{"uid":"cap_TnR063diIOmvku3KD9h9G","slug":"pipeline-durations-record-quality-audit-adjacent-row-changes-ac06d390","name":"Pipeline Durations — Record Quality Audit + Adjacent Row Changes","description":"Pipeline durations — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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-05-011?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_wc262Xw5srbTZjIbzZQJn","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":"Runs two local analytical reports on pipeline duration data: a record quality audit and an adjacent-row change analysis, for up to 200 rows of run_seconds or processed_rows metrics.","exampleAgentPrompt":"Audit my pipeline duration records for data quality issues and check for adjacent-row changes in run_seconds — here are my rows: [{\"row_id\":\"r1\",\"dataset_group\":\"etl-prod\",\"date\":\"2024-01-15\",\"run_seconds\":120,\"processed_rows\":5000},{\"row_id\":\"r2\",\"dataset_group\":\"etl-prod\",\"date\":\"2024-01-16\",\"run_seconds\":null,\"processed_rows\":4800}].","exampleUseCases":[{"title":"ETL pipeline health check","prompt":"I have 50 rows of daily ETL run logs with run_seconds and processed_rows per dataset group — can you run a record quality audit and flag any adjacent-row changes in the run_seconds field?"},{"title":"Detecting sudden throughput drops","prompt":"Check my pipeline duration dataset for data quality problems and show me where processed_rows changes significantly between consecutive rows — I'll paste the records now."},{"title":"Pre-analysis data validation","prompt":"Before I start my pipeline performance analysis, audit these 120 pipeline duration records for bad or missing values and tell me where run_seconds jumps or drops between adjacent rows."}],"resultDescription":"Two independent analytical reports: (1) a record quality audit identifying issues such as null values, out-of-range numbers, or malformed fields across the supplied rows, and (2) an adjacent-row change analysis showing how the selected metric (run_seconds or processed_rows) shifts between consecutive records. All computation is performed locally with no external lookups or predictions.","failureModes":["Fewer than 1 row supplied — minimum array size is 1","More than 200 rows supplied — exceeds maxItems limit","Missing required fields (row_id, dataset_group, date, run_seconds, processed_rows) on any row","Date not in YYYY-MM-DD format — fails pattern validation","Field selector not one of 'run_seconds' or 'processed_rows' — enum validation error","Payment not provided or insufficient — x402 payment required ($0.01 USDC)"],"whenToPreferThis":"Use this endpoint when you have pipeline duration data (run_seconds, processed_rows) and need both a data quality audit and a consecutive-row change analysis in a single low-cost call. Ideal for pre-analysis validation of ETL logs or monitoring pipeline performance consistency. Not suitable when you need live data fetching, predictions, external benchmarks, or more than 200 rows per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:55:14.278Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-record-quality-audit-adjacent-row-changes-ac06d390"}