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Validation Rule Results — Adjacent Row Changes & Secondary-Measure Weighted Mean
x402
Validation Rule Results — Adjacent Row Changes & Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-11).
Computes adjacent row change analysis and secondary-measure weighted mean for validation rule result records (passed_rules, total_rules) on up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validation rule results — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean for supplied validation rule results records (passed_rules, total_rules). 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 for the supplied rows: (1) an adjacent row changes report showing delta values between consecutive rows for the selected field (passed_rules or total_rules), and (2) a secondary-measure weighted mean report computing the weighted average of the selected field using the other measure as the weight. Results are computed locally against the supplied data with no external lookups.
Example use cases
Data quality trend monitoring
“I have daily validation results for two dataset groups over the past month — each row has a date, passed_rules, and total_rules. Can you analyze the adjacent row changes and compute the weighted mean for passed_rules across all 150 rows?”
Compliance audit statistical summary
“I need a weighted mean of our passed_rules values weighted by total_rules, plus a row-by-row change breakdown, for a compliance audit dataset I have with 80 records across three groups.”
Detecting validation anomalies over time
“Can you check my 60-row validation results dataset for adjacent row changes in total_rules by date and dataset group, so I can spot where the number of rules being evaluated jumped unexpectedly?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-08-159?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular validation rule result data (with passed_rules and total_rules columns) and need both a row-by-row change analysis and a weighted mean statistic computed together in a single low-cost call. Ideal for data quality monitoring workflows, compliance audits, or pipeline health checks where you want local statistical analysis without external data lookups or predictions. Best suited for datasets 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, passed_rules, total_rules) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Null values in passed_rules or total_rules may affect weighted mean calculation
- Invalid field selector (not 'passed_rules' or 'total_rules') causes enum validation failure
- Empty rows array rejected (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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