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Data Reconciliation — Base-100 Series + IQR Outlier Flags
x402
Data Reconciliation — Base-100 Series + 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 2026-10-23).
Computes a base-100 indexed time series and IQR-based outlier flags for up to 200 source/target reconciliation rows, returning two analytical reports in one call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags for supplied data reconciliation records (source_total, target_total). 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 normalized index series for the chosen field (source_total or target_total) relative to the specified base row, and (2) IQR-based outlier flags for each row indicating which records fall outside the interquartile range — all computed locally from the supplied rows with no external lookups.
Example use cases
Monthly finance reconciliation outlier review
“I have 12 months of source and target revenue totals for our finance team — can you index them to base-100 starting from January (index 0) and flag any months where the source_total looks like a statistical outlier based on IQR?”
Multi-group ETL pipeline data quality check
“We ran an ETL job and I have 50 rows of source vs target counts across 5 dataset groups with dates from 2025-01-01 to 2025-02-19 — please compute the base-100 series and IQR outlier flags on the target_total field so I can spot pipeline anomalies.”
Retail inventory source-target discrepancy analysis
“I've got 30 rows of inventory reconciliation records across two store groups from Q1 2025, each with a source_total and target_total — index the source_total to base-100 from the first row and flag any IQR outliers so I know which dates had unusual discrepancies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-164?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a normalized base-100 time series and IQR outlier detection on reconciliation data in a single low-cost call ($0.01 USDC for both reports). It is ideal for batch analytical tasks on up to 200 pre-aggregated source/target rows where no live data lookup, prediction, or external enrichment is needed — just local statistical computation on data you already have.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, date, dataset_group, source_total, target_total) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- base_index out of range for the number of rows supplied — error response
- All null values in selected field — unable to compute meaningful index or IQR
- Malformed JSON payload — HTTP 400 or parse error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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