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Join Coverage Record Quality Audit & Numeric Interval Filter
x402
Join Coverage Record Quality Audit & Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Audits record quality and applies a numeric interval filter to join coverage data (matched_rows, source_rows) for up to 200 rows, returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied join coverage records (matched_rows, source_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 identifying nulls, invalid values, and data issues across the supplied rows; and (2) a numeric interval filter report listing which rows have the selected field (matched_rows or source_rows) outside the specified minimum/maximum bounds. Covers up to 200 rows per call. No external lookups or predictions are made.
Example use cases
ETL join coverage anomaly detection
“I have 150 rows of pipeline join coverage data with matched_rows and source_rows fields — can you run a record quality audit and flag any matched_rows values that fall outside the range 0 to 500?”
Data team daily join quality check
“Run a quality audit on these join coverage records for dataset groups alpha and beta from last week, and filter source_rows to highlight anything below 1 or above 10000.”
Null and outlier detection in join metrics
“Check these 80 join coverage rows for null values or quality issues in matched_rows, and also tell me which rows have matched_rows outside the interval 5 to 200.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-008?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, self-contained quality audit of join coverage tabular data (matched_rows, source_rows) combined with a numeric range filter, without requiring any external data sources, live lookups, or ML predictions. Ideal for data engineers and analysts who want a quick, cheap ($0.01 USDC) dual-report on up to 200 rows of join metrics during pipeline validation or daily monitoring routines.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) in any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Minimum value greater than maximum value — may produce empty or misleading interval filter results
- Non-numeric values in matched_rows or source_rows — schema rejection or null handling
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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