{"uid":"cap_nol0wVS7f9HKWLoFBcOSW","slug":"returns-handling-analytics-record-quality-audit-string-normalisation-41ce0a10","name":"Returns Handling Analytics — Record Quality Audit, String Normalisation & Keyed Dataset Comparison","description":"Returns handling — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied returns handling records (returned_units, processing_minutes). 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-retail-04-207?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","returned_units","processing_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"returned_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processing_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","returned_units":10,"processing_minutes":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","returned_units":20,"processing_minutes":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","returned_units":15,"processing_minutes":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","returned_units":30,"processing_minutes":4}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","returned_units","processing_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"returned_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processing_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","returned_units":10,"processing_minutes":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","returned_units":21,"processing_minutes":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","returned_units":17,"processing_minutes":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","returned_units":33,"processing_minutes":4}],"maxItems":200,"minItems":0}}},"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_KZJ5zi-sOorlq5ATnktFf","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 offline analytical reports on retail returns handling data: a record quality audit, string normalisation, and keyed dataset comparison for up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and keyed comparison on my returns handling data? I have two datasets — the primary one has rows like row-1, group-a, 2026-10-01, 10 returned units, 1 processing minute, and the comparison set has slightly different values for the same keys. Up to 200 rows each.","exampleUseCases":[{"title":"Spotting dirty data before reporting","prompt":"I need to audit my weekly returns records before sending them to management — can you run a quality check on these rows covering store groups A and B for October 2026, flagging any missing or invalid returned_units or processing_minutes values? Here are up to 150 rows."},{"title":"Comparing two extracts from different systems","prompt":"We pulled returns data from two separate warehouse systems for the same date range and I need to know where they diverge row by row — can you do a keyed dataset comparison between these two sets of up to 200 rows each, matched on row_id?"},{"title":"Normalising inconsistent store group labels","prompt":"Our returns records have inconsistent capitalisation and spacing in the store_group field across about 80 rows — can you run a string normalisation report on this dataset so we get clean, consistent labels?"}],"resultDescription":"Returns three structured analytical reports: (1) a record quality audit highlighting missing, null, or out-of-range values in returned_units and processing_minutes; (2) a string normalisation report cleaning and standardising text fields like store_group; (3) a keyed dataset comparison showing row-level differences between the primary and reference datasets matched by row_id. All analysis is performed locally with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, store_group, date, returned_units, processing_minutes) cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern rejected","Numeric values outside allowed range (-1e12 to 1e12) may cause errors","Empty rows array (minItems: 1 violated) returns an error","Mismatched row_id keys between primary and comparison datasets may result in incomplete comparison report"],"whenToPreferThis":"Choose this endpoint when you need a combined, cost-effective batch of three offline data quality reports — quality audit, string normalisation, and dataset comparison — on retail returns data (returned_units, processing_minutes) for up to 200 rows, all within a single $0.01 USDC call. It is ideal when no live lookup, prediction, or external action is required and you simply want to validate, clean, and reconcile two versions of a returns handling dataset.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:44:21.631Z","isFirstParty":false,"canonicalSlug":"returns-handling-analytics-record-quality-audit-string-normalisation-41ce0a10"}