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Render Jobs Quality Audit & IQR Outlier Detection
x402
Render Jobs Quality Audit & IQR Outlier Detection 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).
Runs a record-level quality audit and IQR-based outlier flagging on up to 200 render job rows (render_seconds, sample_count), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Render jobs — Record quality audit + IQR outlier flags: Record quality audit + 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: (1) a record-level quality audit covering issues such as missing values, invalid ranges, and formatting problems for each row; and (2) IQR-based outlier flags per row for the selected numeric field (render_seconds or sample_count), identifying which records fall outside the interquartile range bounds. Results are computed locally with no external data lookups.
Example use cases
Render pipeline data quality audit
“I have a batch of 120 render job records with render_seconds and sample_count fields — can you run a quality audit and flag any rows that look like IQR outliers in render_seconds?”
Detect anomalous sample counts in asset groups
“I exported 80 render job logs across two asset groups, group-alpha and group-beta, from last week. Can you audit the data quality and flag any outliers in sample_count using IQR?”
Pre-delivery render data validation
“Before I hand off this render job dataset to the client, can you check it for quality issues and identify any statistically unusual values in render_seconds across all 150 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-02-014?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, inexpensive ($0.01 USDC) offline quality audit and IQR outlier detection on render job data specifically containing render_seconds and sample_count fields, with up to 200 rows, and no need for external data enrichment, predictions, or live lookups. Ideal for validating render pipeline exports before downstream processing.
Side effects
- Fewer than 1 row submitted returns a validation error
- More than 200 rows submitted exceeds the batch limit
- Missing required fields (row_id, date, render_seconds, sample_count) cause row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- All-null numeric column prevents IQR computation
- Payment not processed causes x402 payment-required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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