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Join Coverage Record Quality Audit & Category Frequencies
x402
Join Coverage Record Quality Audit & Category Frequencies 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 two local analytical reports on join coverage data: a record quality audit and a category frequency breakdown for matched_rows and source_rows across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + Category frequencies: Record quality audit + Category frequencies 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 issues such as null values, out-of-range counts, or malformed records within the supplied join coverage rows; and (2) a category frequency summary showing how matched_rows and source_rows are distributed across dataset_group values and dates. Both reports are computed locally using shared analytical engines with no external lookups.
Example use cases
ETL pipeline join quality check
“I ran a nightly ETL join and got these results for four rows across two dataset groups — can you audit the record quality and tell me the category frequencies for matched vs source rows? row-1 (group-a, 2026-10-01, source=500, matched=480), row-2 (group-b, 2026-10-01, source=1200, matched=950), row-3 (group-a, 2026-10-02, source=510, matched=500), row-4 (group-b, 2026-10-02, source=1180, matched=1100).”
Data warehouse join coverage audit
“We're validating our data warehouse joins for last quarter — can you run both the record quality audit and category frequency report on these 5 join coverage records across our sales and inventory groups?”
Detecting anomalous match rates by group
“I suspect some dataset groups have unusually high or low match rates in our join output — run a quality audit and frequency breakdown on these 10 rows so I can spot anomalies before we promote the dataset to production.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-006?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, low-cost dual-report analysis on join coverage data — specifically when you want both a record quality audit and category frequency breakdown computed together in a single call for up to 200 rows, with no need for live lookups or external data enrichment.
Side effects
- Supplying more than 200 rows will be rejected — stay within the maxItems limit
- Rows missing required fields (row_id, dataset_group, date, matched_rows, source_rows) will cause validation errors
- Dates not matching YYYY-MM-DD format will fail schema validation
- Numeric values outside the allowed range (-1T to +1T) will be rejected
- Empty rows array will fail minItems constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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