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Pipeline Durations — String Normalisation + IQR Outlier Flags
x402
Pipeline Durations — String Normalisation + 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 2026-10-16).
Normalises string fields and flags IQR-based outliers in pipeline duration records (run_seconds, processed_rows), returning two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — String normalisation + IQR outlier flags: String normalisation + 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
Two independent analytical reports: one covering string normalisation results for the dataset_group and date fields, and one identifying IQR-based outlier flags for the selected numeric field (run_seconds or processed_rows), covering up to 200 input rows.
Example use cases
ETL job anomaly detection
“I have a batch of 50 pipeline run logs with run_seconds and processed_rows — can you normalize the dataset_group strings and flag any run_seconds values that are IQR outliers so I know which jobs ran unusually long?”
Data quality audit before dashboard load
“Before I load these 120 pipeline duration records into my dashboard, can you run string normalisation on them and use IQR outlier flagging on processed_rows to surface any rows I should investigate?”
Weekly pipeline performance review
“Here are this week's 80 pipeline execution records — run the IQR outlier analysis on run_seconds and normalize the string fields so I can include the flagged anomalies in my weekly performance report.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and IQR-based outlier detection on pipeline timing metrics (run_seconds, processed_rows) in a single call, without requiring external lookups or live data. Ideal for data engineers auditing ETL logs, validating pipeline batch output quality, or preparing cleaned records for downstream reporting — especially when cost efficiency matters at $0.01 for two reports covering up to 200 rows.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, run_seconds, processed_rows) cause validation errors
- Null-only numeric columns may produce empty or degenerate IQR results
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- All-identical numeric values produce zero IQR, flagging no outliers
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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