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Join Coverage Record Quality Audit and Base-100 Series
x402
Join Coverage Record Quality Audit and Base-100 Series 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 analytical reports on join coverage data — a record quality audit and a Base-100 index series — for up to 200 rows of matched_rows/source_rows data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Record quality audit + Base-100 series: Record quality audit + Base-100 series 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 independent analytical reports for the supplied join coverage rows: (1) a record quality audit flagging anomalies, nulls, or inconsistencies in the matched_rows/source_rows data; and (2) a Base-100 index series normalizing the selected field relative to the specified baseline row — all computed locally without external lookups.
Example use cases
ETL join quality audit
“I have 50 rows of daily join coverage results across two dataset groups with matched_rows and source_rows counts — can you run a record quality audit and Base-100 series on them using matched_rows as the field and row 0 as the base?”
Baseline indexing for coverage trends
“Run a Base-100 index series on my join coverage data for dataset group 'orders' across the last 30 days, using source_rows as the field and index 0 as the baseline, so I can see how coverage has shifted over time.”
Detecting anomalies in matched row counts
“I want to audit the data quality of my join coverage records — I've got 120 rows with matched_rows and source_rows values across groups A and B. Can you run both the record quality audit and Base-100 report, using matched_rows and base index 0?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-012?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have join coverage data (matched_rows and source_rows) and need both a record-level quality audit and a Base-100 normalization series in a single $0.01 call, without requiring external data sources, live lookups, or predictions. Ideal for ETL validation workflows, data pipeline monitoring, and coverage trend analysis on batches up to 200 rows.
Side effects
- More than 200 rows supplied — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors
- base_index out of range (must be 0–199 and within the supplied row count)
- Null values in the selected field may affect Base-100 indexing
- Invalid date format (must be YYYY-MM-DD) causes schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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