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Join Coverage Analytics: Category Frequencies + Keyed Dataset Comparison
x402
Join Coverage Analytics: Category Frequencies + Keyed Dataset Comparison 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).
Analyzes join coverage records (matched_rows, source_rows) by computing category frequencies and performing a keyed dataset comparison between two supplied datasets of up to 200 rows each.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Category frequencies + Keyed dataset comparison: Category frequencies + Keyed dataset comparison 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 category frequencies report showing how join coverage records are distributed across dataset_group categories, and (2) a keyed dataset comparison report highlighting differences between the 'rows' and 'other' datasets matched by row_id, covering matched_rows and source_rows values. All analysis is performed locally on the supplied data with no external lookups.
Example use cases
ETL pipeline join audit
“I have two snapshots of my ETL join results from last month — the original run and a reprocessed version. Each has up to 150 rows with row_id, date, dataset_group, matched_rows, and source_rows. Can you compute category frequencies for each group and compare the two snapshots row-by-row to show me where matched_rows differ?”
Data migration coverage check
“After migrating our customer data, I want to verify join coverage. I have the pre-migration and post-migration records — about 80 rows each — with matched_rows and source_rows per group. Can you analyze category frequencies by dataset_group and compare the two datasets keyed by row_id to surface any coverage gaps?”
Weekly join quality monitoring
“Every week I track join coverage for two data feeds — group-a and group-b — and I want to compare this week's results against last week's. I've got about 50 rows for each week with matched_rows and source_rows. Can you give me category frequencies for both groups and a side-by-side keyed comparison showing where coverage changed?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-111?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two sets of join coverage records (matched_rows, source_rows, dataset_group, date) and need both a categorical frequency profile and a keyed row-by-row comparison in a single low-cost call. It is ideal for data engineers and analysts auditing ETL join completeness, comparing dataset snapshots, or monitoring join quality over time — all without needing an external database or prediction service. Best when datasets are under 200 rows and you want two complementary analytical perspectives in one request for $0.01.
Side effects
- Exceeding 200 rows in either dataset returns a validation error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) causes schema rejection
- Malformed date strings not matching YYYY-MM-DD pattern cause input validation failure
- Supplying fewer than 1 row in either array triggers a minItems error
- Numeric values outside ±1,000,000,000,000 range are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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