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Pipeline Durations — Numeric Interval Filter + Daily Sum Series
x402
Pipeline Durations — Numeric Interval Filter + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Filters pipeline duration records by a numeric range on a chosen metric and computes a daily sum time series, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — Numeric interval filter + Daily sum series: Numeric interval filter + Daily sum series 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 analytical reports: (1) the subset of pipeline records whose chosen metric (run_seconds or processed_rows) falls within the specified [minimum, maximum] interval, and (2) a daily sum series aggregating that metric by date across all input records (up to 200 rows). Both reports are computed locally with no external lookups.
Example use cases
ETL job duration range analysis
“Here are my pipeline run logs for October — filter them to only jobs where run_seconds is between 10 and 120, then show me the daily total run time as a time series.”
Processed rows daily throughput check
“I've got 200 pipeline records with processed_rows data — can you filter to rows where processed_rows is between 1000 and 50000 and compute the daily sum of processed_rows across those records?”
Outlier exclusion before daily aggregation
“I want to exclude very short and very long pipeline runs — keep only records where run_seconds is between 30 and 300 and give me the daily summed run_seconds so I can spot trends.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-125?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a numeric range filter and a daily sum aggregation on pipeline duration data (run_seconds or processed_rows) in a single low-cost call. It is ideal for ETL monitoring, pipeline performance analysis, and time series trend detection without requiring any external data source or prediction. Best when your dataset is already collected and has up to 200 rows; it is not suitable for live streaming data, machine learning predictions, or datasets requiring external enrichment.
Side effects
- Fewer than 1 row supplied — request rejected (minItems:1)
- More than 200 rows supplied — request rejected (maxItems:200)
- Invalid date format (not YYYY-MM-DD) — validation error
- Field value not in enum ['run_seconds','processed_rows'] — validation error
- Minimum greater than maximum — may produce empty interval filter result
- Null metric values included — nulls excluded from numeric filter and sum computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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