{"uid":"cap_3ap3lUxLjWGiundiKjFrT","slug":"duplicate-observations-analytics-record-quality-audit-string-bd2a86ce","name":"Duplicate Observations Analytics — Record Quality Audit, String Normalisation & Adjacent Row Changes","description":"Duplicate observations — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied duplicate observations records (duplicate_rows, total_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-04-200?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","duplicate_rows","total_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"duplicate_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rows":1,"dataset_group":"group-a","duplicate_rows":10},{"date":"2026-10-02","row_id":"row-2","total_rows":2,"dataset_group":"group-b","duplicate_rows":20},{"date":"2026-10-03","row_id":"row-3","total_rows":3,"dataset_group":"group-a","duplicate_rows":15},{"date":"2026-10-04","row_id":"row-4","total_rows":4,"dataset_group":"group-b","duplicate_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["duplicate_rows","total_rows"],"type":"string","default":"duplicate_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_91HqbcBRjtNqQB67Aip1W","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 up to 200 duplicate-observation records and returns three independent reports: a record quality audit, string normalization analysis, and adjacent row change detection.","exampleAgentPrompt":"Can you run a full quality audit on my duplicate observation data — I have up to 50 rows with dataset groups like 'group-a' and 'group-b', each with a date, duplicate_rows count, and total_rows count — I want the record quality audit, string normalization, and adjacent row change reports for the duplicate_rows field?","exampleUseCases":[{"title":"Dataset deduplication quality check","prompt":"I have a batch of 80 daily duplicate-observation records for datasets 'inventory' and 'sales', each with a date, duplicate_rows, and total_rows — can you run a quality audit and flag any string normalization issues in the dataset group names for the duplicate_rows field?"},{"title":"Adjacent row anomaly detection","prompt":"My ETL pipeline logs duplicate_rows and total_rows for each dataset every day — can you analyze 120 of these rows and tell me where the duplicate_rows value changes sharply between consecutive rows, plus give me a quality audit?"},{"title":"Cross-group duplicate rate review","prompt":"I need to audit duplicate observation records across three dataset groups — 'orders', 'customers', and 'products' — for the past 60 days, up to 150 rows total. Give me all three reports: quality audit, string normalization, and adjacent changes, focused on the total_rows field."}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit identifying missing, invalid, or anomalous values in the supplied rows; (2) a string normalization report flagging inconsistencies in text fields such as dataset_group; and (3) an adjacent row change report highlighting significant shifts between consecutive records in the selected numeric field (duplicate_rows or total_rows). All analysis runs locally with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Numeric values outside allowed range (-1T to +1T) may be rejected","Empty rows array returns error","Payment of 0.01 USDC not provided — request rejected with 402"],"whenToPreferThis":"Choose this endpoint when you need a quick, low-cost ($0.01) multi-angle quality analysis of duplicate observation records — specifically when you want all three of record quality audit, string normalization, and adjacent row change detection in a single call for up to 200 rows, without any need for live data lookup or external prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:41.099Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-analytics-record-quality-audit-string-bd2a86ce"}