{"uid":"cap_1hvrPSThg2NKzGjFYPkHo","slug":"export-validation-analytics-adjacent-row-changes-secondary-measure-f8fb066d","name":"Export Validation Analytics: Adjacent Row Changes + Secondary-Measure Weighted Mean","description":"Export validation — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean for supplied export validation records (valid_rows, exported_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-14-159?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_rows","exported_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"valid_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"exported_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","valid_rows":10,"dataset_group":"group-a","exported_rows":1},{"date":"2026-10-02","row_id":"row-2","valid_rows":20,"dataset_group":"group-b","exported_rows":2},{"date":"2026-10-03","row_id":"row-3","valid_rows":15,"dataset_group":"group-a","exported_rows":3},{"date":"2026-10-04","row_id":"row-4","valid_rows":30,"dataset_group":"group-b","exported_rows":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_rows","exported_rows"],"type":"string","default":"valid_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_GZQRSRpWIGK4naf0dBIzH","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":"Computes adjacent row-to-row changes and a secondary-measure weighted mean for up to 200 export validation records (valid_rows, exported_rows) in two independent local analytical reports.","exampleAgentPrompt":"Can you run the adjacent row changes and weighted mean analysis on my export validation data? I have rows for group-a and group-b from 2026-10-01 to 2026-10-04 with valid_rows values of 10, 20, 15, and 30 — use valid_rows as the primary field.","exampleUseCases":[{"title":"ETL pipeline export anomaly detection","prompt":"I have daily export validation records from my ETL pipeline for October — can you analyze the adjacent row changes in valid_rows across dataset groups so I can spot any sudden jumps or drops between consecutive days?"},{"title":"Weighted mean summary for exported rows","prompt":"Run the secondary-measure weighted mean report on my exported_rows data across these 4 dataset groups and dates so I can see the weighted average export volume."},{"title":"Dual-report validation audit","prompt":"I need both the adjacent row change analysis and the weighted mean for my valid_rows export records — here are 50 rows across two groups with dates ranging from 2026-10-01 to 2026-11-19, use valid_rows as the field."}],"resultDescription":"Returns two independent analytical reports: (1) an adjacent row changes report showing the delta between consecutive rows for the selected measure, and (2) a secondary-measure weighted mean report summarizing the weighted average — both computed locally on the supplied export validation records (up to 200 rows).","failureModes":["Missing required fields (row_id, date, dataset_group) return validation errors","Exceeding 200 rows causes rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Null values in valid_rows or exported_rows may affect computation accuracy","Fewer than 2 rows prevents meaningful adjacent row change calculation"],"whenToPreferThis":"Choose this endpoint when you need two combined local analytical computations — adjacent row-to-row delta analysis and weighted mean — on export validation data in a single low-cost call, without requiring live external lookups, predictions, or external integrations. Best suited for ETL monitoring, data quality audits, and export pipeline validation workflows with up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:29.380Z","isFirstParty":false,"canonicalSlug":"export-validation-analytics-adjacent-row-changes-secondary-measure-f8fb066d"}