{"uid":"cap_f59iifk0mnAgTyrustX-k","slug":"duplicate-observations-record-quality-audit-numeric-interval-filter-9bd09f71","name":"Duplicate Observations — Record Quality Audit + Numeric Interval Filter","description":"Duplicate observations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied duplicate observations records (duplicate_rows, total_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-04-008?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_86aBl1sAj0cMc_ANx2WLS","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":"Audits record quality and applies a numeric interval filter to supplied duplicate-observation data (duplicate_rows, total_rows), returning two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you audit the record quality of my duplicate observations and filter them by duplicate_rows between 0 and 50? Here are the rows: row-1 for group-a on 2026-10-01 with 10 duplicate_rows out of 100 total_rows, row-2 for group-b on 2026-10-02 with 25 duplicate_rows out of 200 total_rows, and row-3 for group-a on 2026-10-03 with 60 duplicate_rows out of 150 total_rows.","exampleUseCases":[{"title":"ETL pipeline duplicate record check","prompt":"I need to audit the quality of duplicate observations from my ETL pipeline — can you check these 5 rows across two dataset groups and filter where duplicate_rows falls between 0 and 30? Groups are group-a and group-b, dated from 2026-11-01 to 2026-11-05, with duplicate_rows counts of 5, 12, 35, 8, and 22, and total_rows of 100, 150, 200, 80, and 120."},{"title":"Data warehouse duplicate spike investigation","prompt":"We've noticed some spikes in our data warehouse duplicate counts. Can you run a record quality audit on these observations and filter total_rows between 500 and 10000? I have 8 rows across three groups — can I pass them in with their dates and duplicate/total row counts?"},{"title":"Monthly dataset group deduplication review","prompt":"Run a duplicate observation quality audit for my monthly review — here are 4 records: row-1 group-a 2026-10-01 with 10 duplicate_rows out of 1000 total_rows, row-2 group-b 2026-10-02 with 20 duplicate_rows out of 2000 total_rows, row-3 group-a 2026-10-03 with 5 duplicate_rows out of 500 total_rows, row-4 group-b 2026-10-04 with 50 duplicate_rows out of 3000 total_rows. Filter on the duplicate_rows field with a minimum of 0 and maximum of 25."}],"resultDescription":"Two independent analytical reports: (1) a record quality audit assessing the supplied duplicate observation records, and (2) a numeric interval filter report identifying which rows' chosen field values (duplicate_rows or total_rows) fall within the specified minimum/maximum range. No external lookups or predictions are made — all analysis is performed locally on the supplied data.","failureModes":["Fewer than 1 row supplied — request rejected (minItems: 1)","More than 200 rows supplied — request rejected (maxItems: 200)","Invalid date format (must be YYYY-MM-DD) — validation error","row_id missing or empty — required field error","Field enum value not 'duplicate_rows' or 'total_rows' — validation error","Numeric values outside ±1,000,000,000,000 range — validation error","Payment of 0.01 USDC not completed — 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you need a combined record quality audit AND numeric interval filter on duplicate observation data (duplicate_rows and total_rows fields) in a single call, without requiring any external data lookup or live database access. It is ideal for offline or batch data quality checks on datasets up to 200 rows where you already have the duplicate counts in hand. Prefer it over general-purpose analytics when you specifically need two co-located reports — quality audit plus interval filtering — on duplicate record metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:16.836Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-record-quality-audit-numeric-interval-filter-9bd09f71"}