{"uid":"cap_LIDy9cYLTOgW_JVcfKRLx","slug":"replenishment-timing-string-normalisation-base-100-series-a61f894a","name":"Replenishment Timing — String Normalisation + Base-100 Series","description":"Replenishment timing — String normalisation + Base-100 series: String normalisation + Base-100 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-12-030?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_2KzGugrOdRjYwYgtK66Ua","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 analytical reports on supplied replenishment timing data: string normalisation of text fields and a base-100 indexed series for either lead_days or received_units.","exampleAgentPrompt":"I have replenishment timing records for up to 4 store groups with dates, lead_days, and received_units — can you run string normalisation on the text fields and build a base-100 series for lead_days anchored at row index 0?","exampleUseCases":[{"title":"Lead time index for retail planning","prompt":"I've got 150 rows of replenishment timing data with store_group, date, and lead_days — please normalise the string fields and create a base-100 index series for lead_days starting from row 0 so I can compare lead time changes over time."},{"title":"Received units trend baseline analysis","prompt":"Can you take my 80-row replenishment dataset with received_units by store group and date, normalise the store group strings, and build a base-100 series for received_units anchored at row index 5?"},{"title":"Multi-store replenishment data cleanup","prompt":"I have replenishment records across groups like 'group-a' and 'group-B' with inconsistent capitalisation — run string normalisation and give me a base-100 indexed series for lead_days from row index 0 across all 120 rows."}],"resultDescription":"Two analytical reports: (1) a string normalisation report cleaning text fields such as store_group across all supplied rows, and (2) a base-100 indexed numeric series for the selected field (lead_days or received_units) anchored at the specified base_index row — covering up to 200 input rows per call.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, store_group, date, lead_days, received_units) on any row causes validation failure","Invalid date format (must match YYYY-MM-DD pattern)","base_index out of range (must be between 0 and 199 and within actual row count)","Numeric field values outside allowed range (±1,000,000,000,000)","All-null values for the selected numeric field may produce an empty or degenerate series"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of retail replenishment timing records (with lead_days and/or received_units) and need both string normalisation of categorical fields and a base-100 indexed time series in a single low-cost call. It is ideal for offline batch analytics on supplied data without requiring external lookups or live data connections.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:34:48.569Z","isFirstParty":false,"canonicalSlug":"replenishment-timing-string-normalisation-base-100-series-a61f894a"}