{"uid":"cap_XVl8szXrwmbV8vbRaA4WB","slug":"pipeline-durations-numeric-row-ordering-iqr-outlier-flags-04454862","name":"Pipeline Durations — Numeric Row Ordering + IQR Outlier Flags","description":"Pipeline durations — Numeric row ordering + IQR outlier flags: Numeric row ordering + 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-05-119?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_p0k5UFvm_d6lt48JGQte7","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":"Applies numeric row ordering and IQR-based outlier flagging to up to 200 pipeline duration records (run_seconds or processed_rows), returning two independent analytical reports.","exampleAgentPrompt":"I have 4 pipeline runs — row-1 on 2026-10-01 took 10 seconds and processed 1 row (group-a), row-2 on 2026-10-02 took 20 seconds and 2 rows (group-b), row-3 on 2026-10-03 took 15 seconds and 3 rows (group-a), row-4 on 2026-10-04 took 30 seconds and 4 rows (group-b) — can you rank them by run_seconds and flag any IQR outliers?","exampleUseCases":[{"title":"Outlier detection in nightly ETL runs","prompt":"Here are 50 nightly ETL pipeline records with their run_seconds — can you rank them numerically and flag which ones are IQR outliers so I can investigate slowdowns?"},{"title":"Processed row anomaly check across dataset groups","prompt":"I've got 120 pipeline runs across two dataset groups for October — can you order them by processed_rows and flag any that are statistically anomalous using IQR?"},{"title":"Performance audit before pipeline scaling","prompt":"Before I scale up my pipeline, I want to audit 80 recent runs — can you rank them by run_seconds and highlight any outlier runs using IQR so I know which ones to investigate first?"}],"resultDescription":"Two independent analytical reports: one providing numeric row ordering (ranked positions) for the selected field (run_seconds or processed_rows), and one providing IQR-based outlier flags indicating which rows fall outside the interquartile range bounds — all computed locally without external lookups.","failureModes":["Fewer than 1 row provided — minimum 1 row required","More than 200 rows submitted — exceeds maximum batch size","Invalid date format (must match YYYY-MM-DD pattern)","row_id missing or empty — required field","Selected field not one of run_seconds or processed_rows — invalid enum value","Null values in the selected numeric field may affect IQR computation","run_seconds or processed_rows values outside allowed numeric range"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis of pipeline duration or throughput data — specifically numeric ordering and IQR outlier detection — without any external data lookups, predictions, or professional assessments. It is well-suited for batches of up to 200 rows where you want two reports (ranking + outlier flags) in a single low-cost call. Prefer alternatives if you need time-series forecasting, cross-dataset joins, or analysis of fields beyond run_seconds and processed_rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:41.322Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-numeric-row-ordering-iqr-outlier-flags-04454862"}