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Minimum-Stock Replenishment Gap - IQR Outlier Flags
x402
Minimum-Stock Replenishment Gap - IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Detects IQR-based outlier records in minimum-stock replenishment gap calculations for up to 200 retail inventory rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Minimum-stock replenishment gap - IQR outlier flags: IQR outlier flags for Minimum-stock replenishment gap. Supplied retail figures only, up to 200 records. No platform access, live rates or order execution. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded iqr outlier flags report.
Output
A bounded IQR outlier flags report identifying which of the submitted retail inventory rows fall outside 1.5× the interquartile range for the computed minimum-stock replenishment gap. Each record is flagged or not flagged, allowing users to pinpoint statistically anomalous observations across up to 200 rows.
Example use cases
Retail SKU anomaly detection
“I have 50 SKU records with their minimum stock levels, current available units, and inbound units — can you run IQR outlier detection on them to find which SKUs have unusually large or small replenishment gaps?”
Warehouse replenishment audit
“We're auditing our warehouse replenishment process and I want to flag any statistically unusual rows in our stock data. Here are 120 records each with minimum_units, available_units, and inbound_units — which ones are IQR outliers?”
Inventory health spot-check
“Before our inventory review meeting, can you check these 30 store-level stock records for outlier replenishment gaps using IQR flagging? Each record has minimum units, available units, and inbound units values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-retail-minimum-stock-gap-outliers?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, cheap ($0.01 USDC) statistical outlier detection specifically for retail inventory replenishment gaps using the IQR method, on a batch of up to 200 records with minimum, available, and inbound unit counts. It is not a substitute for live inventory systems, order execution, or platform integrations — it is purely a statistical computation layer over supplied figures.
Side effects
- Fewer than 2 rows supplied — minimum array length not met
- Row missing required field (minimum_units, available_units, or inbound_units) — validation error
- More than 200 rows submitted — exceeds maxItems limit
- Non-numeric values in numeric fields — schema validation failure
- All rows identical — IQR of zero may produce trivial or unexpected flagging behavior
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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