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Validation Rule Results Analyzer — Record Quality Audit, String Normalisation & Base-100 Series
x402
Validation Rule Results Analyzer — Record Quality Audit, String Normalisation & Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-11).
Runs three local analytical reports (record quality audit, string normalisation, and base-100 index series) on supplied validation rule result records (passed_rules, total_rules) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validation rule results — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied validation rule results records (passed_rules, total_rules). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports for the supplied rows: (1) a record quality audit flagging completeness and consistency issues per row, (2) a string normalisation report cleaning and standardising text fields like row_id and dataset_group, and (3) a base-100 index series for the selected numeric field (passed_rules or total_rules) rebased to 100 at the specified row. All computation is local with no external lookups.
Example use cases
Daily pipeline validation compliance audit
“I have 50 daily validation snapshots across two dataset groups — can you run a record quality audit, string normalisation, and base-100 index series on the passed_rules field, starting the index from the first row? I want to see how compliance has trended over time.”
Spotting rule coverage gaps across groups
“Can you audit these 120 rows of validation results — each row has a row_id, date, dataset_group, passed_rules, and total_rules — and give me the quality audit, string normalisation, and base-100 series reports focusing on total_rules, indexed from row 0?”
Baseline-relative rule pass-rate indexing
“I want to track how my rule pass counts have evolved relative to a specific baseline row — run the record quality audit, string normalisation, and base-100 series on passed_rules for my 80 validation rows, setting the base index at row 10.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-08-201?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical views — quality audit, string normalisation, and base-100 indexing — on validation rule result data (passed_rules, total_rules) in a single low-cost call. It is best suited for offline/batch analysis of up to 200 rows with no need for external lookups, live data, or predictions. Prefer alternatives if you need real-time validation against a live schema, ML-based anomaly detection, or more than 200 rows processed at once.
Side effects
- Fewer than 1 or more than 200 rows submitted — rejected with validation error
- Missing required fields (row_id, date, dataset_group, passed_rules, total_rules) in any row
- Date strings not matching YYYY-MM-DD pattern — rejected by schema validation
- base_index value out of range (must be 0–199 and within actual row count)
- Null values in passed_rules or total_rules may affect numeric index computation
- Payment not included or insufficient — x402 payment required at $0.01 USDC per call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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