{"uid":"cap_JXpBqXv9hHEnuZ9K1sDt_","slug":"pipeline-durations-daily-sum-series-iqr-outlier-flags-b7d7e117","name":"Pipeline Durations — Daily Sum Series + IQR Outlier Flags","description":"Pipeline durations — Daily sum series + IQR outlier flags: Daily sum 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-140?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","run_seconds","processed_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"run_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","run_seconds":10,"dataset_group":"group-a","processed_rows":1},{"date":"2026-10-02","row_id":"row-2","run_seconds":20,"dataset_group":"group-b","processed_rows":2},{"date":"2026-10-03","row_id":"row-3","run_seconds":15,"dataset_group":"group-a","processed_rows":3},{"date":"2026-10-04","row_id":"row-4","run_seconds":30,"dataset_group":"group-b","processed_rows":4}],"maxItems":200,"minItems":1},"field":{"enum":["run_seconds","processed_rows"],"type":"string","default":"run_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_0GlBLWNhOZP3DlkGUX48f","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 daily sum time series and IQR-based outlier flags for supplied pipeline duration records (run_seconds or processed_rows), returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Analyze these pipeline run records for daily totals and flag any outlier days using IQR — I have up to 50 rows with run_seconds and processed_rows columns, and I want the run_seconds report.","exampleUseCases":[{"title":"ETL pipeline anomaly detection","prompt":"I have a list of ETL job runs over the past month with run_seconds and processed_rows per day — can you compute daily sums and flag any days that look like outliers based on IQR? Use the run_seconds field."},{"title":"Data throughput daily summary","prompt":"Here are 120 pipeline execution records across multiple dataset groups — give me a daily sum series for processed_rows and highlight which days had abnormally high or low counts using IQR outlier detection."},{"title":"Multi-group pipeline performance audit","prompt":"I want to audit our pipeline durations across two dataset groups over the last quarter — can you aggregate run_seconds by day and tell me which days were statistical outliers using IQR flagging?"}],"resultDescription":"Returns two independent analytical reports: (1) a daily sum time series aggregating the selected metric (run_seconds or processed_rows) by date, and (2) IQR-based outlier flags identifying which dates or records fall outside the interquartile range. Both reports are computed locally without external lookups.","failureModes":["Input array exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, date, dataset_group, run_seconds, processed_rows) cause validation errors","Invalid date format (must be YYYY-MM-DD) triggers schema rejection","Null values in the selected metric field may affect IQR calculation accuracy","Too few data points to compute meaningful IQR statistics (edge case with very small datasets)"],"whenToPreferThis":"Choose this endpoint when you have raw pipeline execution records (with run_seconds and/or processed_rows) and need both a daily aggregated time series and statistical outlier detection in a single call, without requiring external data sources or live system access. Ideal for post-hoc batch job analysis of up to 200 records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:54.487Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-daily-sum-series-iqr-outlier-flags-b7d7e117"}