{"uid":"cap_M8hakH21Ba4yM5TCVWpGu","slug":"pipeline-durations-analytics-record-quality-audit-string-37d0a695","name":"Pipeline Durations Analytics: Record Quality Audit + String Normalisation + Adjacent Row Changes","description":"Pipeline durations — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied pipeline durations records (run_seconds, processed_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-200?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_EblKossIy0Fce7LEpq54E","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 three analytical reports (record quality audit, string normalisation, and adjacent row change detection) on up to 200 pipeline duration records containing run_seconds and processed_rows fields.","exampleAgentPrompt":"Can you run the three-report pipeline duration analysis on my dataset — record quality audit, string normalisation, and adjacent row changes — for these rows: row-1 on 2026-10-01 in group-a with run_seconds=45 and processed_rows=1200, row-2 on 2026-10-02 in group-b with run_seconds=60 and processed_rows=980? Use run_seconds as the primary field.","exampleUseCases":[{"title":"ETL pipeline run quality audit","prompt":"I have a batch of 50 pipeline run records with dates, dataset groups, run_seconds and processed_rows — can you audit them for quality issues, normalise the string fields, and flag any adjacent row changes in run_seconds?"},{"title":"Detecting throughput drops between pipeline steps","prompt":"Here are 30 rows from our nightly ETL logs. Can you run the adjacent row change detection and quality audit on processed_rows so I can spot where throughput dropped significantly between consecutive runs?"},{"title":"Normalising inconsistent dataset group labels","prompt":"Our pipeline logs have messy dataset_group strings across 80 rows — can you run the string normalisation and record quality reports on this data so we can see what needs cleaning before we load it to the warehouse?"}],"resultDescription":"Three independent analytical reports for the submitted pipeline duration records: (1) a record quality audit highlighting data issues, (2) a string normalisation report for text fields like dataset_group, and (3) an adjacent row changes report showing value differences between consecutive rows — all computed locally without external lookups.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Missing required fields (row_id, date, dataset_group, run_seconds, or processed_rows) causes validation error","Invalid date format (must match YYYY-MM-DD pattern)","run_seconds or processed_rows values outside allowed numeric range cause schema rejection","Empty rows array (minItems: 1 required)"],"whenToPreferThis":"Choose this endpoint when you need a bundled, cost-efficient set of three data quality and change-detection reports on pipeline duration records (run_seconds, processed_rows) for up to 200 rows in a single $0.01 USDC call, without requiring any external data sources or real-time lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:11.939Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-analytics-record-quality-audit-string-37d0a695"}