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Validation Rule Results Analytics — Record Quality Audit, String Normalisation & Numeric Interval Filter
x402
Validation Rule Results Analytics — Record Quality Audit, String Normalisation & Numeric Interval Filter 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).
Performs three analytical reports on validation rule result records: record quality audit, string normalisation, and numeric interval filtering of passed_rules/total_rules fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validation rule results — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter 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, (2) string normalisation output for text fields like dataset_group, and (3) a numeric interval filter report identifying rows where the selected field (passed_rules or total_rules) falls within the specified min/max range. All processing is local with no external lookups.
Example use cases
Data pipeline rule compliance audit
“I have a batch of up to 50 validation rule result records from my ETL pipeline — each with a row_id, dataset_group, date, passed_rules, and total_rules. Can you run the full quality audit, normalise the string fields, and filter passed_rules between 5 and 200 to flag anything out of range?”
Dataset group string cleaning
“My validation logs have messy dataset_group strings mixed with passed_rules and total_rules counts. Run string normalisation and a record quality audit on these rows — focus on passed_rules and use a minimum of 0 and maximum of 500.”
Rule pass rate interval check
“I need to filter my rule result records to only those where total_rules falls between 10 and 1000 — can you also run the quality audit alongside that? I have about 80 rows with row_id, date, dataset_group, passed_rules, and total_rules.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-08-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined record quality audit, string normalisation, and numeric interval filter on validation rule result data (passed_rules/total_rules) in a single call. It is ideal for batch data quality checks on up to 200 rows without any external API calls or live lookups. Prefer this over generic data tools when you specifically track rule compliance metrics by dataset group and need all three analytical reports at the cost of a single $0.01 USDC call.
Side effects
- Fewer than 1 or more than 200 rows submitted — rejected with validation error
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) on any row — schema validation failure
- Date field not matching YYYY-MM-DD pattern — rejected
- Minimum value greater than maximum value — may produce empty interval filter results
- Null numeric values for passed_rules or total_rules — may affect numeric filter and audit reports
- Invalid field enum value (not passed_rules or total_rules) — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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