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On-time Dispatch Share IQR Outlier Flags
x402
On-time Dispatch 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 2026-10-17).
Detects IQR-based statistical outliers in retail on-time dispatch share data across up to 200 records
Price / call$0.01
Success—
StatusUnknown
How this service works
On-time dispatch share - IQR outlier flags: IQR outlier flags for On-time dispatch 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 with IQR outlier flags for each submitted row, indicating which on-time dispatch share values fall outside the interquartile range. Each record receives a flag denoting whether it is a statistical outlier relative to the submitted dataset.
Example use cases
Retail logistics anomaly audit
“I have dispatch records for 8 of our retail distribution centers — can you flag which ones have statistically unusual on-time rates using IQR analysis? Here are the numbers: 500 dispatches/460 on-time, 480/441, 510/469, 490/200, 520/478, 505/464, 495/455, 515/473.”
Supplier punctuality outlier screening
“We get dispatch data from 12 retail suppliers every week. Can you run IQR outlier flagging on this week's on-time dispatch figures to spot which suppliers are way outside the normal range? I'll paste the dispatches and on-time counts for each.”
Weekly dispatch performance QA check
“Before I submit our weekly dispatch performance report, can you check these 15 store records for IQR outliers in on-time dispatch share? I want to catch any data entry errors or genuinely anomalous locations before the report goes out.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-retail-dispatch-on-time-outliers?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, cost-effective IQR-based statistical outlier detection specifically on retail on-time dispatch share data (up to 200 records). It is purpose-built for this metric rather than a generic statistics API, making it appropriate for logistics QA workflows, supplier audits, or pre-reporting data validation where dispatch punctuality is the key KPI.
Side effects
- Fewer than 2 rows submitted — minimum input requirement not met
- Row missing required 'dispatches' or 'on_time_dispatches' fields — validation error
- 'dispatches' value is 0 or negative — excluded by schema minimum (exclusiveMinimum: 0)
- More than 200 rows submitted — exceeds maxItems limit
- Payment of 0.01 USDC not completed — request rejected
- Non-numeric values in numeric fields — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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