{"uid":"cap_l0CXgzuNNcEmLEOCm491H","slug":"replenishment-timing-string-normalisation-and-exact-row-deduplication-7ead632e","name":"Replenishment Timing String Normalisation and Exact Row Deduplication","description":"Replenishment timing — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication 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-12-020?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}}},"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_9n7WJr3lsDycWtokTO_vh","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":"Normalises strings and removes exact duplicate rows from replenishment timing records containing lead_days and received_units fields, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up my replenishment timing records — I have about 150 rows with store_group, date, lead_days, and received_units fields — normalise any inconsistent strings and remove exact duplicate rows, then give me the two summary reports?","exampleUseCases":[{"title":"Retail replenishment data pipeline cleanup","prompt":"I'm preparing replenishment timing data for our retail stores before loading it into our warehouse. Can you take these 120 rows with store_group, date, lead_days, and received_units, normalise the string fields, strip any exact duplicates, and give me the two clean-up reports?"},{"title":"Supply chain lead time deduplication","prompt":"Our lead_days and received_units records for store group 'Northeast' have a bunch of exact duplicate rows from a data export error — can you run string normalisation and exact row deduplication on these 80 replenishment timing entries and show me what was removed?"},{"title":"Pre-analysis replenishment record audit","prompt":"Before I hand off this replenishment timing dataset to the analytics team, I want to make sure the store_group strings are consistent and there are no exact duplicate rows — can you process these 200 replenishment records and give me both the normalisation and deduplication reports?"}],"resultDescription":"Two analytical reports covering (1) string normalisation outcomes for text fields such as store_group and date, and (2) exact row deduplication results identifying and removing fully duplicate records, applied to the submitted replenishment timing rows containing lead_days and received_units.","failureModes":["Exceeding 200 row limit returns a validation error","Missing required fields (row_id, store_group, date, lead_days, received_units) cause row-level rejection","Malformed date strings not matching YYYY-MM-DD pattern are rejected","Numeric values outside the allowed range (-1e12 to 1e12) are rejected","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and exact duplicate removal specifically for replenishment timing records with lead_days and received_units fields, with up to 200 rows and no need for external data lookup, prediction, or live enrichment. It is cost-effective at $0.01 USDC for two reports and is ideal for pre-processing steps before loading retail inventory data into analytics pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T13:17:37.817Z","isFirstParty":false,"canonicalSlug":"replenishment-timing-string-normalisation-and-exact-row-deduplication-7ead632e"}