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Data Reconciliation Analytics — Numeric Distribution + Trailing Mean Series
x402
Data Reconciliation Analytics — Numeric Distribution + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes numeric distribution statistics and a trailing mean time series for source_total and target_total reconciliation data, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series 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
Two analytical reports computed locally from the supplied rows: (1) a numeric distribution report showing descriptive statistics (e.g. min, max, mean, median, spread) for the chosen field across all rows; and (2) a trailing mean series showing rolling averages over the specified window size, indexed by date. Both reports are derived purely from the input data with no external lookups.
Example use cases
ETL pipeline reconciliation health check
“I have 50 daily reconciliation records comparing our data warehouse source_total to the target_total after ETL. Can you run the numeric distribution and trailing mean series with a window of 7 on the source_total field so I can see if there's drift or skew?”
Finance team source-vs-target variance profiling
“Our finance team needs to profile this quarter's reconciliation data — 120 rows across two dataset groups, each with a source_total and target_total. Please compute both the numeric distribution and the trailing mean series using target_total and a window of 5 so we can spot outliers.”
Data quality audit across grouped datasets
“I'm auditing data quality for two dataset groups over the past 90 days. Here are 90 reconciliation rows with source_total and target_total values — run the numeric distribution report and a trailing mean series with window size 10 on source_total so I can compare trends across groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-076?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a distributional profile and a rolling mean time series from reconciliation records in a single low-cost call. It is ideal for ETL validation, financial data quality audits, or any workflow comparing source vs target totals across time-stamped, grouped rows — without needing external data, predictions, or live lookups. Prefer it over general-purpose analytics tools when you want a lightweight, deterministic, offline computation on up to 200 rows at minimal cost.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds maximum batch size
- Missing required fields (row_id, dataset_group, date, source_total, target_total) on any row
- Invalid date format — must match YYYY-MM-DD pattern
- Window size less than 2 or greater than 200
- source_total or target_total outside the range -1,000,000,000,000 to 1,000,000,000,000
- Payment failure — 0.01 USDC not received or insufficient balance
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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