{"uid":"cap_1YHGifQCLIo3XAY2LbRgy","slug":"pipeline-durations-analytics-string-normalisation-numeric-row-ordering-f7cc6e60","name":"Pipeline Durations Analytics — String Normalisation & Numeric Row Ordering","description":"Pipeline durations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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-05-025?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_tCqXQVr0t8ttLOa56sf2s","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":"Normalises string fields and orders rows numerically for up to 200 pipeline duration records (run_seconds, processed_rows), returning two analytical reports per call.","exampleAgentPrompt":"Normalise the string fields and rank these pipeline run records numerically by run_seconds — I have 4 rows: row-1 on 2026-10-01 in group-a with run_seconds=10 and processed_rows=1, row-2 on 2026-10-02 in group-b with run_seconds=20 and processed_rows=2, row-3 on 2026-10-03 in group-a with run_seconds=15 and processed_rows=3, and row-4 on 2026-10-04 in group-b with run_seconds=30 and processed_rows=4.","exampleUseCases":[{"title":"Rank ETL jobs by run time","prompt":"I have 10 pipeline run records from last week with run_seconds and processed_rows — can you normalise the dataset_group strings and rank them numerically by run_seconds so I can see which jobs took longest?"},{"title":"Normalise group labels across pipeline logs","prompt":"My pipeline logs have inconsistent dataset_group labels and I need them normalised, plus the rows ordered by processed_rows — here are 50 records with row IDs, dates, run_seconds, and processed_rows values. Field to order by is processed_rows."},{"title":"Two-report analytics for daily batch jobs","prompt":"Can you run string normalisation and numeric row ordering on my daily batch pipeline data? I'll give you 30 rows with run_seconds and processed_rows, grouped by dataset_group, and I need both reports back sorted by run_seconds."}],"resultDescription":"Two analytical reports per call: (1) a string normalisation report for the dataset_group and related string fields, and (2) a numeric row ordering report ranking the supplied rows by the chosen numeric field (run_seconds or processed_rows), covering up to 200 input rows with no external lookups or live data.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, date, run_seconds, processed_rows) — row rejected or error returned","Invalid date format (not YYYY-MM-DD) — validation failure","Null numeric values in run_seconds or processed_rows may affect ordering output","Payment not completed via x402 protocol — request not processed"],"whenToPreferThis":"Choose this endpoint when you need deterministic, offline string normalisation and numeric ordering for pipeline duration records (run_seconds, processed_rows) without any external API calls, predictions, or live lookups. It is best suited for data engineering workflows where you want two clean analytical reports — normalised labels and ranked rows — for up to 200 pipeline job records at minimal cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T12:51:21.665Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-analytics-string-normalisation-numeric-row-ordering-f7cc6e60"}