{"uid":"cap_YmrJfuId5Ss08yS_w2g1r","slug":"data-ingestion-batches-duplicate-key-report-iqr-outlier-flags-6b9306df","name":"Data Ingestion Batches — Duplicate Key Report + IQR Outlier Flags","description":"Data ingestion batches — Duplicate key report + IQR outlier flags: Duplicate key report + IQR outlier flags for supplied data ingestion batches records (received_rows, accepted_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-01-065?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_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_ryc_xR4AknT57dILAoCEV","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 data ingestion batch records to produce a duplicate key report and IQR-based outlier flags for received_rows or accepted_rows metrics.","exampleAgentPrompt":"Can you check my ingestion batch records for duplicate row IDs and flag any IQR outliers in the received_rows column? I have about 50 rows with fields like row_id, dataset_group, date, received_rows, and accepted_rows.","exampleUseCases":[{"title":"ETL pipeline duplicate key audit","prompt":"I've got 120 rows of daily ingestion batch records — each has a row_id, dataset_group, date, received_rows, and accepted_rows. Can you run a duplicate key report on them and also flag any IQR outliers in accepted_rows so I can catch data quality issues before loading to the warehouse?"},{"title":"Anomaly detection in data ingestion metrics","prompt":"My data pipeline logs show received_rows counts that seem weirdly high on some days. Can you take my 80 batch records and flag any statistical outliers in received_rows using IQR, and also check if any row IDs are repeated?"},{"title":"Data quality check before reporting","prompt":"Before I generate my weekly ingestion summary report, I need to verify data quality — can you run a duplicate key check and IQR outlier detection on my accepted_rows for these 45 ingestion batch records across dataset groups A and B?"}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any repeated row_id values across the submitted batch records, and (2) IQR-based outlier flags marking records whose received_rows or accepted_rows values fall outside the interquartile range bounds — all computed locally with no external lookups.","failureModes":["Fewer than 1 row submitted — minimum 1 row required","More than 200 rows submitted — batch size limit exceeded","Invalid date format (must match YYYY-MM-DD pattern)","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows)","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)","Invalid field enum value — must be 'received_rows' or 'accepted_rows'","Payment not included or insufficient (requires 0.01 USDC via x402)"],"whenToPreferThis":"Choose this endpoint when you need simultaneous duplicate key detection and IQR outlier flagging on data ingestion batch records (received_rows/accepted_rows) in a single low-cost call. It is ideal for ETL data quality checks, pre-load validation, and pipeline audits where you want both uniqueness and statistical anomaly reports without external dependencies or live data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:41.322Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-duplicate-key-report-iqr-outlier-flags-6b9306df"}