{"uid":"cap_Ty4UOknMztgbMF4oBe5eE","slug":"render-jobs-iqr-outlier-flags-two-measure-correlation-28059a11","name":"Render Jobs IQR Outlier Flags + Two-Measure Correlation","description":"Render jobs — IQR outlier flags + Two-measure correlation: IQR outlier flags + Two-measure correlation for supplied render jobs records (render_seconds, sample_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-creative-02-176?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","render_seconds","sample_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"sample_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"render_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","sample_count":1,"render_seconds":10},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","sample_count":2,"render_seconds":20},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","sample_count":3,"render_seconds":15},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","sample_count":4,"render_seconds":30}],"maxItems":200,"minItems":1},"field":{"enum":["render_seconds","sample_count"],"type":"string","default":"render_seconds"}}},"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_iQSglL0YPsKQ6VTx0K3Gv","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":"Computes IQR-based outlier flags and a two-measure Pearson/Spearman correlation report for up to 200 render job records across render_seconds and sample_count.","exampleAgentPrompt":"Can you check my render job logs for outliers and see if render_seconds and sample_count are correlated? Here are the rows: row-1 on 2026-10-01 for group-a with render_seconds=120 and sample_count=50, row-2 on 2026-10-02 for group-b with render_seconds=15 and sample_count=200, row-3 on 2026-10-03 for group-a with render_seconds=118 and sample_count=48 — use render_seconds as the primary field for the outlier analysis.","exampleUseCases":[{"title":"Detecting slow render job anomalies","prompt":"I have a batch of 80 render jobs from last week — can you flag which ones had abnormally high or low render_seconds using IQR, and also tell me if there's a correlation between render time and sample count? I'll give you all the row data with dates and asset groups."},{"title":"QA check on rendering pipeline output","prompt":"We ran our nightly rendering pipeline and I want to know if any jobs produced weird sample_count values that are statistical outliers, and whether sample_count correlates with render_seconds across the 150 jobs. Here's the full dataset with row IDs and asset group labels."},{"title":"Comparing asset groups for render performance","prompt":"I've got render job records for two asset groups — group-alpha and group-beta — across the past 30 days. Can you run IQR outlier detection on render_seconds and show me the correlation between render duration and sample count for all 60 rows?"}],"resultDescription":"Returns two independent analytical reports for the submitted render job rows: (1) IQR outlier flags identifying which rows fall outside the interquartile range for the selected measure, and (2) a two-measure correlation report quantifying the statistical relationship between render_seconds and sample_count. Both reports are generated locally from supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — minimum row count violation","More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, date, render_seconds, or sample_count) in any row","Invalid date format (must match YYYY-MM-DD pattern)","Numeric values outside allowed range (±1,000,000,000,000)","Invalid field enum value (must be render_seconds or sample_count)","Payment not included or insufficient — x402 payment of 0.01 USDC required"],"whenToPreferThis":"Choose this endpoint when you need both IQR-based outlier detection and a two-measure correlation analysis on render job data (render_seconds and sample_count) in a single call for up to 200 rows. It is ideal for rendering pipeline QA, performance audits, and anomaly detection workflows where no external data enrichment or prediction is needed — just local statistical computation on supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:42:34.062Z","isFirstParty":false,"canonicalSlug":"render-jobs-iqr-outlier-flags-two-measure-correlation-28059a11"}