset comparison report for two sets of reconciliation records (source_total vs target_total), up to 200 rows each, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Base-100 series + Keyed dataset comparison: Base-100 series + Keyed dataset comparison 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) a base-100 indexed time series showing relative movement of the chosen field (source_total or target_total) across the supplied rows, and (2) a keyed dataset comparison report highlighting matches, mismatches, and deltas between the two supplied datasets grouped by row_id, dataset_group, and date. No external data is fetched; all computation is performed locally on the supplied data.
Example use cases
Monthly finance ledger reconciliation
“I have two sets of monthly finance ledger records — each with a row_id, date, dataset_group, source_total, and target_total — and I need to reconcile them: give me a base-100 series and a keyed comparison so I can see exactly where the source and target figures differ across up to 150 rows.”
Sales channel data discrepancy audit
“Can you compare my two sales channel datasets for Q3? Both have row_id, date, dataset_group, source_total, and target_total fields. I want a base-100 indexed trend and a side-by-side keyed comparison report so I can spot any discrepancies between the two sources.”
ETL pipeline output validation
“After our ETL run, I have the original source totals and the transformed target totals for 200 rows, each tagged with a row_id, date, and dataset_group. Please run a base-100 series and keyed dataset comparison on both so I can validate the pipeline output didn't introduce errors.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-168?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline, local analytical computation on supplied reconciliation data — specifically when you want both a base-100 normalized time series AND a keyed dataset comparison in a single call for up to 200 rows, without any live lookups, predictions, or external data enrichment. Prefer this over generic analytics endpoints when your use case is source-vs-target data reconciliation with date and group keying.
Side effects
- Missing required fields (row_id, dataset_group, date, source_total, target_total) returns a validation error
- More than 200 rows supplied causes rejection
- Date values not matching YYYY-MM-DD pattern cause schema validation failure
- Null values in source_total or target_total may affect numeric computations
- Empty rows array (minItems: 1 violated) returns an error
- row_id or dataset_group exceeding 80 characters causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array | |
| base_index | integer |
Tags
x402
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