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Data Ingestion Batches — Record Quality Audit + Trailing Mean Series
x402
Data Ingestion Batches — Record Quality Audit + Trailing Mean 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 two analytical reports on ingestion batch data: a record quality audit and a trailing mean series for received_rows or accepted_rows over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series for supplied data ingestion batches records (received_rows, accepted_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent reports: (1) a record quality audit covering the supplied rows with quality flags and assessments per record, and (2) a trailing mean series for the selected field (received_rows or accepted_rows) computed using the specified window size — both derived purely from the submitted data with no external lookups.
Example use cases
Daily ingestion pipeline quality review
“I have 30 days of ingestion batch records for my data warehouse pipeline — each row has a date, dataset group, and received vs accepted row counts. Can you audit them for quality issues and also compute a 7-day trailing mean on accepted_rows so I can spot trends?”
Acceptance rate anomaly detection
“My ingestion team logged received_rows and accepted_rows for four dataset groups over the past two weeks. Run a quality audit on those records and give me a trailing mean series with a window of 5 on received_rows so we can see where drops are happening.”
ETL batch monitoring for multiple groups
“We have batch ingestion logs from groups 'sales', 'inventory', and 'returns' for the last 60 days. Can you audit the record quality and calculate a trailing mean with window 10 on accepted_rows to help us monitor data completeness over time?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-010?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a record-level quality audit and a rolling/trailing mean time series computed together from your ingestion batch data in a single low-cost call. Ideal for data engineering teams monitoring ETL pipeline health across dataset groups without needing external data enrichment or predictions — just local analytical computation on your submitted rows.
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) on any row
- Invalid date format (must match YYYY-MM-DD pattern)
- Window size outside range 2–200
- Field value not one of the allowed enum values (received_rows, accepted_rows)
- All numeric values null — no computable series
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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