{"uid":"cap_J5gv9ktM1ChCuDUmFy2Cr","slug":"returns-handling-string-normalisation-adjacent-row-changes-511f81ab","name":"Returns Handling — String Normalisation + Adjacent Row Changes","description":"Returns handling — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes 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-04-029?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},"field":{"enum":["returned_units","processing_minutes"],"type":"string","default":"returned_units"}}},"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_JyQwVGL9fQlr2YIz7tXB1","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":"Performs string normalisation and adjacent row change analysis on returns handling records (returned_units, processing_minutes) for up to 200 rows, producing 2 independent analytical reports.","exampleAgentPrompt":"Can you run string normalisation and adjacent row change analysis on my returns handling data? I have 4 rows: row-1 for group-a on 2026-10-01 with 10 returned_units and 1 processing_minute, row-2 for group-b on 2026-10-02 with 20 returned units and 2 minutes, row-3 for group-a on 2026-10-03 with 15 units and 3 minutes, row-4 for group-b on 2026-10-04 with 30 units and 4 minutes — analyse the returned_units field.","exampleUseCases":[{"title":"Retail store returns quality audit","prompt":"I have 50 rows of returns data across our store groups — can you normalise the string fields and show me adjacent row changes in returned_units so I can spot anomalies between consecutive days?"},{"title":"Processing time row-by-row comparison","prompt":"Run adjacent row change analysis on my processing_minutes for these 12 returns handling records across groups A and B — I want to see how processing time shifts from one row to the next."},{"title":"Multi-store returns data standardisation","prompt":"I need to clean up the store_group labels and check row-to-row shifts in returned_units across this dataset of 80 returns records — can you run the string normalisation and adjacent row changes reports on the returned_units field?"}],"resultDescription":"Two independent analytical reports covering: (1) string normalisation results for the supplied returns handling records, and (2) adjacent row change computations for the selected numeric field (returned_units or processing_minutes) across up to 200 input rows. No external lookups or predictions are performed — all analysis uses local engines on the supplied data.","failureModes":["Rows array is empty or missing — requires at least 1 row","More than 200 rows submitted — exceeds maxItems limit","Invalid date format not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, store_group, date, returned_units, processing_minutes) — schema validation failure","Invalid field selector — must be 'returned_units' or 'processing_minutes'","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and adjacent row change analysis on returns handling records in a single call. It is suitable for offline/batch analytics on up to 200 rows of retail returns data without requiring live lookups, external data sources, or predictions. Prefer it for cost-effective dual-report processing at $0.01 USDC per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-31T00:42:38.743Z","isFirstParty":false,"canonicalSlug":"returns-handling-string-normalisation-adjacent-row-changes-511f81ab"}