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Join Coverage Record Quality Audit and Equal-Width Histogram
x402
Join Coverage Record Quality Audit and Equal-Width Histogram 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).
Runs a record quality audit and an equal-width histogram analysis on join coverage data (matched_rows, source_rows) for up to 200 rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram 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
Two analytical reports: (1) a record quality audit identifying missing values, nulls, and data issues in the supplied join coverage records; and (2) an equal-width histogram of the selected field (matched_rows or source_rows) divided into the specified number of bins, summarizing value distribution across the dataset.
Example use cases
ETL pipeline join coverage audit
“I need a quality audit and a histogram with 8 bins on matched_rows for my ETL join coverage — here are 120 rows across three dataset groups: 'sales', 'inventory', and 'returns', dated from 2024-01-01 to 2024-03-31. Can you run both reports?”
Detecting nulls in source row counts
“Can you check the record quality of my join coverage data for nulls and bad values in the source_rows field, and also give me a 5-bin histogram? I've got 60 rows across two groups, 'users' and 'events'.”
Daily coverage distribution summary
“I want to analyze the distribution of matched_rows in my daily join coverage dataset — run a 15-bin equal-width histogram and a quality audit across 200 rows for dataset group 'transactions' from 2024-06-01 through 2024-06-30.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-013?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a histogram distribution analysis on join coverage data (matched_rows and source_rows) in a single low-cost call. It is ideal for data engineers and analysts who want to assess join completeness and detect anomalies in batch form for up to 200 rows without needing external lookups, predictions, or live data connections.
Side effects
- Fewer than 1 row submitted returns a validation error
- More than 200 rows submitted exceeds the row limit
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- bins value outside 1–30 range returns a validation error
- Non-numeric values in matched_rows or source_rows where numbers are required may cause computation failure
- Missing required fields (row_id, dataset_group, date) cause schema validation errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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