{"uid":"cap_dKzCfNCarL0lpQzCvX2Da","slug":"duplicate-observations-record-quality-audit-iqr-outlier-flags-871ee956","name":"Duplicate Observations — Record Quality Audit + IQR Outlier Flags","description":"Duplicate observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags 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-04-014?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_DqX_RAPiRXcR_5fBW6FcV","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":"Performs a record quality audit and IQR-based outlier detection on up to 200 rows of duplicate observation data (duplicate_rows, total_rows), returning two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and IQR outlier check on these duplicate observation records across my dataset groups? I have 4 rows: row-1 on 2026-10-01 for group-a with duplicate_rows=10 and total_rows=1, row-2 on 2026-10-02 for group-b with duplicate_rows=20 and total_rows=2, row-3 on 2026-10-03 for group-a with duplicate_rows=15 and total_rows=3, row-4 on 2026-10-04 for group-b with duplicate_rows=30 and total_rows=4 — analyze the duplicate_rows field.","exampleUseCases":[{"title":"ETL pipeline duplicate tracking audit","prompt":"I've got a list of daily ETL run records with duplicate_rows and total_rows counts per dataset group — can you audit them for data quality issues and flag any IQR outliers in the duplicate_rows field? Here are my 6 rows: row-1 2025-01-01 group-sales duplicate_rows=5 total_rows=100, row-2 2025-01-02 group-sales duplicate_rows=300 total_rows=200, row-3 2025-01-03 group-sales duplicate_rows=4 total_rows=150, row-4 2025-01-01 group-ops duplicate_rows=2 total_rows=80, row-5 2025-01-02 group-ops duplicate_rows=3 total_rows=90, row-6 2025-01-03 group-ops duplicate_rows=200 total_rows=95."},{"title":"Multi-group data deduplication health check","prompt":"Run a quality audit on my deduplication records and flag any outliers using IQR — I want to check the total_rows field across these 5 entries: row-A 2024-06-01 group-finance duplicate_rows=12 total_rows=500, row-B 2024-06-02 group-finance duplicate_rows=14 total_rows=510, row-C 2024-06-03 group-finance duplicate_rows=11 total_rows=9999, row-D 2024-06-04 group-marketing duplicate_rows=8 total_rows=300, row-E 2024-06-05 group-marketing duplicate_rows=9 total_rows=290."},{"title":"Weekly data quality review for duplicate metrics","prompt":"I need a record quality audit plus IQR outlier flags for my weekly duplicate tracking data — 8 rows spanning two groups: row-w1 through row-w4 for group-alpha on 2025-03-01 to 2025-03-04 with duplicate_rows of 20, 22, 19, 150 and total_rows of 400, 410, 395, 405; and row-w5 through row-w8 for group-beta on the same dates with duplicate_rows of 5, 6, 4, 5 and total_rows of 200, 210, 195, 205. Analyze the duplicate_rows field."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit covering issues such as missing values, invalid ranges, and data consistency in the supplied duplicate observation rows, and (2) IQR-based outlier flags identifying which rows have statistically extreme values in the selected field (duplicate_rows or total_rows). All analysis is performed locally on the supplied data with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows supplied — validation error","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) on any row","Date field not matching YYYY-MM-DD pattern — schema validation failure","Invalid field selector (not 'duplicate_rows' or 'total_rows') — enum validation error","Numeric values outside supported range — schema rejection","Insufficient data variance for meaningful IQR computation (e.g. all identical values)"],"whenToPreferThis":"Choose this endpoint when you need both a record quality audit and IQR outlier detection on duplicate-observation tracking data in a single call at minimal cost ($0.01 USDC for both reports). It is best suited for offline or batch data quality checks on up to 200 rows of duplicate_rows/total_rows metrics grouped by dataset and date, requiring no external data, predictions, or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:23.125Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-record-quality-audit-iqr-outlier-flags-871ee956"}