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Returns Handling Analytics — String Normalisation & Daily Sum Series
x402
Returns Handling Analytics — String Normalisation & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs two local analytical reports on retail returns data: string normalisation of store/group labels and a daily sum time series for returned_units or processing_minutes (up to 200 rows).
Price / call$0.01
Success—
StatusUnknown
How this service works
Returns handling — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied returns handling records (returned_units, processing_minutes). 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-normalized version of the store_group labels from the submitted rows, and (2) a daily sum time series for the selected numeric field (returned_units or processing_minutes), aggregating values by date across all submitted rows. Both reports are computed locally with no external lookups.
Example use cases
Daily returns volume trend by store
“Here are 150 rows of our returns data with dates, store groups, and returned_units — can you normalize the store group names and build me a daily sum series for returned_units so I can see our return volume trend over time?”
Processing time aggregation for ops review
“I've got a returns handling log with 80 records including date, store_group, and processing_minutes — please normalize the store labels and give me a daily total of processing_minutes so I can review operational throughput day by day.”
Cleaning mixed-case group labels for reporting
“Our returns export has inconsistent capitalization in the store_group field across 60 rows — run string normalization on those labels and also give me the daily sum series for returned_units so I can feed clean data into our weekly report.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-04-027?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalization of retail store/group label fields AND a daily sum time series for returns metrics in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want offline, deterministic computation with no external data dependencies. It is not suitable for real-time lookups, predictive analytics, or datasets exceeding 200 rows.
Side effects
- Fewer than 1 row submitted returns a validation error
- More than 200 rows submitted exceeds the row limit and is rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in the selected numeric field may affect sum accuracy
- Unrecognized field enum value causes rejection
- Missing required fields (row_id, date, store_group) cause per-row errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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