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Schema Conformity — Numeric Row Ordering + IQR Outlier Flags
x402
Schema Conformity — Numeric Row Ordering + 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 2026-10-15).
Sorts schema conformity records by numeric value and flags IQR-based outliers across valid_records and checked_records fields for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — Numeric row ordering + IQR outlier flags: Numeric row ordering + 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) rows ordered numerically by the selected field (valid_records or checked_records), and (2) IQR-based outlier flags indicating which rows fall below Q1−1.5×IQR or above Q3+1.5×IQR. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Daily data quality audit
“I have 50 rows of daily schema conformity checks — can you sort them by valid_records and flag any statistical outliers using IQR? Here's the data with row IDs, dataset groups, dates, and both valid_records and checked_records values.”
Detecting anomalous checked_records spikes
“Run an IQR outlier analysis on my checked_records field across these 30 conformity records — I want to see which rows are statistically unusual and how the rows rank numerically.”
Multi-group conformity ranking
“I have schema conformity data across two dataset groups over the past month — can you order all 80 rows by their valid_records value and tell me which ones fall outside the IQR range so I can investigate?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-119?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both numeric ordering and IQR-based outlier detection on schema conformity metrics (valid_records, checked_records) in a single low-cost call. Ideal for data quality pipelines processing up to 200 rows where no live data lookup or ML prediction is needed — purely analytical, deterministic, and runs locally on submitted data.
Side effects
- More than 200 rows submitted — endpoint rejects with error
- Missing required fields (row_id, date, valid_records, checked_records) cause validation failure
- Invalid date format (non-YYYY-MM-DD) triggers pattern validation error
- All null values in selected field produce no meaningful IQR computation
- Empty rows array rejected due to minItems:1 constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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