{"uid":"cap_pabch3jsS0az3mZazlvRz","slug":"pipeline-durations-record-quality-audit-string-normalisation-afcdfaed","name":"Pipeline Durations — Record Quality Audit + String Normalisation","description":"Pipeline durations — Record quality audit + String normalisation: Record quality audit + String normalisation 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-05-001?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}}},"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_jWf1qWCNIyRynpev7ofMD","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":"Audits data quality and normalises strings for pipeline duration records (run_seconds, processed_rows) across up to 200 rows, returning 2 independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and string normalisation on my pipeline duration data? Here are 4 rows: row-1 on 2026-10-01 for group-a with run_seconds=10 and processed_rows=1, row-2 on 2026-10-02 for group-b with run_seconds=20 and processed_rows=2, row-3 on 2026-10-03 for group-a with run_seconds=15 and processed_rows=3, and row-4 on 2026-10-04 for group-b with run_seconds=30 and processed_rows=4.","exampleUseCases":[{"title":"ETL pipeline health check","prompt":"I've got 150 rows of pipeline execution logs with run_seconds and processed_rows — can you audit them for data quality issues and normalise any messy string fields like dataset_group? Dates range from 2026-09-01 to 2026-09-30."},{"title":"Pre-warehouse data validation","prompt":"Before I load my pipeline metrics into the data warehouse, can you check these 80 records for quality problems — things like nulls, negatives, or weird values in run_seconds and processed_rows — and also clean up the dataset_group strings?"},{"title":"Anomaly detection in batch runs","prompt":"We had some weird batch pipeline runs last week and I suspect bad data. Can you audit these 200 rows of pipeline duration records for quality issues and tell me if anything in run_seconds or processed_rows looks off, plus normalise the string columns?"}],"resultDescription":"Two independent analytical reports per call: (1) a record quality audit covering issues such as nulls, out-of-range values, duplicates, and anomalies in run_seconds and processed_rows; (2) a string normalisation report covering the dataset_group and other string fields — all computed locally without external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, run_seconds, processed_rows, dataset_group) causes row rejection","Malformed date strings not matching YYYY-MM-DD pattern fail schema validation","Numeric values outside ±1,000,000,000,000 boundary are rejected","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need a fast, offline, cost-effective dual-report (quality audit + string normalisation) on pipeline duration records (run_seconds, processed_rows) with no external data fetching or prediction requirements, and your dataset fits within 200 rows per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:41:03.481Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-record-quality-audit-string-normalisation-afcdfaed"}