{"uid":"cap_3OEiQXVX1BghDPUDsj5c-","slug":"replenishment-timing-string-normalisation-daily-sum-series-6e5126f0","name":"Replenishment Timing — String Normalisation + Daily Sum Series","description":"Replenishment timing — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied replenishment timing records (lead_days, received_units). 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-12-027?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","lead_days","received_units"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"lead_days":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"store_group":{"type":"string","default":"","maxLength":80},"received_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","lead_days":10,"store_group":"group-a","received_units":1},{"date":"2026-10-02","row_id":"row-2","lead_days":20,"store_group":"group-b","received_units":2},{"date":"2026-10-03","row_id":"row-3","lead_days":15,"store_group":"group-a","received_units":3},{"date":"2026-10-04","row_id":"row-4","lead_days":30,"store_group":"group-b","received_units":4}],"maxItems":200,"minItems":1},"field":{"enum":["lead_days","received_units"],"type":"string","default":"lead_days"}}},"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_Piry2rHeffjBz3E7XamMn","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 two local analytical reports on replenishment timing data: string normalisation of store/group fields and a daily sum series for lead_days or received_units, across up to 200 rows.","exampleAgentPrompt":"I have replenishment timing records with store groups, dates, lead days, and received units — can you run string normalisation on the store group names and also give me a daily sum series for lead_days across these rows? Here are up to 200 rows including entries like store group 'group-a' on 2026-10-01 with lead_days 10 and received_units 1.","exampleUseCases":[{"title":"Daily lead time aggregation for retail stores","prompt":"I have about 150 replenishment records with dates, store groups, and lead_days values — can you give me a daily sum series for lead_days and also normalise the store group name strings so they're consistent?"},{"title":"Received units trend by date","prompt":"Can you process my replenishment data — around 80 rows with date, store_group, and received_units — and produce a daily sum series for received_units alongside a string normalisation report on the store group labels?"},{"title":"Cleaning and summarising multi-group replenishment logs","prompt":"I've got replenishment timing logs from multiple store groups across about 200 rows, each with a date, lead_days, and received_units. Please run string normalisation on the store_group field and generate a daily sum series for received_units."}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report cleaning the store_group field across all supplied rows, and (2) a daily sum series aggregating the chosen numeric field (lead_days or received_units) by date. No external lookups or predictions are made — all computation is local and deterministic.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, store_group, date, lead_days, received_units) causes rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array is not accepted (minItems: 1)","Invalid field enum value (not 'lead_days' or 'received_units') causes an error"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation of categorical label fields and a daily aggregation time series from replenishment timing data in a single low-cost call. It is ideal for retail and supply chain analysts cleaning and summarising up to 200 rows of replenishment logs without needing live data, external lookups, or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T12:41:19.810Z","isFirstParty":false,"canonicalSlug":"replenishment-timing-string-normalisation-daily-sum-series-6e5126f0"}