{"uid":"cap_apE16EgagzVNSYCpq7csm","slug":"duplicate-observations-analytics-record-quality-audit-string-da081cc8","name":"Duplicate Observations Analytics: Record Quality Audit, String Normalisation & Two-Measure Correlation","description":"Duplicate observations — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation 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-04-204?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}}},"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_MaqSP81yIkFc59nYLvg6M","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 supplied duplicate-observation records: a record quality audit, string normalisation, and a two-measure correlation between duplicate_rows and total_rows.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and correlation analysis on my duplicate observations data? I have 4 rows: row-1 on 2026-10-01 in group-a with 10 duplicate rows out of 1 total, row-2 on 2026-10-02 in group-b with 20 duplicates out of 2 total, row-3 on 2026-10-03 in group-a with 15 duplicates out of 3 total, and row-4 on 2026-10-04 in group-b with 30 duplicates out of 4 total.","exampleUseCases":[{"title":"ETL pipeline duplicate record audit","prompt":"I need to audit the quality of duplicate records coming out of our ETL pipeline. Here are 5 rows with date, dataset group, duplicate_rows, and total_rows — can you run a full quality audit, normalize the string fields, and correlate duplicate_rows against total_rows for me?"},{"title":"Data warehouse duplicate rate analysis","prompt":"We have a data warehouse table and I want to understand how duplicate rows correlate with total row counts across our dataset groups over the last week. Can you run a two-measure correlation plus a record quality audit on these 10 daily observations?"},{"title":"Dataset group string consistency check","prompt":"Our dataset group labels might have inconsistent casing or whitespace issues across these 15 duplicate observation records. Can you run a string normalisation report plus a record quality audit so I can see what needs cleaning before we load to production?"}],"resultDescription":"Returns three independent analytical reports for the submitted rows (up to 200): (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed dates; (2) a string normalisation report highlighting inconsistencies in text fields like dataset_group; and (3) a two-measure correlation report quantifying the relationship between duplicate_rows and total_rows across the supplied records. All analysis is performed locally with no external lookups or predictions.","failureModes":["Fewer than 1 row submitted — minimum 1 row required","More than 200 rows submitted — hard cap enforced","Malformed date strings not matching YYYY-MM-DD pattern","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows)","Numeric fields outside allowed range (-1e12 to 1e12)","Payment failure or insufficient USDC balance"],"whenToPreferThis":"Choose this endpoint when you need a bundled, cost-effective ($0.01 USDC for all three reports) offline analytical pass over a small batch of duplicate-observation records (up to 200 rows) and require record quality auditing, string field normalisation, and numeric correlation in a single call with no external data dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:01:05.622Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-analytics-record-quality-audit-string-da081cc8"}