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Request Latency IQR Outlier Flags and Two-Measure Correlation
x402
Request Latency IQR Outlier Flags and Two-Measure Correlation 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).
Analyzes supplied request latency records to flag IQR outliers and compute correlation between latency_ms and request_count, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Request latency — IQR outlier flags + Two-measure correlation: IQR outlier flags + Two-measure correlation for supplied request latency records (latency_ms, request_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
Returns two analytical reports: (1) per-row IQR outlier flags indicating which latency_ms values fall outside the interquartile range, and (2) a two-measure correlation result between latency_ms and request_count across the supplied dataset. No external data is fetched; analysis is performed entirely on the supplied rows.
Example use cases
API latency spike investigation
“I have 150 rows of daily request latency data per microservice component — can you flag which latency_ms values are IQR outliers and tell me if there's a correlation between latency and request_count? I'll share the rows with row_id, component, date, latency_ms, and request_count.”
Performance regression audit
“After our last deployment I want to check if any request latency records are statistical outliers using IQR and whether request volume is correlated with slower response times — here are the latency records for the past 30 days across components A, B, and C.”
SLA monitoring data review
“Can you analyze these request latency records for two things: which rows have latency_ms values that are IQR outliers, and what's the correlation between latency_ms and request_count across all 80 rows I'm sending?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-03-176?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of request latency records and need both IQR-based outlier detection and a statistical correlation between latency and request count in a single low-cost call. It is ideal for lightweight, offline statistical analysis of performance data without requiring a full analytics platform or live monitoring system. Prefer it over general-purpose analytics when cost efficiency ($0.01 for two reports) and simplicity matter.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, date, latency_ms, request_count) cause validation errors
- Null or non-numeric latency_ms or request_count values may reduce correlation accuracy or be excluded
- Date strings not matching YYYY-MM-DD pattern will fail schema validation
- Too few rows for meaningful IQR or correlation computation may produce degenerate results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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