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Replenishment Timing — String Normalisation + Base-100 Series
x402
Replenishment Timing — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Runs two analytical reports on supplied replenishment timing data: string normalisation of text fields and a base-100 indexed series for either lead_days or received_units.
Price / call$0.01
Success—
StatusUnknown
How this service works
Replenishment timing — String normalisation + Base-100 series: String normalisation + Base-100 series for supplied replenishment timing records (lead_days, received_units). 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: (1) a string normalisation report cleaning text fields such as store_group across all supplied rows, and (2) a base-100 indexed numeric series for the selected field (lead_days or received_units) anchored at the specified base_index row — covering up to 200 input rows per call.
Example use cases
Lead time index for retail planning
“I've got 150 rows of replenishment timing data with store_group, date, and lead_days — please normalise the string fields and create a base-100 index series for lead_days starting from row 0 so I can compare lead time changes over time.”
Received units trend baseline analysis
“Can you take my 80-row replenishment dataset with received_units by store group and date, normalise the store group strings, and build a base-100 series for received_units anchored at row index 5?”
Multi-store replenishment data cleanup
“I have replenishment records across groups like 'group-a' and 'group-B' with inconsistent capitalisation — run string normalisation and give me a base-100 indexed series for lead_days from row index 0 across all 120 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-12-030?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of retail replenishment timing records (with lead_days and/or received_units) and need both string normalisation of categorical fields and a base-100 indexed time series in a single low-cost call. It is ideal for offline batch analytics on supplied data without requiring external lookups or live data connections.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, store_group, date, lead_days, received_units) on any row causes validation failure
- Invalid date format (must match YYYY-MM-DD pattern)
- base_index out of range (must be between 0 and 199 and within actual row count)
- Numeric field values outside allowed range (±1,000,000,000,000)
- All-null values for the selected numeric field may produce an empty or degenerate series
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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