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Render Jobs — Adjacent Row Changes + IQR Outlier Flags
x402
Render Jobs — Adjacent Row Changes + 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).
Analyzes up to 200 render job records for adjacent row changes and IQR-based outlier flags across render_seconds and sample_count fields, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Render jobs — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags for supplied render jobs records (render_seconds, sample_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
Two independent analytical reports for the submitted render job rows: (1) an adjacent row change report showing differences between consecutive render_seconds or sample_count values, and (2) an IQR outlier flag report identifying which rows fall outside the interquartile range bounds — both covering up to 200 input rows.
Example use cases
Render pipeline anomaly audit
“Here are 150 rows of render job data with dates, asset groups, render_seconds, and sample_counts — flag any IQR outliers and show me where render_seconds changed dramatically between adjacent rows.”
Asset group render time QA
“I need to check my render job logs for group-a and group-b over the past month — run both the adjacent row change report and the IQR outlier detection on the sample_count field for these 80 records.”
Daily render duration monitoring
“Can you analyze these 200 render job entries and tell me which render_seconds values are statistical outliers by IQR, and which rows show the biggest jumps compared to the row before them?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-02-157?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular render job records and need both sequential (adjacent row delta) analysis and distribution-based (IQR) outlier detection in a single call — particularly useful for creative pipeline QA, render farm monitoring, or batch audits where you want statistical anomaly flags without any external lookup or ML prediction overhead.
Side effects
- Fewer than 1 or more than 200 rows submitted — request rejected
- Missing required fields (row_id, date, render_seconds, sample_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Null numeric values may reduce outlier detection accuracy
- Field enum value not one of render_seconds or sample_count causes rejection
- Payment of 0.01 USDC not provided results in 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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