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Join Coverage Analytics: Record Quality Audit + Exact Row Deduplication + Equal-Width Histogram
x402
Join Coverage Analytics: Record Quality Audit + Exact Row Deduplication + 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 2026-10-24).
Runs three local analytical reports (record quality audit, exact row deduplication, and equal-width histogram) 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 + Exact row deduplication + Equal-width histogram: Record quality audit + Exact row deduplication + Equal-width histogram for supplied join coverage records (matched_rows, source_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports: (1) a record quality audit flagging nulls, type issues, and anomalies in matched_rows/source_rows; (2) an exact row deduplication report identifying and removing duplicate records; and (3) an equal-width histogram of the selected numeric field (matched_rows or source_rows) binned into the specified number of bins. All computed locally without external lookups.
Example use cases
Join coverage data quality check
“I have 50 join coverage records with matched_rows and source_rows for several dataset groups from last quarter — can you audit their quality, deduplicate exact duplicates, and show me a 5-bin histogram of the matched_rows values?”
Detecting duplicates in pipeline join output
“My ETL pipeline produced 120 join coverage rows and I suspect there are duplicates — please run an exact deduplication report and a record quality audit on these rows so I know what to clean up.”
Distribution analysis of source rows
“Can you generate a 10-bin equal-width histogram of the source_rows field across my 80 join coverage records, along with a quality audit so I can see if any values are null or out of range?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-219?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, deduplication, and histogram — on join coverage data (matched_rows, source_rows) in a single low-cost call. It is ideal for lightweight, offline profiling of small-to-medium datasets (up to 200 rows) without requiring external data connections or predictions. Prefer it over general-purpose analytics platforms when you want a fast, deterministic, local analysis at $0.01 per call.
Side effects
- More than 200 rows submitted — request rejected with row count limit error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- bins value outside 1–30 range — parameter validation error
- Empty rows array — minimum item count violation
- Numeric values outside ±1,000,000,000,000 range — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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