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Data Reconciliation — String Normalisation + Trailing Mean Series
x402
Data Reconciliation — String Normalisation + 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).
Runs two local analytical reports on supplied reconciliation data: string normalisation of row identifiers and a trailing mean series over source/target totals, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — String normalisation + Trailing mean series: String normalisation + 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
Returns two analytical reports: (1) string-normalised versions of the row identifier fields across the supplied records, and (2) a trailing mean series computed over the chosen field (source_total or target_total) using the specified window size, for up to 200 input rows. No external lookups or live data are used.
Example use cases
Monthly finance reconciliation smoothing
“I've got 120 rows of month-end reconciliation data with source and target totals for November 2025 across three groups — can you run string normalisation on the row labels and compute a trailing mean on target_total with a window of 7?”
Detecting label inconsistencies in ETL output
“Our ETL pipeline produced 80 reconciliation records with messy row_id strings across two dataset groups for Q3 2025 — please normalise the strings and give me a trailing mean series on source_total using a window of 4 so I can spot anomalies.”
Rolling average for daily data feed comparison
“I have 30 daily rows for January 2026 comparing source and target totals for a single dataset group — run string normalisation on the row IDs and give me the trailing mean for source_total with a window of 3.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-028?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two bundled local analytical operations — string normalisation and trailing mean computation — applied to your own supplied reconciliation records without any external data fetching or live predictions. It is cost-effective at $0.01 USDC for both reports on up to 200 rows. Prefer it over general-purpose analytics when the input schema (source_total, target_total, dataset_group, date, row_id) matches your reconciliation data structure exactly.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group, source_total, target_total) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Window size outside 2–200 range is rejected
- Non-numeric values in source_total or target_total fields cause parsing errors
- Fewer rows than the window size may produce incomplete trailing mean output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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