{"uid":"cap_zUk1Op9axKpc42oyHn9-3","slug":"transformation-throughput-duplicate-key-report-adjacent-row-changes-dd04aa5d","name":"Transformation Throughput — Duplicate Key Report + Adjacent Row Changes","description":"Transformation throughput — Duplicate key report + Adjacent row changes: Duplicate key report + Adjacent row changes for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-062?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_rP7XVdWavcnzb3ES-utsL","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":"Analyzes supplied transformation throughput records to produce two reports: a duplicate key report and an adjacent row changes report, for up to 200 rows.","exampleAgentPrompt":"Can you run a duplicate key report and adjacent row changes report on my transformation throughput data? Here are my records with row_id, dataset_group, date, processed_rows, and duration_seconds — analyze the processed_rows field across up to 200 rows.","exampleUseCases":[{"title":"ETL pipeline duplicate key audit","prompt":"I have a list of up to 150 ETL job records with row IDs, dataset groups, dates, processed row counts, and duration in seconds — can you check them for duplicate row keys and show me where adjacent rows changed in processed_rows?"},{"title":"Spot sequential throughput shifts","prompt":"Here are my daily transformation logs for the last quarter, each with a row_id, dataset_group, date, processed_rows, and duration_seconds. Run the adjacent row changes report on duration_seconds so I can see where processing time jumped between consecutive entries."},{"title":"Data pipeline quality check before merge","prompt":"Before I merge these pipeline throughput records into our warehouse, can you scan them for duplicate key collisions and flag any adjacent row changes in processed_rows? I have about 80 rows with row_id, dataset_group, date, processed_rows, and duration_seconds."}],"resultDescription":"Returns two independent analytical reports for the supplied rows: (1) a duplicate key report identifying any repeated row_id values, and (2) an adjacent row changes report highlighting consecutive rows where the selected metric field (processed_rows or duration_seconds) changed. No external lookups or predictions are made; analysis is performed locally on the supplied data.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds maximum limit","Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Field value outside allowed numeric range — rejected","Invalid field enum value (not processed_rows or duration_seconds) — error"],"whenToPreferThis":"Choose this endpoint when you need both a duplicate key check and an adjacent row change analysis on transformation throughput records (processed_rows and duration_seconds) in a single $0.01 call for up to 200 rows. Ideal for lightweight, offline data quality checks on ETL or pipeline logs without requiring external data sources, predictions, or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:42:01.505Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-duplicate-key-report-adjacent-row-changes-dd04aa5d"}