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Join Coverage Record Quality Audit & Numeric Distribution
x402
Join Coverage Record Quality Audit & Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Runs two local analytical reports—record quality audit and numeric distribution—on up to 200 join coverage rows containing matched_rows and source_rows fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + Numeric distribution: Record quality audit + Numeric distribution 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 computed locally: (1) a record quality audit assessing completeness, nulls, and validity of the submitted join coverage rows; and (2) a numeric distribution report for the selected field (matched_rows or source_rows), including statistical summaries such as min, max, mean, percentiles, and frequency distribution across up to 200 rows.
Example use cases
Join pipeline data quality check
“I've got a list of 50 join coverage rows from my ETL pipeline — each has a row_id, dataset_group, date, matched_rows, and source_rows. Can you run a record quality audit and numeric distribution on them, focusing the distribution on source_rows, so I can see if anything looks off?”
Weekly dataset group distribution review
“Every Monday I need to profile our join coverage numbers. Here are this week's 120 rows with matched_rows and source_rows across groups alpha, beta, and gamma — run the quality audit and matched_rows distribution report for me.”
Debugging anomalous match counts
“Something looks wrong with our join coverage — some dataset groups have way more matched_rows than source_rows. Can you run the record quality audit and numeric distribution on these 30 rows so I can spot where the anomalies are?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-004?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, offline data profiling for join coverage datasets without any external lookups or ML predictions — ideal for ETL validation workflows, data quality gates, and auditing matched vs. source row counts across dataset groups. Prefer it over heavier analytics platforms when you have up to 200 rows and need two quick reports (quality audit + numeric distribution) at minimal cost.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required row fields (row_id, dataset_group, date, matched_rows, source_rows) causes a schema validation failure
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- An empty rows array (minItems:1 violated) returns an error
- Invalid field enum value (not 'matched_rows' or 'source_rows') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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