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Join Coverage Analytics: Record Quality Audit + String Normalisation + Daily Sum Series
x402
Join Coverage Analytics: 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 2026-10-19).
Runs three local analytical reports on join coverage data (matched_rows, source_rows): a record quality audit, string normalisation, and daily sum series — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied join coverage records (matched_rows, source_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
Three independent analytical reports returned for the submitted rows: (1) a record quality audit flagging issues in the supplied join coverage records, (2) a string normalisation report on text fields like row_id and dataset_group, and (3) a daily sum series aggregating the selected numeric field (matched_rows or source_rows) by date — all computed locally with no external lookups.
Example use cases
ETL pipeline join quality check
“I've got 150 rows of join coverage data from our nightly ETL run for October, with dataset groups 'sales' and 'returns' — can you audit the record quality, normalise any string fields, and give me daily sums for matched_rows?”
Coverage gap investigation by group
“We're seeing unexpected drops in match rates for our 'customers' and 'orders' dataset groups last week. Can you run the record quality audit and daily sum series on these 80 rows using the source_rows field so I can spot the problem days?”
Data pipeline monitoring dashboard prep
“I need to prep daily aggregation and quality metrics for our join coverage dashboard — here are 200 rows across 5 dataset groups from November 2026, please run all three reports on the matched_rows field.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical reports (quality audit, string normalisation, daily aggregation) on join coverage data in a single cheap call. Ideal for data engineers monitoring ETL pipelines, analysts checking match rates over time, or anyone needing a quick multi-faceted diagnostic on up to 200 rows of joined dataset records without requiring external lookups or live data access.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors
- Date values not matching YYYY-MM-DD pattern will fail schema validation
- Null numeric values for both matched_rows and source_rows may reduce audit accuracy
- Invalid field enum value (anything other than 'matched_rows' or 'source_rows') causes rejection
- Payment of 0.01 USDC not provided or declined blocks execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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