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Data Reconciliation — Trailing Mean Series + IQR Outlier Flags
x402
Data Reconciliation — Trailing Mean 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 2026-10-24).
Computes a trailing mean time series and flags IQR-based outliers across source_total and target_total reconciliation records, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Trailing mean series + IQR outlier flags: Trailing mean 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 independent analytical reports: (1) a trailing mean time series computed over the specified window for the chosen field (source_total or target_total), and (2) IQR-based outlier flags per row identifying which records fall outside the interquartile range bounds. Both reports are derived locally from the supplied data with no external lookups.
Example use cases
Financial reconciliation anomaly detection
“I've got 120 rows of daily source and target totals from our accounts reconciliation process — run a trailing mean with a window of 7 and flag any IQR outliers in the target_total so I can see which days had unusual discrepancies.”
ETL pipeline data quality check
“After our nightly ETL run I have source_total and target_total counts per dataset group across 90 dates — can you compute a trailing mean series with window 3 and highlight any IQR outlier rows in source_total to catch data drift?”
Monthly reporting variance review
“Here are 60 rows of reconciliation records across two groups covering the last two months — please generate the trailing mean and IQR outlier flags for source_total with a window of 4 so I can spot which entries are statistically unusual before my report.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-149?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, locally-computed statistical analysis of reconciliation data — specifically trailing moving averages combined with IQR outlier detection — without any external data lookup or prediction. Ideal for data quality workflows where you supply your own source/target totals and want two complementary statistical reports (smoothed trend + anomaly flags) in a single call for under $0.01.
Side effects
- Fewer than 1 row or more than 200 rows submitted — request rejected
- Window size smaller than 2 or larger than 200 — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- source_total or target_total values outside ±1,000,000,000,000 — rejected
- Missing required fields (row_id, dataset_group, date) — request fails
- Payment not received or insufficient USDC — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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