{"uid":"cap_71k3FvBO4ntCM399JPNVt","slug":"returns-handling-string-normalisation-trailing-mean-series-b27fc6cf","name":"Returns Handling — String Normalisation + Trailing Mean Series","description":"Returns handling — String normalisation + Trailing mean series: String normalisation + Trailing mean series 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-04-028?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_JeJXhr3ZBc-w3S7-ZK6zi","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 string normalisation and trailing mean series analytics on retail returns data (returned_units, processing_minutes) for up to 200 rows, producing two local reports per call.","exampleAgentPrompt":"Can you run string normalisation and trailing mean series (window of 7) on my returns handling data for returned_units — I have about 50 rows with date, row_id, store_group, returned_units, and processing_minutes?","exampleUseCases":[{"title":"Retail returns trend smoothing","prompt":"I have 120 rows of daily returns data across store groups A, B, and C with returned_units and processing_minutes — can you compute a trailing mean series with a window of 5 on returned_units, along with string normalisation on the records?"},{"title":"Processing time efficiency analysis","prompt":"Run a trailing mean series with window size 10 on processing_minutes for my 80-row returns dataset, and also normalise the string fields — I want to see if our processing times are trending up or down across store groups."},{"title":"Small-batch returns audit","prompt":"I've got 30 returns handling records with row_id, date, store_group, returned_units, and processing_minutes. Can you run the string normalisation report and a trailing mean (window 2) on returned_units to get a quick overview?"}],"resultDescription":"Two analytical reports per call: (1) a string normalisation report cleaning and standardising string fields in the supplied returns records, and (2) a trailing mean series for the selected numeric field (returned_units or processing_minutes) computed over the specified sliding window — all derived locally from the supplied data, with no external lookup or prediction.","failureModes":["Fewer than 1 or more than 200 rows submitted — returns validation error","Window size larger than number of rows — may produce empty or insufficient series","Invalid date format (not YYYY-MM-DD) — schema validation failure","Missing required fields (row_id, date, returned_units, processing_minutes) — rejected","Non-numeric values in returned_units or processing_minutes where numbers expected — null handling or error","Field enum value not one of 'returned_units' or 'processing_minutes' — validation error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local analytical computation on retail returns data — specifically string normalisation combined with a trailing mean series — without requiring any live data lookup, external prediction, or professional assessment. It is cost-effective at $0.01 USDC for two reports on up to 200 rows. Prefer it over general-purpose analytics tools when you already have structured returns records and need a fast, deterministic dual-report output.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-31T00:43:20.442Z","isFirstParty":false,"canonicalSlug":"returns-handling-string-normalisation-trailing-mean-series-b27fc6cf"}