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Data Ingestion Batches — Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Data Ingestion Batches — Record Quality Audit + String Normalisation + 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 2026-10-17).
Runs three analytical reports on supplied data ingestion batch records: a record quality audit, string normalisation, and keyed comparison between two datasets — all locally, with no external calls.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied data ingestion batches records (received_rows, accepted_rows). 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 completeness, validity, and anomalies in received_rows and accepted_rows; (2) a string normalisation report cleaning and standardising text fields like dataset_group; and (3) a keyed comparison report showing differences between the primary and secondary datasets matched by row_id. All reports are computed locally from supplied data only.
Example use cases
Pipeline batch quality gate check
“Run a record quality audit on my latest ingestion batch — I have 4 rows for dataset groups 'sales' and 'returns' from 2026-11-01 to 2026-11-04, with received_rows of 500, 320, 410, 290 and accepted_rows of 498, 315, 400, 285. Flag any quality issues.”
Before-and-after ingestion comparison
“Compare my two ingestion batch snapshots by row key — the baseline has received_rows of 1000, 850, 920 and the reprocessed version has 1000, 860, 905 for the same row IDs and groups. I want to see the keyed differences.”
String normalisation for ingestion group labels
“Run a string normalisation report on my ingestion batch records — I have dataset_group values like 'Group-A', 'group_a', 'GROUP A' across 6 rows and I want them cleaned up consistently.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous analytical perspectives on data ingestion batch records — quality auditing, string normalisation, and cross-dataset comparison — in a single $0.01 call with up to 200 rows. Ideal for data engineers validating ETL pipeline outputs, comparing ingestion snapshots, or cleaning up group label strings, without requiring any external data lookups or live connections.
Side effects
- More than 200 rows submitted — request rejected due to row limit
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric values out of allowed range (±1,000,000,000,000) — validation error
- Empty rows array — rejected due to minItems:1 constraint
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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