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Data Ingestion Batches — Record Quality Audit & Adjacent Row Changes
x402
Data Ingestion Batches — Record Quality Audit & Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Performs a two-report analysis on up to 200 data ingestion batch records: a record quality audit and adjacent row change detection for received_rows or accepted_rows fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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 analytical reports: (1) a record quality audit flagging issues or anomalies in the supplied ingestion batch records, and (2) an adjacent row change report showing differences and eligible percentage changes between consecutive rows — both computed for the specified field (received_rows or accepted_rows) across up to 200 records.
Example use cases
Pipeline data quality review
“I have a week's worth of ingestion batch records for two dataset groups — 'customers' and 'transactions' — with received and accepted row counts per day. Can you run a quality audit and flag any records that look off, and also show me how accepted_rows changed between consecutive records?”
Acceptance rate anomaly detection
“My data pipeline has been behaving strangely. I have 50 daily batch records for the 'orders' dataset group with received_rows and accepted_rows values. Can you audit the record quality and show me the adjacent row changes for accepted_rows so I can spot where something went wrong?”
Cross-group ingestion comparison
“I'm reviewing ingestion health across three dataset groups — 'logs', 'events', and 'metrics' — and I have about 120 batch records spanning last month. Please run a quality audit and adjacent row change report on the received_rows field so I can see which groups have inconsistencies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-011?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular ingestion batch data with received_rows and accepted_rows metrics and need both a data quality audit and a period-over-period row change analysis in a single call. It is best suited for small-to-medium batch sizes (up to 200 rows) where you want two complementary analytical perspectives — quality flags and trend changes — without any external lookups or live data fetching. Prefer this over generic analytics tools when your data is already structured with dataset_group and date fields and you need fast, local computation results for under $0.01.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Null values in the target field may affect adjacency change calculations
- row_id exceeds 80-character limit — validation error
- Empty rows array — minItems constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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