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Third-Party Reviews IQR Outlier Flags + Keyed Dataset Comparison
x402
Third-Party Reviews 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 2026-10-26).
Analyzes up to 200 third-party review records to flag IQR-based outliers and perform a keyed dataset comparison across vendors_reviewed and outstanding_actions fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Third party reviews — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied third party reviews records (vendors_reviewed, outstanding_actions). 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 independent analytical reports: (1) IQR outlier flags identifying which rows have values falling outside the interquartile range for the selected field (vendors_reviewed or outstanding_actions), and (2) a keyed dataset comparison report showing differences between the primary and reference datasets matched by row_id. No external lookups or predictions are made; all analysis is performed locally on the supplied data.
Example use cases
Vendor review audit outlier detection
“I have 120 rows of monthly third-party vendor review data with vendors_reviewed counts and outstanding_actions numbers — can you flag any rows that are IQR outliers in the vendors_reviewed field and also compare this dataset against last quarter's records to highlight rows that have changed?”
Procurement compliance anomaly check
“Run outlier detection on our procurement team's third-party review logs for the outstanding_actions field — I have two datasets, the current one and a reference baseline, both under 200 rows, and I need to know which rows are statistically anomalous and which don't match between the two sets.”
Quarterly vendor scorecard comparison
“Compare our Q3 and Q4 vendor review datasets for any IQR outliers in vendors_reviewed, and tell me which row IDs appear in one dataset but not the other or have significantly different values — both datasets have about 80 rows with date, control_group, vendors_reviewed, and outstanding_actions fields.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-security-24-179?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous IQR-based statistical outlier detection AND a keyed dataset comparison on third-party review data (vendors_reviewed, outstanding_actions) in a single low-cost call. Ideal for batch audit workflows on datasets up to 200 rows where no live data lookup, prediction, or external action is required. Prefer this over general analytics APIs when you specifically need both report types bundled affordably at $0.01 USDC.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, control_group, date, vendors_reviewed, outstanding_actions) cause validation errors
- Null values in the selected numeric field may reduce outlier detection accuracy
- Mismatched row_id keys between primary and reference datasets result in unmatched rows in the comparison report
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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