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First-attempt Delivery Share — IQR Outlier Flags
x402
First-attempt Delivery Share — 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 2026-10-19).
Detects IQR-based statistical outliers in first-attempt delivery share data across up to 200 retail shipment records.
Price / call$0.01
Success—
StatusUnknown
How this service works
First-attempt delivery share - IQR outlier flags: IQR outlier flags for First-attempt delivery share. 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 report containing IQR outlier flags for each submitted record, indicating which rows have first-attempt delivery share values that fall outside the interquartile range of the supplied dataset. Covers up to 200 records of retail delivery figures.
Example use cases
Carrier performance anomaly audit
“I have 50 rows of delivery attempt data from our logistics partner — each row has the number of attempted shipments and how many were delivered on the first try. Can you run IQR outlier detection on it and tell me which rows have abnormally low or high first-attempt delivery rates?”
Retail fulfillment data quality check
“Before I submit our quarterly retail delivery report, can you check these 80 records of attempted shipments and first-attempt deliveries for statistical outliers using IQR? I want to know if any warehouse locations are producing suspicious numbers.”
Last-mile KPI benchmarking cleanup
“We're benchmarking first-attempt delivery share across 120 regional depots. Can you flag the IQR outliers in the dataset — rows where attempted_shipments and first_attempt_deliveries look anomalous compared to the rest — so I can investigate those depots further?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-retail-first-attempt-delivery-outliers?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have retail logistics data with first-attempt delivery counts and want to quickly identify statistical outliers using the interquartile range method without building your own analysis pipeline. It is ideal for data quality checks before reporting, carrier performance audits, or cleaning fulfillment datasets prior to downstream analysis. Best suited for datasets of up to 200 records where a fast, low-cost ($0.01 USDC) bounded outlier report is sufficient.
Side effects
- Fewer than 2 rows submitted — minimum row count not met
- Row count exceeds 200 — maxItems limit exceeded
- attempted_shipments is zero or negative — exclusiveMinimum violation
- Extra fields in row objects — additionalProperties:false rejection
- Malformed numeric values — type validation failure
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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