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Data Ingestion Batches — Record Quality Audit + String Normalisation + Base-100 Series
x402
Data Ingestion Batches — Record Quality Audit + String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Runs three local analytical reports on data ingestion batch records: a record quality audit, string normalisation, and a base-100 index 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 + Base-100 series: Record quality audit + String normalisation + Base-100 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 flagging missing, null, or out-of-range values in the ingestion rows; (2) a string normalisation report cleaning dataset_group and other string fields; and (3) a base-100 index series for the chosen numeric field (received_rows or accepted_rows), anchored at the specified base_index row. All computed locally with no external lookups.
Example use cases
Pipeline acceptance rate quality check
“I have 150 rows of daily ingestion logs with received_rows and accepted_rows for two dataset groups. Can you audit them for record quality issues, normalise the dataset_group strings, and give me a base-100 index series on accepted_rows starting from row 0?”
Spotting data ingestion anomalies
“Something looks off in our data pipeline — can you run a quality audit and base-100 series on received_rows for this batch of 80 ingestion records so I can see where things diverge from the baseline?”
Normalising inconsistent dataset labels
“Our dataset_group values are messy with inconsistent casing and spacing. Can you run the string normalisation report on these ingestion batch rows and also give me the quality audit while you're at it?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-201?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and base-100 indexing — on data ingestion batch records in a single $0.01 call, without needing live lookups, external data enrichment, or predictive analytics. Ideal for ETL pipeline monitoring, data quality gates, and trend indexing on received vs accepted row counts across dataset groups.
Side effects
- Fewer than 1 or more than 200 rows submitted — rejected with validation error
- Invalid date format (not YYYY-MM-DD) causes row-level validation failure
- base_index out of range (0–199) or exceeding submitted row count
- Null or out-of-range numeric values in received_rows/accepted_rows may be flagged but not rejected
- Unrecognised field enum value (anything other than 'received_rows' or 'accepted_rows') causes request rejection
- Extra properties in row objects rejected due to additionalProperties: false
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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