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Join Coverage Analytics: Numeric Distribution + Adjacent Row Changes
x402
Join Coverage Analytics: Numeric Distribution + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Analyzes join coverage data (matched_rows, source_rows) by producing two local analytical reports: a numeric distribution summary and an adjacent row change analysis, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes 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 analytical reports computed locally from the supplied rows: (1) a numeric distribution summary of the selected field (matched_rows or source_rows), including statistics like min, max, mean, percentiles, and frequency; (2) an adjacent row change analysis showing delta values between consecutive rows ordered by date, highlighting increases and decreases in the selected metric. Both reports cover up to 200 input rows.
Example use cases
Pipeline join quality audit
“I have daily join coverage logs for two dataset groups over the past week — can you give me a numeric distribution and row-by-row change report on the matched_rows field so I can see where match rates jumped or dropped?”
ETL anomaly detection review
“Here are 50 rows of source_rows and matched_rows from our nightly ETL job — run both the distribution and adjacent change analysis on source_rows so I can spot any anomalies between consecutive runs.”
Multi-group coverage comparison
“I've got join coverage data across three dataset groups for Q4 — can you profile the numeric distribution and show me where adjacent row changes are largest for the matched_rows column?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-077?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular join coverage data (matched_rows, source_rows) and need both a numeric distribution profile and a sequential row-change analysis in a single low-cost call. It is ideal for pipeline monitoring, ETL auditing, and data quality checks where you want offline/local analytics without external lookups. Prefer this over general-purpose analytics APIs when you specifically need join coverage metrics profiled across dataset groups with no side effects.
Side effects
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) returns a validation error
- Exceeding 200 rows causes rejection — trim input to 200 rows max
- Invalid date format (not YYYY-MM-DD) triggers a schema validation failure
- Empty rows array returns an error — at least 1 row required
- Null numeric values may reduce statistical coverage in distribution report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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