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Validation Rule Results Analytics — String Normalisation + Secondary-Measure Weighted Mean
x402
Validation Rule Results Analytics — String Normalisation + 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 string normalisation and secondary-measure weighted mean statistics for up to 200 rows of validation rule result records (passed_rules, total_rules), delivering two independent analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validation rule results — String normalisation + Secondary-measure weighted mean: String normalisation + 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
Two independent analytical reports: (1) a string normalisation output for the selected measure (passed_rules or total_rules) across the supplied rows, and (2) a secondary-measure weighted mean computation — both derived entirely from the supplied data, with no external lookups or live data.
Example use cases
Data pipeline quality audit
“I have validation results from my ETL pipeline — 50 rows with dataset group, date, passed_rules and total_rules for each run. Can you normalize the passed_rules values and give me the weighted mean so I can see which groups are performing well?”
Compliance rule monitoring dashboard
“Run string normalisation and weighted mean analytics on these 120 compliance rule check records across our three dataset groups — I want to track total_rules as the primary field for the weighted mean report.”
Multi-team data quality benchmarking
“I need to compare validation rule pass rates across our data teams for last quarter. Here are 200 rows of passed_rules and total_rules by team group and date — can you compute the normalisation and secondary-measure weighted mean for passed_rules?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-08-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local analytical computation on validation rule result records (passed_rules / total_rules) without any external data enrichment or live lookup. It is ideal when you want two distinct statistical views — string normalisation plus a weighted mean — delivered as a pair within a single low-cost call. Prefer it for data quality monitoring, compliance pipelines, or ETL audit workflows where the data is already in hand and you need standardised statistical summaries up to 200 rows.
Side effects
- More than 200 rows submitted — request rejected, max 200 rows per call
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- Empty rows array — minimum 1 row required
- Invalid field enum value (must be 'passed_rules' or 'total_rules') — schema error
- Payment of 0.01 USDC not fulfilled — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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