{"uid":"cap_rwVIwkaAnZ9TqsWtu87yO","slug":"export-validation-record-quality-audit-adjacent-row-changes-ed9ff733","name":"Export Validation — Record Quality Audit + Adjacent Row Changes","description":"Export validation — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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-14-011?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_uEU6X7_wr0F5oIKL7VQDa","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 two local analytical reports on export validation data: a record quality audit and adjacent row change detection, for up to 200 rows of valid_rows/exported_rows data.","exampleAgentPrompt":"Can you run a record quality audit and adjacent row change analysis on my export validation data? I have 4 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, and I want to focus on the valid_rows field.","exampleUseCases":[{"title":"Nightly export pipeline quality check","prompt":"I have yesterday's export validation records for two dataset groups — can you audit the record quality and flag any suspicious changes between adjacent rows? Here are 50 rows with row_id, date, dataset_group, valid_rows, and exported_rows, and I want the analysis on exported_rows."},{"title":"Catching data drops in ETL output","prompt":"Run an adjacent row change report on my ETL export data — I want to see where valid_rows jumps or drops unexpectedly between consecutive dates. I've got 120 rows across three dataset groups from last month."},{"title":"Pre-release dataset validation","prompt":"Before we ship this dataset, can you do a record quality audit on our export validation records and also check for any unusual changes between adjacent rows? I have 80 rows covering group-a through 2026-10-31 and I want to focus on valid_rows."}],"resultDescription":"Returns two independent analytical reports per call: (1) a record quality audit highlighting issues such as nulls, out-of-range values, or malformed records across the submitted rows, and (2) an adjacent row change report identifying significant differences or anomalies between consecutive rows — all computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, valid_rows, exported_rows) cause validation errors","Invalid date format (must be YYYY-MM-DD) triggers schema rejection","Field selector not one of 'valid_rows' or 'exported_rows' — enum validation failure","Empty rows array (minItems: 1 not met) causes rejection","Numeric values outside allowed range cause schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need two complementary analytics reports — record quality audit plus adjacent row change detection — on export validation data in a single low-cost call. It is ideal for batch offline analysis of up to 200 rows where no live external lookups, predictions, or integrations are needed. Prefer it over single-report endpoints when both quality auditing and row-change detection are required simultaneously for valid_rows or exported_rows metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:58.551Z","isFirstParty":false,"canonicalSlug":"export-validation-record-quality-audit-adjacent-row-changes-ed9ff733"}