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Join Coverage Analytics: Grouped Numeric Summary + Daily Sum Series
x402
Join Coverage Analytics: Grouped Numeric Summary + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes a grouped numeric summary and a daily sum time series for join coverage data (matched_rows, source_rows) across up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Grouped numeric summary + Daily sum series: Grouped numeric summary + Daily sum 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
Returns two independent analytical reports: (1) a grouped numeric summary breaking down the selected field (matched_rows or source_rows) by dataset_group, including descriptive statistics; and (2) a daily sum time series showing the total of the selected field aggregated by date across all supplied rows. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
ETL pipeline join coverage audit
“I have daily join coverage logs for two dataset groups over the past week — can you give me a grouped numeric summary and daily sum series for matched_rows? Here are the records: row-1 on 2026-10-01, matched_rows=10, source_rows=100, group-a; row-2 on 2026-10-02, matched_rows=15, source_rows=110, group-a; row-3 on 2026-10-01, matched_rows=8, source_rows=90, group-b; row-4 on 2026-10-02, matched_rows=12, source_rows=95, group-b.”
Source row volume trend by group
“Can you compute the daily sum series and grouped summary for source_rows across these 5 join coverage records? row-1 on 2026-11-01, source_rows=500, matched_rows=450, group-finance; row-2 on 2026-11-02, source_rows=600, matched_rows=580, group-finance; row-3 on 2026-11-01, source_rows=300, matched_rows=290, group-ops; row-4 on 2026-11-02, source_rows=350, matched_rows=340, group-ops; row-5 on 2026-11-03, source_rows=400, matched_rows=385, group-ops — use the source_rows field.”
Data quality monitoring for nightly joins
“Every night our pipeline produces join coverage records — here are last night's 3 records and I need a grouped numeric summary plus daily sum series for matched_rows: row-1 on 2026-12-01, matched_rows=200, source_rows=210, dataset_group=customers; row-2 on 2026-12-01, matched_rows=180, source_rows=195, dataset_group=orders; row-3 on 2026-12-01, matched_rows=90, source_rows=100, dataset_group=inventory.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-089?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have join coverage records with matched_rows and source_rows fields and need both a group-level numeric summary and a date-level daily sum series in a single call. It is ideal for data engineers or analytics pipelines monitoring ETL join quality across dataset groups over time. Prefer it over general-purpose analytics tools when you need a quick, low-cost ($0.01 USDC) dual-report output on up to 200 supplied rows without needing live data lookups or predictions.
Side effects
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Supplying more than 200 rows exceeds the maxItems limit and is rejected
- Null numeric values may be excluded from aggregations or cause incomplete statistics
- Empty rows array (minItems:1 violated) returns an error
- Invalid field enum value (not 'matched_rows' or 'source_rows') causes a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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