{"uid":"cap_CltNTmm6b1qU0ceOK-DZH","slug":"data-reconciliation-analytics-record-quality-audit-string-35f56484","name":"Data Reconciliation Analytics: Record Quality Audit + String Normalisation + Numeric Interval Filter","description":"Data reconciliation — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied data reconciliation records (source_total, target_total). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-197?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_kB3RJSkvHAMGY_bn5JYEi","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":"Runs three local analytical reports on up to 200 reconciliation rows: a record quality audit, string normalisation, and a numeric interval filter on source/target totals.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric interval filter on my reconciliation data? Here are up to 200 rows with row_id, dataset_group, date, source_total, and target_total — filter on the source_total field between 0 and 100.","exampleUseCases":[{"title":"Pre-load reconciliation data validation","prompt":"I have 150 reconciliation rows with source_total and target_total values and I need to check them for quality issues, normalise the string fields, and filter the source_total column to only see records between 0 and 50000 before I load them into the warehouse."},{"title":"Spotting dirty string data in grouped records","prompt":"Can you run a string normalisation report on my dataset_group and row_id fields across these 80 reconciliation records? I also want a quality audit and want to see which target_total values fall between -1000 and 1000."},{"title":"Financial reconciliation discrepancy audit","prompt":"Run a full quality audit, string normalisation, and numeric range filter on these 200 reconciliation rows — filter on target_total between 100 and 500000 — so I can find any dirty or out-of-range records before my month-end close."}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging data issues across the supplied rows, (2) a string normalisation report for string fields such as row_id and dataset_group, and (3) a numeric interval filter report identifying which records fall within the specified min/max range for the chosen field (source_total or target_total). All computed locally with no external lookups.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, dataset_group, date, source_total, target_total) — validation error","Date field not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside ±1,000,000,000,000 — schema rejection","minimum greater than maximum — likely produces empty interval filter results","Payment not completed — 402 response, no reports returned"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and numeric interval filtering — on reconciliation data in a single low-cost call. Ideal when you have up to 200 source/target rows and want offline, deterministic analysis without any external API calls, predictions, or professional assessments. Not suitable if you need live data lookup, ML-based anomaly detection, or more than 200 rows per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:52.015Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-analytics-record-quality-audit-string-35f56484"}