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Pipeline Durations — Daily Sum Series + IQR Outlier Flags
x402
Pipeline Durations — Daily Sum Series + 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 2026-10-24).
Computes daily sum time series and IQR-based outlier flags for supplied pipeline duration records (run_seconds or processed_rows), returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied pipeline durations records (run_seconds, processed_rows). 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
Returns two independent analytical reports: (1) a daily sum time series aggregating the selected metric (run_seconds or processed_rows) by date, and (2) IQR-based outlier flags identifying which dates or records fall outside the interquartile range. Both reports are computed locally without external lookups.
Example use cases
ETL pipeline anomaly detection
“I have a list of ETL job runs over the past month with run_seconds and processed_rows per day — can you compute daily sums and flag any days that look like outliers based on IQR? Use the run_seconds field.”
Data throughput daily summary
“Here are 120 pipeline execution records across multiple dataset groups — give me a daily sum series for processed_rows and highlight which days had abnormally high or low counts using IQR outlier detection.”
Multi-group pipeline performance audit
“I want to audit our pipeline durations across two dataset groups over the last quarter — can you aggregate run_seconds by day and tell me which days were statistical outliers using IQR flagging?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-140?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw pipeline execution records (with run_seconds and/or processed_rows) and need both a daily aggregated time series and statistical outlier detection in a single call, without requiring external data sources or live system access. Ideal for post-hoc batch job analysis of up to 200 records.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group, run_seconds, processed_rows) cause validation errors
- Invalid date format (must be YYYY-MM-DD) triggers schema rejection
- Null values in the selected metric field may affect IQR calculation accuracy
- Too few data points to compute meaningful IQR statistics (edge case with very small datasets)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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