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Pipeline Durations Trailing Mean + IQR Outlier Flags
x402
Pipeline Durations Trailing Mean + 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 2026-10-22).
Computes a trailing mean time series and flags IQR-based outliers for supplied pipeline duration records (run_seconds and processed_rows).
Price / call$0.01
Success—
StatusUnknown
How this service works
Pipeline durations — Trailing mean series + IQR outlier flags: Trailing mean 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 trailing mean time series for the selected field (run_seconds or processed_rows) computed over the specified rolling window, and (2) IQR-based outlier flags identifying which records fall outside the interquartile fence. Results are computed locally from the supplied data — no external lookups are made. Up to 200 rows and 2 reports per call.
Example use cases
Spot slow ETL jobs over time
“I have a week of nightly ETL run logs — can you compute a trailing mean with window 3 and flag any runs where run_seconds looks like an IQR outlier? Here are 7 rows: row-1 2024-03-01 pipeline-A 340s 12000 rows, row-2 2024-03-02 pipeline-A 355s 11800 rows, row-3 2024-03-03 pipeline-A 2100s 12100 rows, row-4 2024-03-04 pipeline-A 360s 11900 rows, row-5 2024-03-05 pipeline-A 345s 12050 rows, row-6 2024-03-06 pipeline-A 370s 11750 rows, row-7 2024-03-07 pipeline-A 350s 12000 rows.”
Monitor throughput anomalies by dataset group
“Can you run trailing mean and IQR outlier detection on processed_rows for these pipeline runs with a window of 4? I have two groups: group-x and group-y with 8 records from 2024-05-01 to 2024-05-08 — some runs processed suspiciously few rows and I want them flagged.”
Daily pipeline health report for ops team
“Every morning I want to check if yesterday's pipeline runs were normal — here are 10 rows of run data across groups prod-ingest and prod-transform with dates from 2024-06-01 to 2024-06-10. Use a trailing window of 5 and flag outliers on run_seconds so I can see which runs were unusually long.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-05-149?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw pipeline duration records (up to 200 rows) and need both a trailing mean trend line and IQR-based anomaly flags computed together in one call without any external data sources. It is ideal for lightweight, self-contained statistical analysis of ETL or batch job performance data where you supply all the data and need fast, reproducible results. Prefer this over general-purpose analytics platforms when you want a simple pay-per-call micro-analysis with no setup.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds maximum limit
- Window size larger than the number of supplied rows — trailing mean cannot be computed
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- run_seconds or processed_rows values outside allowed numeric range
- Missing required fields row_id, dataset_group, date, run_seconds, or processed_rows — schema validation error
- Invalid field enum value — must be 'run_seconds' or 'processed_rows'
- Payment not included or insufficient — x402 payment of 0.01 USDC required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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