{"uid":"cap_QtFzZ3hd5-w4Olr3-YVRy","slug":"data-pipeline-runs-iqr-outlier-flags-dbca4481","name":"Data Pipeline Runs – IQR Outlier Flags","description":"Data pipeline runs - IQR outlier flags: IQR outlier flags for Data pipeline runs. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded iqr outlier flags report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-pipeline-runs-outliers?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","pipeline","date","processed_rows","rejected_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"pipeline":{"type":"string","default":"","maxLength":80},"rejected_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","pipeline":"group-a","rejected_rows":1,"processed_rows":10},{"date":"2026-10-02","row_id":"row-2","pipeline":"group-b","rejected_rows":2,"processed_rows":20},{"date":"2026-10-03","row_id":"row-3","pipeline":"group-a","rejected_rows":3,"processed_rows":15},{"date":"2026-10-04","row_id":"row-4","pipeline":"group-b","rejected_rows":4,"processed_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","rejected_rows"],"type":"string","default":"processed_rows"}}},"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_2RWtBqifIe7AMX5zOyNHR","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":"Detects IQR-based statistical outliers in data pipeline run metrics (processed_rows or rejected_rows) across up to 200 typed records","exampleAgentPrompt":"Can you run an IQR outlier detection report on these pipeline run records and flag any anomalies in the processed_rows field? I have about 50 rows covering runs for pipelines group-a and group-b from October 2026.","exampleUseCases":[{"title":"Flagging bad ETL batch runs","prompt":"I have 90 days of daily pipeline run data for three pipelines and I want to know which runs had statistically outlying processed_row counts — can you flag the IQR outliers in processed_rows for me?"},{"title":"Spotting rejection rate spikes","prompt":"Run an IQR outlier check on my pipeline runs using the rejected_rows field — I want to know which specific run dates had abnormally high rejection counts compared to the rest."},{"title":"Data quality audit before reporting","prompt":"Before I publish our monthly pipeline health report, can you flag any outlier runs in processed_rows using IQR analysis on all 150 run records I'm providing?"}],"resultDescription":"A bounded IQR outlier flags report identifying which of the submitted pipeline run records are statistical outliers for the chosen metric field (processed_rows or rejected_rows), based on interquartile range analysis. No forecasting or external enrichment is included — results are purely descriptive analytics on the supplied data.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — request rejected (maxItems exceeded)","Missing required fields (row_id, pipeline, date, processed_rows, rejected_rows) — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Invalid field enum value (not 'processed_rows' or 'rejected_rows') — rejected","Payment not provided or insufficient USDC — 402 payment required response"],"whenToPreferThis":"Choose this endpoint when you need a quick, local IQR-based outlier detection report on a set of data pipeline run records (up to 200) without any external enrichment or forecasting. It is ideal for data engineers and analysts who want to statistically flag anomalous pipeline runs by processed or rejected row counts using a well-understood robust method (IQR), at very low cost per call ($0.01 USDC).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:47:23.781Z","isFirstParty":false,"canonicalSlug":"data-pipeline-runs-iqr-outlier-flags-dbca4481"}