{"uid":"cap_51em1yyLdTwcWb3LGBqWw","slug":"returns-handling-string-normalisation-exact-row-deduplication-288f3b4c","name":"Returns Handling — String Normalisation & Exact Row Deduplication","description":"Returns handling — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied returns handling records (returned_units, processing_minutes). 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-retail-04-020?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}}},"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_SlHOG4g6NKk61zCAKctqv","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":"Cleans and deduplicates up to 200 returns-handling records by normalising strings and removing exact duplicate rows, producing 2 independent analytical reports on returned_units and processing_minutes.","exampleAgentPrompt":"Can you clean up my returns data for October — I have about 150 rows with store_group, date, returned_units, and processing_minutes fields — normalise the strings and remove any exact duplicate rows, then give me 2 reports on the returned_units and processing_minutes?","exampleUseCases":[{"title":"Retail returns data deduplication audit","prompt":"I've got 180 rows of returns handling records from our store groups covering last quarter — each row has a date, store_group, returned_units, and processing_minutes. Can you normalise the strings and strip out any exact duplicate rows, then give me the two analytical reports?"},{"title":"Processing time cleanup for warehouse ops","prompt":"Our warehouse team exported returns processing logs with about 120 rows — there are definitely some duplicates and inconsistent string casing in the store_group field. Please normalise everything and deduplicate the rows, and send back reports on the returned_units and processing_minutes columns."},{"title":"Multi-store returns reconciliation prep","prompt":"Before I import our multi-store returns data into the dashboard, I need to clean 95 rows: normalise store_group strings and remove any exact duplicate entries across the date, returned_units, and processing_minutes fields. Can you run that and give me the two summary reports?"}],"resultDescription":"Two independent analytical reports covering the cleaned dataset: one on returned_units and one on processing_minutes. Rows have been string-normalised and exact duplicates removed, with results covering up to 200 input records.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, store_group) — validation error","Malformed date format (not YYYY-MM-DD) — schema rejection","Empty rows array — minimum 1 item required","Numeric values outside allowed range (-1e12 to 1e12) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need offline, local-engine string normalisation and exact-row deduplication specifically for retail returns handling records (returned_units, processing_minutes) with up to 200 rows and want two bundled analytical reports at a fixed low cost — without needing live lookups, predictions, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:39:15.161Z","isFirstParty":false,"canonicalSlug":"returns-handling-string-normalisation-exact-row-deduplication-288f3b4c"}