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Null Coverage Record Quality Audit + Numeric Interval Filter
x402
Null 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 2026-10-14).
Audits null coverage (missing vs total values) in up to 200 rows and filters records by a numeric interval, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied null coverage records (missing_values, total_values). 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 summarizing null coverage statistics (missing_values vs total_values ratios, counts, and flags per row and group), and (2) a filtered list of records where the chosen field (missing_values or total_values) falls within the specified numeric interval [minimum, maximum]. All processing is local with no external lookups.
Example use cases
Data completeness check across groups
“I have 6 dataset rows from two groups — can you run a quality audit on the null coverage for these records and also filter where missing_values falls between 0 and 25? Rows: row-1 (group-a, 2025-01-01, missing=5, total=100), row-2 (group-b, 2025-01-02, missing=30, total=200), row-3 (group-a, 2025-01-03, missing=10, total=150), row-4 (group-b, 2025-01-04, missing=0, total=90), row-5 (group-a, 2025-01-05, missing=22, total=110), row-6 (group-b, 2025-01-06, missing=40, total=180).”
Filtering records by total values range
“For these records, can you check record quality and filter by total_values between 100 and 500? Here are the rows: row-A (groupX, 2025-03-01, missing=5, total=80), row-B (groupY, 2025-03-02, missing=12, total=300), row-C (groupX, 2025-03-03, missing=0, total=450), row-D (groupY, 2025-03-04, missing=7, total=600).”
Monthly ETL null coverage audit
“We ran our monthly ETL last night and ended up with these 5 rows — please audit the null coverage quality and filter on missing_values between 10 and 100: row-1 (etl-batch-1, 2025-06-01, missing=15, total=500), row-2 (etl-batch-1, 2025-06-02, missing=0, total=490), row-3 (etl-batch-2, 2025-06-03, missing=110, total=510), row-4 (etl-batch-2, 2025-06-04, missing=50, total=505), row-5 (etl-batch-1, 2025-06-05, missing=25, total=498).”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-008?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined null coverage quality audit and numeric interval filter on a small-to-medium dataset (up to 200 rows) in a single call for a flat $0.01 USDC fee. It is ideal for data engineering pipelines, ETL validation steps, or ad-hoc data quality checks where you want two analytical outputs (audit + filter) without calling separate services or running external queries.
Side effects
- Missing required fields (row_id, date, missing_values, total_values) cause validation errors
- Exceeding 200 rows returns a row limit error
- Invalid date format (not YYYY-MM-DD) causes a schema validation failure
- Providing minimum greater than maximum may return empty filter results or an error
- Null or non-numeric values in missing_values/total_values may produce unexpected audit results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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