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Inventory Administration — Record Quality Audit + Trailing Mean Series
x402
Inventory Administration — Record Quality Audit + 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 2026-10-31).
Runs two local analytical reports on inventory session data: a record quality audit and a trailing mean series for count_sessions or discrepancy_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Inventory administration — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series for supplied inventory administration records (count_sessions, discrepancy_count). 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 derived entirely from the supplied data: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed records across the inventory rows, and (2) a trailing mean series for the selected numeric field (count_sessions or discrepancy_count) computed using the specified window size — all processed locally with no external lookups or predictions.
Example use cases
Warehouse session count smoothing
“I have daily warehouse inventory session counts for two team groups over the past 3 months — can you compute a trailing mean with a window of 14 for the count_sessions field and also flag any record quality issues in the data?”
Discrepancy trend audit for ops team
“Run a record quality audit and a trailing mean series with window 5 on my inventory discrepancy_count data — I've got about 120 rows tagged by team group and date, and I want to see where data quality breaks down and how the discrepancy trend smooths out.”
Monthly inventory QA review
“I need two reports on this month's inventory admin records: a quality audit to catch any bad rows, and a trailing mean series over discrepancy_count using a window of 10 — I have around 30 rows across groups alpha and beta.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-21-010?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two bundled local analytical operations — record quality auditing and trailing mean computation — on inventory administration data (count_sessions, discrepancy_count) in a single cost-efficient call. Ideal for batch offline analysis of up to 200 rows where no live data lookup, external enrichment, or predictive modeling is required.
Side effects
- Fewer than 1 row supplied — minItems validation error
- More than 200 rows supplied — maxItems validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Field value not one of the allowed enum values — schema validation error
- Window size less than 2 or greater than 200 — range validation error
- Null numeric values may reduce trailing mean coverage for affected rows
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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