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Schema Conformity Base-100 Series and IQR Outlier Flags
x402
Schema Conformity Base-100 Series and IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Computes a base-100 indexed time series and IQR-based outlier flags for schema conformity metrics (valid_records, checked_records) across up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags for supplied schema conformity records (valid_records, checked_records). 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 analytical reports: (1) a base-100 indexed time series for the selected field (valid_records or checked_records) relative to the specified base_index row, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range — all computed locally from the supplied data with no external lookups.
Example use cases
Data quality trend monitoring
“I have daily schema conformity logs for two dataset groups over the past month — around 60 rows with valid_records and checked_records. Can you normalize the valid_records to a base-100 index starting from the first row and flag any outliers using IQR?”
Detecting validation anomalies
“I need to find anomalous days in my data pipeline's checked_records counts — here are 120 rows of schema conformity data by date and dataset group. Run IQR outlier detection on the checked_records field and give me the base-100 series too, starting from index 0.”
Comparing conformity across groups
“I've got schema conformity records from two dataset groups over the last quarter, about 90 rows total with date, valid_records, and checked_records. Can you base-100 index the valid_records starting at row 0 and tell me which rows are flagged as outliers by IQR?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-164?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular schema conformity data (valid_records, checked_records) and need both a normalized base-100 trend series and IQR outlier detection in a single call for up to 200 rows. Ideal for data quality monitoring pipelines, audit reporting, and batch anomaly detection without requiring an external analytics platform. Not suitable for live data lookups, predictions, or datasets exceeding 200 rows.
Side effects
- Fewer than 1 row submitted — minimum 1 row required
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, valid_records, checked_records) on any row
- Invalid date format — must match YYYY-MM-DD pattern
- base_index references a row index outside the supplied dataset
- All values null for the selected field — insufficient data for IQR computation
- Invalid field enum value — must be 'valid_records' or 'checked_records'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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