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Data Ingestion Batches — Record Quality Audit + String Normalisation + Equal-Width Histogram
x402
Data Ingestion Batches — Record Quality Audit + String Normalisation + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs three local analytical reports (record quality audit, string normalisation, and equal-width histogram) on up to 200 data ingestion batch records containing received_rows and accepted_rows fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Record quality audit + String normalisation + Equal-width histogram: Record quality audit + String normalisation + Equal-width histogram 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 flagging data issues such as nulls, out-of-range values, and missing fields; (2) a string normalisation report cleaning and standardising text fields like dataset_group and date; and (3) an equal-width histogram of the chosen numeric field (received_rows or accepted_rows) divided into the specified number of bins. All reports are computed locally from the supplied rows with no external lookups.
Example use cases
ETL pipeline data quality check
“I have 80 rows from our nightly ETL ingestion job with row_id, dataset_group, date, received_rows, and accepted_rows fields — can you run a record quality audit and string normalisation on them and also give me a 10-bin histogram of the accepted_rows distribution?”
Ingestion acceptance rate profiling
“Audit the quality of these 120 data ingestion batch records and show me a 5-bin equal-width histogram of received_rows so I can see how the load is distributed across our dataset groups.”
Dataset group anomaly detection prep
“I've got 200 rows of ingestion batch data — run all three reports: record quality audit, string normalisation, and a 7-bin histogram on accepted_rows — I want to spot any anomalies before the data goes to our warehouse.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-202?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous analytical reports (quality audit, string normalisation, histogram) on a batch of up to 200 data ingestion records in a single call for a flat $0.01 USDC fee, without requiring any external data lookups, predictions, or live connections. It is ideal for profiling ETL pipeline outputs, validating ingestion batch health, or characterising row count distributions before downstream processing.
Side effects
- Rows array exceeds 200 items — request rejected
- Required fields (row_id, date, received_rows, accepted_rows) missing from row objects
- Invalid date format (must match YYYY-MM-DD pattern)
- bins parameter out of range (must be 1–30)
- field value not one of the allowed enum values (received_rows, accepted_rows)
- Payment of 0.01 USDC not provided or declined
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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