{"uid":"cap_OScaEnffVdCDqWtT2pzpn","slug":"damaged-stock-numeric-row-ordering-two-measure-correlation-559adfe1","name":"Damaged Stock Numeric Row Ordering + Two-Measure Correlation","description":"Damaged stock — Numeric row ordering + Two-measure correlation: Numeric row ordering + Two-measure correlation for supplied damaged stock records (handled_units, damaged_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-18-120?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","handled_units","damaged_units"],"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},"damaged_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"handled_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","damaged_units":1,"handled_units":10},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","damaged_units":2,"handled_units":20},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","damaged_units":3,"handled_units":15},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","damaged_units":4,"handled_units":30}],"maxItems":200,"minItems":1},"field":{"enum":["handled_units","damaged_units"],"type":"string","default":"handled_units"}}},"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_koW7AIyxssYX4ycGwIZy-","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":"Sorts damaged stock records by row number and computes Pearson/rank correlation between handled_units and damaged_units across up to 200 supplied rows.","exampleAgentPrompt":"I have 4 rows of damaged stock data — row-1 group-a 2026-10-01 handled=10 damaged=1, row-2 group-b 2026-10-02 handled=20 damaged=2, row-3 group-a 2026-10-03 handled=15 damaged=3, row-4 group-b 2026-10-04 handled=30 damaged=4 — can you sort those records numerically by row and compute the correlation between handled_units and damaged_units?","exampleUseCases":[{"title":"Retail store damage correlation audit","prompt":"I have weekly data from two store groups showing how many units were handled and how many were damaged — here are 50 rows with row_id, store_group, date, handled_units, and damaged_units. Sort them numerically and tell me how correlated handling volume is with damage count."},{"title":"Warehouse throughput vs damage analysis","prompt":"Can you take my 120 rows of warehouse stock records and run a numeric sort plus a two-measure correlation between handled_units and damaged_units so I can see if busier days cause more damage?"},{"title":"Multi-date store group damage trend check","prompt":"I've got damaged stock records for group-a and group-b across 30 dates. Please order the rows numerically and compute the correlation between the handled and damaged unit counts — I want two separate report outputs from the same data."}],"resultDescription":"Returns two independent analytical reports from shared local engines: (1) the input rows sorted in numeric row order, and (2) a two-measure correlation analysis between handled_units and damaged_units, including a correlation coefficient or equivalent statistic. No external lookups or predictions are performed.","failureModes":["More than 200 rows submitted — request exceeds row limit","Missing required fields (row_id, date, handled_units, damaged_units) — validation error","Date field not matching YYYY-MM-DD pattern — schema rejection","Null values in both numeric fields for a row — may affect correlation computation","Single-row input — correlation between two measures is undefined with n=1"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of damaged stock records with handled_units and damaged_units fields and need both a numeric row sort and a two-measure correlation between those fields in a single call. It is a low-cost ($0.01 USDC), self-contained local computation with no external dependencies, ideal for offline batch analysis of retail or warehouse damage data where no real-time lookup or predictive modeling is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:11:22.344Z","isFirstParty":false,"canonicalSlug":"damaged-stock-numeric-row-ordering-two-measure-correlation-559adfe1"}