{"uid":"cap__TpKq4D-uFYiKLhI7Pz0X","slug":"data-ingestion-batches-record-quality-audit-string-normalisation-ac346eca","name":"Data Ingestion Batches — Record Quality Audit + String Normalisation + Trailing Mean Series","description":"Data ingestion batches — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied data ingestion batches records (received_rows, accepted_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-01-199?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_xh1mmTdQuesowtuWTsVbe","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 on data ingestion batch records: a record quality audit, string normalisation, and trailing mean series computation for received_rows and accepted_rows fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and trailing mean series (window=3) on my ingestion batch data for received_rows? Here are the rows: row-1 / group-a / 2026-10-01 / received=100 / accepted=90, row-2 / group-b / 2026-10-02 / received=200 / accepted=180, row-3 / group-a / 2026-10-03 / received=150 / accepted=140.","exampleUseCases":[{"title":"Pipeline ingestion quality health check","prompt":"I have a week's worth of ingestion batch records — can you audit them for quality issues, normalise the dataset_group strings, and give me a trailing mean series with window=5 on received_rows? I'll paste the rows: row-1/group-A/2026-11-01/received=500/accepted=480, row-2/Group-a/2026-11-02/received=520/accepted=500, row-3/group_a/2026-11-03/received=490/accepted=470."},{"title":"Accepted rows trend smoothing for reporting","prompt":"Can you compute a trailing mean series with a window of 4 on the accepted_rows field from my ingestion data, and also run a quality audit and string normalisation on the same batch? Rows: row-1/dataset-X/2026-10-01/received=1000/accepted=950, row-2/Dataset-X/2026-10-02/received=1100/accepted=1040, row-3/dataset_x/2026-10-03/received=980/accepted=920, row-4/DATASET-X/2026-10-04/received=1050/accepted=1000."},{"title":"Multi-group ingestion anomaly detection","prompt":"I'm seeing inconsistent dataset_group labels and some suspiciously low accepted_rows counts — can you run a record quality audit, normalise the strings, and give a trailing mean (window=2) on received_rows across these 5 batch records? row-1/group-Alpha/2026-09-01/received=300/accepted=10, row-2/Group_Alpha/2026-09-02/received=310/accepted=305, row-3/group-beta/2026-09-03/received=0/accepted=0, row-4/GROUP-BETA/2026-09-04/received=280/accepted=270, row-5/group-alpha/2026-09-05/received=290/accepted=285."}],"resultDescription":"Returns three independent analytical reports for the supplied batch rows: (1) a record quality audit flagging issues in received_rows/accepted_rows values, (2) a string normalisation report on fields like dataset_group, and (3) a trailing mean series for the selected numeric field (received_rows or accepted_rows) over the specified window size. All computed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) on any row — validation error","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Window size less than 2 or greater than 200 — parameter error","Numeric values outside allowed range (±1,000,000,000,000) — schema rejection","Additional properties on row objects not permitted — additionalProperties error"],"whenToPreferThis":"Choose this endpoint when you need three analytical views on data ingestion batch records in a single low-cost call: quality auditing, string normalisation, and rolling mean computation. It is ideal for ETL monitoring, pipeline health checks, and data quality reviews where received_rows and accepted_rows are the core metrics, and where no live external data, predictions, or professional assessments are needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T18:48:39.008Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-record-quality-audit-string-normalisation-ac346eca"}