{"uid":"cap_wzR4Ch79xBWCyzIZVSOFJ","slug":"render-jobs-trailing-mean-series-iqr-outlier-flags-19205d97","name":"Render Jobs — Trailing Mean Series + IQR Outlier Flags","description":"Render jobs — Trailing mean series + IQR outlier flags: Trailing mean series + IQR outlier flags 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-02-149?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_0aEoeXSm_VU-IDqkv3Cs2","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 trailing moving average series and IQR-based outlier flags for render job records (render_seconds or sample_count) across up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"I have 50 daily render job records with render_seconds and sample_count — can you compute a trailing mean series and flag IQR outliers for the render_seconds field using a window of 7?","exampleUseCases":[{"title":"Render time anomaly detection for studio","prompt":"I've got 120 render job records grouped by asset group and date — can you run a trailing mean with a window of 5 on render_seconds and flag any IQR outliers so I can see which days had abnormal render times?"},{"title":"Sample count trend analysis for pipeline QA","prompt":"Here are 80 rows of render job data — please compute a trailing mean series and IQR outlier flags for the sample_count field using a window of 10, so I can catch any batches with unusually high or low sample counts."},{"title":"Weekly render performance review across asset groups","prompt":"I want to review the last 200 render job records for performance issues — can you calculate a rolling mean and IQR outlier flags for render_seconds with a window of 14, broken out by asset group?"}],"resultDescription":"Two analytical reports per call: (1) a trailing moving-average time series for the selected field (render_seconds or sample_count) computed over the specified window, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range. Results are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum row count not met","More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, date, render_seconds, sample_count) in any row","Date format not matching YYYY-MM-DD pattern — validation error","Window parameter outside 2–200 range — rejected","Invalid field enum value (must be render_seconds or sample_count)","Payment not completed — x402 payment required before processing"],"whenToPreferThis":"Choose this endpoint when you have tabular render job data and need both a trailing mean time series and IQR outlier detection in a single call without setting up local analytics infrastructure. It is purpose-built for render pipeline data with render_seconds and sample_count fields, handles up to 200 rows, and delivers two reports for a flat $0.01 USDC — ideal for lightweight, on-demand render performance QA within agent workflows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T18:54:59.935Z","isFirstParty":false,"canonicalSlug":"render-jobs-trailing-mean-series-iqr-outlier-flags-19205d97"}