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Return Restock Value IQR Outlier Flags
x402
Return Restock Value 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 2026-10-12).
Analyzes retail return restock contribution data for up to 200 records and flags statistical outliers using the interquartile range (IQR) method.
Price / call$0.01
Success—
StatusUnknown
How this service works
Return restock value after processing - IQR outlier flags: IQR outlier flags for Return restock value after processing. 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 rows in the submitted retail return restock dataset are statistical outliers based on interquartile range analysis across the four input fields (returned_units, recoverable_percent, unit_inventory_value, processing_cost).
Example use cases
Flagging anomalous return batches
“I have 20 rows of retail return data with returned units, recoverable percent, unit inventory value, and processing cost — can you run an IQR outlier check on them and tell me which rows are statistical anomalies?”
Validating return data before reporting
“Before I submit our monthly returns report, can you check these 50 return restock records for IQR outliers? I want to catch any entries where processing cost or recoverable percent look statistically extreme.”
Investigating unusual restock cost spikes
“Our return restock costs seem off this quarter. Can you run an IQR outlier analysis on these 15 return records — each has returned units, recoverable percent, unit inventory value, and processing cost — and flag which ones are outside the normal range?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-retail-return-restock-contribution-outliers?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a low-cost, bounded IQR outlier detection report specifically on retail return restock contribution data (returned units, recoverable percent, unit inventory value, processing cost). It is ideal for batch quality-checking up to 200 return records for statistical anomalies without requiring platform access, live rates, or order execution. Not suitable for real-time streaming analysis, order management, or datasets exceeding 200 rows.
Side effects
- Fewer than 2 rows submitted — minimum of 2 rows required
- More than 200 rows submitted — maxItems limit exceeded
- Missing required fields (returned_units, recoverable_percent, unit_inventory_value, or processing_cost) in any row
- Values outside allowed ranges (e.g. recoverable_percent > 100, negative values)
- Additional properties included in row objects — schema is strict (additionalProperties: false)
- Payment not processed — x402 payment required at $0.01 USDC per call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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