{"uid":"cap_vQCBqLxOdwnDFOR4WHnUv","slug":"data-reconciliation-adjacent-row-changes-iqr-outlier-flags-a0c8b1ed","name":"Data Reconciliation: Adjacent Row Changes + IQR Outlier Flags","description":"Data reconciliation — Adjacent row changes + IQR outlier flags: Adjacent row changes + 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-11-157?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_WxVDeqbOGiOX_a4lnNfst","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 reconciliation rows (source_total vs target_total) and produces two reports: adjacent row-to-row change analysis and IQR-based outlier flagging.","exampleAgentPrompt":"Can you run adjacent row change analysis and IQR outlier flagging on my reconciliation data? I have 28 rows across two dataset groups — 'ledger-A' and 'ledger-B' — with dates in October 2025, and I want to analyze the source_total field.","exampleUseCases":[{"title":"Financial ledger reconciliation audit","prompt":"I have 50 rows of daily ledger reconciliation data with source_total and target_total values for groups 'emea' and 'apac' from Q3 2025 — can you run the adjacent row changes and IQR outlier detection on the source_total field so I can spot anything suspicious?"},{"title":"ETL pipeline data quality check","prompt":"After our ETL run, I have 120 reconciliation records across dataset groups 'raw' and 'processed' for September 2025. Run both the row-change and IQR outlier reports on target_total so I can see if any rows deviate badly from the norm."},{"title":"Month-end close anomaly detection","prompt":"I need to check our month-end close figures — I have 80 reconciliation rows with source_total and target_total for 'cost-center-1' and 'cost-center-2' dated November 2025. Flag any IQR outliers and show me where adjacent row changes are largest for source_total."}],"resultDescription":"Returns two independent analytical reports for the submitted rows: (1) adjacent row change analysis showing value-to-value deltas between consecutive rows for the selected field, and (2) IQR (interquartile range) outlier flags identifying which rows have statistically unusual values. Both reports are computed locally with no external data lookups.","failureModes":["More than 200 rows submitted — request will be rejected","Missing required fields (row_id, dataset_group, date, source_total, target_total) cause validation error","Malformed date strings (non-YYYY-MM-DD format) fail schema validation","Numeric values outside ±1,000,000,000,000 range cause rejection","Invalid field enum value (not 'source_total' or 'target_total') causes error","Empty rows array causes rejection"],"whenToPreferThis":"Choose this endpoint when you need lightweight, self-contained statistical analysis of reconciliation record sets — specifically adjacent row delta tracking and IQR-based outlier detection — without requiring external data sources, predictions, or professional assessments. Ideal for data quality checks on financial reconciliation pipelines, ETL validation, and audit workflows where you have up to 200 rows of source/target total pairs and need two complementary anomaly reports in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:48.843Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-adjacent-row-changes-iqr-outlier-flags-a0c8b1ed"}