{"uid":"cap_Z1BFkhhJ5LYt-WcdCeX3G","slug":"data-reconciliation-numeric-row-ordering-iqr-outlier-flags-42e84084","name":"Data Reconciliation — Numeric Row Ordering + IQR Outlier Flags","description":"Data reconciliation — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied data reconciliation records (source_total, target_total). 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-11-119?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_total","target_total"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_total":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"target_total":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_total":10,"target_total":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_total":20,"target_total":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_total":15,"target_total":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_total":30,"target_total":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["source_total","target_total"],"type":"string","default":"source_total"}}},"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_XmnN_RRdkltJDp1Tw9Gmx","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":"Sorts reconciliation rows by numeric value and flags statistical outliers using IQR analysis across source_total and target_total fields for up to 200 rows.","exampleAgentPrompt":"I need to check my reconciliation data for outliers — can you sort these rows by source_total and flag any IQR outliers? Here are my records: row-1 on 2024-01-01 in group-A with source_total 100 and target_total 98, row-2 on 2024-01-02 in group-A with source_total 5000 and target_total 4900, row-3 on 2024-01-03 in group-B with source_total 110 and target_total 105.","exampleUseCases":[{"title":"Monthly close reconciliation anomaly check","prompt":"I have 50 rows from our month-end reconciliation — can you sort them by source_total and use IQR to flag any rows that look like statistical outliers? I want two reports, one for source_total and one for target_total."},{"title":"ETL pipeline data drift detection","prompt":"We're comparing source and target totals from our ETL pipeline across different dataset groups. Can you order these 80 rows by value and highlight which ones are outliers based on IQR? Use source_total as the primary field."},{"title":"Accounts payable discrepancy triage","prompt":"Here are 120 accounts payable reconciliation records with source_total and target_total for group 'AP-2024'. Sort them numerically and flag any IQR outliers so I can prioritize which rows to investigate first."}],"resultDescription":"Returns two independent analytical reports for the submitted rows: (1) a numeric ordering/ranking of rows by the selected field, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range. Both reports use local analytical computation with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected due to maxItems limit","Missing required fields (row_id, dataset_group, date, source_total, or target_total) cause validation errors","Invalid date format (non YYYY-MM-DD) will fail schema validation","Numeric values outside ±1 trillion range will be rejected","All-null source_total or target_total may produce degenerate IQR output"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis of reconciliation data — specifically numeric ordering and IQR outlier detection — without requiring external data lookups, predictions, or professional assessments. Best for data quality workflows, ETL validation, and financial reconciliation pipelines with up to 200 rows where cost efficiency ($0.01 for two reports) matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:59.124Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-numeric-row-ordering-iqr-outlier-flags-42e84084"}