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Join Coverage IQR Outlier Flags + Keyed Dataset Comparison
x402
Join Coverage IQR Outlier Flags + Keyed Dataset Comparison 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).
Runs two analytical reports on join coverage data: IQR-based outlier detection and a keyed comparison between two datasets, for up to 200 rows of matched_rows/source_rows records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied join coverage records (matched_rows, source_rows). 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) IQR outlier flags identifying which rows have matched_rows or source_rows values outside the interquartile range, and (2) a keyed dataset comparison highlighting differences between the primary and reference datasets matched by row_id and dataset_group. No external lookups or predictions are made — all analysis is performed locally on the supplied data.
Example use cases
Pipeline join anomaly detection
“I'm running a nightly ETL and want to flag any days where matched_rows looks like an outlier using IQR — here's my join coverage table with row_id, date, dataset_group, matched_rows, and source_rows for the past 30 days. Also compare it against last month's equivalent data to see what changed.”
Cross-environment join coverage audit
“We have join coverage metrics from our staging and production environments — can you run an IQR outlier check on source_rows and then do a keyed comparison between the two environments to spot any discrepancies? Both datasets have the same row_id and dataset_group keys.”
Data quality regression check after schema change
“After our schema migration last week, I want to check whether our join coverage numbers shifted — please flag any IQR outliers in matched_rows across my two dataset snapshots (before and after migration) and give me a keyed comparison report so I can see exactly which rows changed.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-179?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier detection and a keyed dataset comparison on join coverage metrics (matched_rows, source_rows) in a single low-cost call. Ideal for data engineers auditing ETL pipeline join completeness, comparing snapshots across time periods or environments, and flagging statistical anomalies — all without sending data to external ML services or live lookup systems.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds limit, request rejected
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Mismatched keys between primary and other datasets — comparison report may show all rows as unmatched
- Null values in the selected field — outlier detection may skip or flag those rows
- Payment not included or insufficient — x402 payment required at $0.01 USDC
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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