{"uid":"cap_3cTJBpCTfXQYSfhZciKyg","slug":"data-reconciliation-record-quality-audit-explicit-missing-value-fill-3af053e5","name":"Data Reconciliation — Record Quality Audit + Explicit Missing-Value Fill","description":"Data reconciliation — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill 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-11-019?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_DhhiUJGsrrjGUAbtwJpwA","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 fills missing values for source/target reconciliation records (up to 200 rows), returning two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and fill missing values using the median method on my reconciliation data — I have 4 rows across two groups (group-a and group-b) with source_total and target_total values, some of which are null, for dates in October 2026?","exampleUseCases":[{"title":"Financial pipeline reconciliation audit","prompt":"I have 150 rows of daily source and target totals from our finance pipeline — some source_total values are null. Can you audit the record quality and fill those missing source_total values using the median method?"},{"title":"ETL data validation before reporting","prompt":"Before I publish our monthly report, can you check these 80 reconciliation records across three dataset groups for quality issues and fill any missing target_total values using the mean?"},{"title":"Data warehouse source-target mismatch review","prompt":"I'm comparing data warehouse snapshots — here are 50 rows with row IDs, dates, dataset groups, and source/target totals. Can you audit them for quality problems and impute any missing source_total fields using zero fill?"}],"resultDescription":"Two independent analytical reports: (1) a record quality audit flagging completeness, validity, and integrity issues across the submitted rows, and (2) an explicit missing-value fill report showing imputed values for the specified field (source_total or target_total) using the chosen method (zero, mean, or median). No external data is fetched; all analysis uses local engines on the supplied data.","failureModes":["Submitting more than 200 rows causes a validation error","Missing required fields (row_id, dataset_group, date, source_total, target_total) causes rejection","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Numeric values outside ±1,000,000,000,000 are rejected","Unrecognized method or field enum values cause an error","Empty rows array (minItems: 1 violated) returns an error"],"whenToPreferThis":"Choose this endpoint when you need both a record quality audit AND explicit missing-value imputation on reconciliation data in a single call, especially for source/target financial or ETL datasets up to 200 rows. Prefer this over generic data profiling tools when your data is structured around source_total and target_total reconciliation pairs and you want two distinct reports (quality + imputation) from a local analytical engine without any external lookups or live data fetches.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:08.108Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-record-quality-audit-explicit-missing-value-fill-3af053e5"}