{"uid":"cap_nQQU1OlIOXGHkWeSOkF3G","slug":"transformation-throughput-record-quality-audit-iqr-outlier-flags-1ce68f42","name":"Transformation Throughput Record Quality Audit + IQR Outlier Flags","description":"Transformation throughput — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-014?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_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_MvWnBCyP-Vx1QW3GBmqEU","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 data quality and flags IQR-based outliers for transformation throughput records containing processed_rows and duration_seconds fields, delivering two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit and IQR outlier detection on my transformation throughput data? I have 50 rows with processed_rows and duration_seconds values grouped by dataset_group, and I want to check the processed_rows field for outliers.","exampleUseCases":[{"title":"ETL pipeline anomaly detection","prompt":"I have 120 rows of nightly ETL job metrics with processed_rows and duration_seconds per dataset group — can you audit their data quality and flag any IQR outliers in the duration_seconds field so I know which runs were statistically abnormal?"},{"title":"Data quality gate before reporting","prompt":"Before I publish my weekly pipeline throughput report, can you check these 80 transformation records for data quality issues and outliers in processed_rows? I need both an audit and an IQR outlier report."},{"title":"Debugging sparse or null throughput records","prompt":"Some of my pipeline records look off — can you run a quality audit and IQR outlier check on these 35 rows of processed_rows and duration_seconds data grouped by dataset_group to find any nulls, bad values, or statistical outliers in the processed_rows field?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying issues such as nulls, invalid values, and format problems across the supplied rows; and (2) an IQR-based outlier flagging report identifying which rows contain statistically extreme values for the selected field (processed_rows or duration_seconds). Both reports are generated locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — returns validation error","More than 200 rows submitted — request rejected due to maxItems limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Missing required fields (row_id, dataset_group, date) — request rejected","Invalid field enum value (not processed_rows or duration_seconds) — schema error","All values null for selected field — IQR computation may be undefined or empty"],"whenToPreferThis":"Choose this endpoint when you need both a data quality audit and IQR-based outlier detection specifically on transformation throughput metrics (processed_rows, duration_seconds) in a single low-cost call. It is ideal for data engineering workflows, ETL pipeline monitoring, and pre-reporting data validation where you have up to 200 rows and want two independent analytical perspectives without any external data lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:57.959Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-record-quality-audit-iqr-outlier-flags-1ce68f42"}