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Validation Rule Results — String Normalisation + Date by Category Pivot
x402
Validation Rule Results — String Normalisation + Date by Category Pivot 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).
Applies string normalisation and a date-by-category pivot analysis to up to 200 validation rule result records (passed_rules, total_rules), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validation rule results — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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
Two independent analytical reports: (1) a string-normalised view of the input validation rule result records, and (2) a date-by-category pivot table aggregating the selected numeric field (passed_rules or total_rules) by date and dataset_group, covering up to 200 input rows.
Example use cases
Daily data quality compliance pivot
“I have 150 rows of validation results from our ETL pipeline across two dataset groups over the past month — can you pivot the passed_rules counts by date and group, and normalise the string fields at the same time?”
Rule coverage audit across dataset groups
“Can you run string normalisation and a date-by-category pivot on these 80 validation rule records using total_rules as the field, so I can see how rule coverage varies by dataset_group over time?”
Pre-reporting validation metric cleanup
“Before I generate our weekly quality report, can you normalise the string fields and produce a date-by-category pivot for my 200 validation rule result rows based on passed_rules?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-08-035?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and a date-by-category pivot on validation rule result data (passed_rules / total_rules) in a single call for up to 200 rows. It is well-suited for data quality reporting pipelines where you want two complementary views — cleaned string data and a time-group breakdown — without external lookups or predictions.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) — row-level or request-level error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Numeric field values outside allowed range — validation error
- Empty rows array — minimum items constraint failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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