{"uid":"cap_bm79UwgStzp2wgtIlRLCu","slug":"request-latency-iqr-outlier-flags-and-two-measure-correlation-a1ebd086","name":"Request Latency IQR Outlier Flags and Two-Measure Correlation","description":"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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-software-03-176?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","component","date","latency_ms","request_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"component":{"type":"string","default":"","maxLength":80},"latency_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"request_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","component":"group-a","latency_ms":10,"request_count":1},{"date":"2026-10-02","row_id":"row-2","component":"group-b","latency_ms":20,"request_count":2},{"date":"2026-10-03","row_id":"row-3","component":"group-a","latency_ms":15,"request_count":3},{"date":"2026-10-04","row_id":"row-4","component":"group-b","latency_ms":30,"request_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["latency_ms","request_count"],"type":"string","default":"latency_ms"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_WYqGB4wQxgYDIA37zjJQS","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"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.","exampleAgentPrompt":"Can you run IQR outlier flagging and a two-measure correlation between latency_ms and request_count on my request latency dataset — here are my rows with row_id, component, date, latency_ms, and request_count for up to 200 records?","exampleUseCases":[{"title":"API latency spike investigation","prompt":"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."},{"title":"Performance regression audit","prompt":"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."},{"title":"SLA monitoring data review","prompt":"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?"}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:52:21.730Z","isFirstParty":false,"canonicalSlug":"request-latency-iqr-outlier-flags-and-two-measure-correlation-a1ebd086"}