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Validation Rule Results — IQR Outlier Flags + Secondary-Measure Weighted Mean
x402
Validation Rule Results — IQR Outlier Flags + 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 2026-10-14).
Runs two local statistical analyses on validation rule result records: IQR-based outlier detection and a secondary-measure weighted mean, returning both reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validation rule results — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + 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 statistical reports for the supplied rows: (1) IQR outlier flags per row indicating which records fall outside the interquartile range for the selected field, and (2) a secondary-measure weighted mean computed across the supplied data. Both reports are computed locally with no external lookups.
Example use cases
Flag anomalous data quality check rows
“I have a batch of 50 daily validation snapshots with passed_rules and total_rules for several dataset groups — can you run IQR outlier flagging and a weighted mean on passed_rules to see which days had unusually low rule pass rates?”
Compare rule compliance across dataset groups
“For my two dataset groups, alpha and beta, I've got 30 rows of validation results from last quarter. Run both the IQR outlier flags and the secondary-measure weighted mean on total_rules so I can see which groups are behaving abnormally.”
Monitor pipeline health after a schema migration
“We just migrated our data pipeline and I want to check if any of the 80 post-migration validation result rows are outliers — use IQR outlier detection and the weighted mean on passed_rules across all dataset groups to surface anything suspicious.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-08-177?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 validation rule result records and need both IQR-based outlier detection and a weighted mean in a single paid call. Ideal for data quality monitoring workflows where you want statistical anomaly flagging on pass/fail rule metrics without any external data fetching or model inference. Prefer this over generic stats tools when your data is already structured as passed_rules and total_rules per group and date.
Side effects
- Fewer than 1 row supplied — minimum item count not met
- More than 200 rows supplied — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) on any row
- Date field does not match YYYY-MM-DD pattern — validation error
- Numeric values outside allowed range (±1,000,000,000,000)
- Invalid field enum value — must be 'passed_rules' or 'total_rules'
- Payment failure — 0.01 USDC not provided via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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