{"uid":"cap_UttWaCqKbc4TzH4MvxTPq","slug":"warehouse-bins-string-normalisation-daily-sum-series-d26b1819","name":"Warehouse Bins — String Normalisation + Daily Sum Series","description":"Warehouse bins — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied warehouse bins records (occupied_volume, available_volume). 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-13-027?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","occupied_volume","available_volume"],"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},"occupied_volume":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"available_volume":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","occupied_volume":10,"available_volume":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","occupied_volume":20,"available_volume":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","occupied_volume":15,"available_volume":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","occupied_volume":30,"available_volume":4}],"maxItems":200,"minItems":1},"field":{"enum":["occupied_volume","available_volume"],"type":"string","default":"occupied_volume"}}},"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_wjqIeJ7UpXDhBRxXKGHh1","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 string fields and computes daily sum time series for warehouse bin occupancy and availability volume data (up to 200 rows, 2 reports per call).","exampleAgentPrompt":"Can you normalise the store_group strings and generate a daily sum series for occupied_volume across these warehouse bin records? I have 4 rows: row-1 in group-a on 2026-10-01 with occupied_volume 10 and available_volume 1, row-2 in group-b on 2026-10-02 with 20 and 2, row-3 in group-a on 2026-10-03 with 15 and 3, and row-4 in group-b on 2026-10-04 with 30 and 4.","exampleUseCases":[{"title":"Daily occupancy trend for warehouse audit","prompt":"I have a set of warehouse bin records with dates, store groups, and occupied volumes — can you normalise the store group names and show me the daily sum of occupied_volume so I can spot trends over the past month?"},{"title":"Available space rollup by date for restocking","prompt":"Run string normalisation and a daily sum series on available_volume for these warehouse bin rows — I need to know how much total available space we had each day to plan restocking schedules."},{"title":"Retail inventory data cleaning and aggregation","prompt":"I've got up to 150 rows of retail warehouse bin data with messy store_group labels and I need two things: cleaned/normalised string fields and a daily total for occupied_volume — can you produce both reports in one go?"}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report cleaning the store_group and related string fields across the submitted rows, and (2) a daily sum series aggregating the selected numeric field (occupied_volume or available_volume) by date. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected or truncated","Invalid date format (not YYYY-MM-DD) — schema validation error","Missing required fields (row_id, date, occupied_volume, available_volume) — validation failure","Numeric values outside ±1,000,000,000,000 range — schema rejection","Invalid field enum value (not occupied_volume or available_volume) — error","Payment not included or insufficient — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and a daily sum time series computed together on warehouse bin data in a single low-cost call. Ideal for retail/logistics pipelines that need to clean categorical labels and roll up volume metrics by date without external dependencies. Best when your dataset fits within 200 rows and you want two complementary reports for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:36:36.379Z","isFirstParty":false,"canonicalSlug":"warehouse-bins-string-normalisation-daily-sum-series-d26b1819"}