{"uid":"cap_BM7-jYFKxo38b6Y-rdEkI","slug":"transformation-throughput-record-quality-audit-string-normalisation-3ce621c1","name":"Transformation Throughput — Record Quality Audit + String Normalisation + Adjacent Row Changes","description":"Transformation throughput — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-200?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_rows"}}},"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_9NK7dei3g8gFmSfOCRG2u","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 local analytical reports on transformation throughput records: record quality audit, string normalisation, and adjacent row change detection for up to 200 rows.","exampleAgentPrompt":"Run a record quality audit, string normalisation, and adjacent row changes analysis on my transformation throughput data — here are 4 rows with processed_rows and duration_seconds fields, grouped by dataset_group across dates 2026-10-01 through 2026-10-04, and I want the report for the processed_rows field.","exampleUseCases":[{"title":"ETL pipeline quality audit","prompt":"I have a batch of 50 transformation throughput records with processed_rows and duration_seconds — can you run a full quality audit, string normalisation, and adjacent row change detection on them? The field I care most about is processed_rows."},{"title":"Detecting step changes in throughput metrics","prompt":"My pipeline logs show processed_rows and duration_seconds across several dataset groups over the past week — run the adjacent row changes report on them so I can see where big jumps or drops happened between consecutive rows."},{"title":"Cleaning dataset group name inconsistencies","prompt":"I've got transformation throughput records where the dataset_group names look inconsistent — can you run the string normalisation report on these rows to flag and clean up any naming issues in the dataset?"}],"resultDescription":"Three independent analytical reports generated from the supplied rows: (1) a record quality audit flagging missing, invalid, or out-of-range values; (2) a string normalisation report identifying and standardising inconsistencies in string fields; (3) an adjacent row changes report highlighting value changes between consecutive rows — all computed locally with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes rejection","Invalid date format (not YYYY-MM-DD) triggers a pattern validation error","Providing an unsupported field enum value causes a schema error","Empty rows array (minItems:1 violated) returns an error"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and adjacent row change detection — on transformation throughput records (processed_rows, duration_seconds) in a single low-cost call. It is ideal when you have up to 200 rows of ETL pipeline data and want offline, local analysis without any live lookups or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:41.399Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-record-quality-audit-string-normalisation-3ce621c1"}