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Data Ingestion Batches — Record Quality Audit + String Normalisation + Daily Sum Series
x402
Data Ingestion Batches — Record Quality Audit + String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Runs three analytical reports on data ingestion batch records: a record quality audit, string normalisation, and a daily sum series for received_rows or accepted_rows fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series 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
Returns three independent analytical reports: (1) a record quality audit highlighting issues in the supplied batch rows, (2) a string normalisation report cleaning text fields such as dataset_group, and (3) a daily sum series aggregating either received_rows or accepted_rows by date — all computed locally without external lookups.
Example use cases
Pipeline data quality health check
“I have 80 rows of data ingestion batch records with received_rows and accepted_rows for each date and dataset group — can you run a record quality audit, string normalisation, and daily sum series on them so I can see where data is being dropped?”
Daily accepted row aggregation by group
“Can you compute the daily sum series for accepted_rows across my ingestion batch records? I've got rows covering the past two weeks split across three dataset groups and I need to spot daily trends.”
Pre-migration batch data cleanse
“Before I migrate my ingestion pipeline data, can you run string normalisation and a quality audit on my 150-row batch dataset that has received_rows, accepted_rows, date, and dataset_group fields?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and daily sum series — on up to 200 ingestion batch records in a single low-cost call. It is ideal for data engineers monitoring ETL pipeline health or cleaning batch records without external dependencies or live data lookups.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) causes rejection
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Numeric values outside ±1,000,000,000,000 are rejected
- Invalid field enum value (not 'received_rows' or 'accepted_rows') causes an error
- Empty rows array is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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