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Data Reconciliation Analytics: Record Quality Audit + String Normalisation + Numeric Interval Filter
x402
Data Reconciliation Analytics: Record Quality Audit + String Normalisation + Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Runs three local analytical reports on up to 200 reconciliation rows: a record quality audit, string normalisation, and a numeric interval filter on source/target totals.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied data reconciliation records (source_total, target_total). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports: (1) a record quality audit flagging data issues across the supplied rows, (2) a string normalisation report for string fields such as row_id and dataset_group, and (3) a numeric interval filter report identifying which records fall within the specified min/max range for the chosen field (source_total or target_total). All computed locally with no external lookups.
Example use cases
Pre-load reconciliation data validation
“I have 150 reconciliation rows with source_total and target_total values and I need to check them for quality issues, normalise the string fields, and filter the source_total column to only see records between 0 and 50000 before I load them into the warehouse.”
Spotting dirty string data in grouped records
“Can you run a string normalisation report on my dataset_group and row_id fields across these 80 reconciliation records? I also want a quality audit and want to see which target_total values fall between -1000 and 1000.”
Financial reconciliation discrepancy audit
“Run a full quality audit, string normalisation, and numeric range filter on these 200 reconciliation rows — filter on target_total between 100 and 500000 — so I can find any dirty or out-of-range records before my month-end close.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and numeric interval filtering — on reconciliation data in a single low-cost call. Ideal when you have up to 200 source/target rows and want offline, deterministic analysis without any external API calls, predictions, or professional assessments. Not suitable if you need live data lookup, ML-based anomaly detection, or more than 200 rows per call.
Side effects
- More than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, source_total, target_total) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside ±1,000,000,000,000 — schema rejection
- minimum greater than maximum — likely produces empty interval filter results
- Payment not completed — 402 response, no reports returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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