{"uid":"cap_DoqnO_XmJYCLv9Ssg6roR","slug":"damaged-stock-quality-audit-and-numeric-row-ordering-143610af","name":"Damaged Stock Quality Audit and Numeric Row Ordering","description":"Damaged stock — Record quality audit + Numeric row ordering: Record quality audit + Numeric row ordering 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-18-007?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_vHV68qUIIuspI4yCCYTU_","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 damaged stock records: a data quality audit and a numeric row ordering, for up to 200 rows of handled/damaged unit data.","exampleAgentPrompt":"Can you run a quality audit and numeric row ordering on my damaged stock records? I have 12 rows covering store groups North and South from 2025-01-01 to 2025-01-12, each with handled_units and damaged_units counts — please order by damaged_units.","exampleUseCases":[{"title":"Retail warehouse damage data audit","prompt":"I've got 50 rows of damaged stock records from our three store groups for last quarter — each row has a row ID, date, store group, handled units, and damaged units. Can you run a quality audit to flag any bad or missing values, and also order the rows by damaged_units so I can see which entries had the most damage?"},{"title":"Spot-check incoming supplier damage logs","prompt":"We just received a batch of 80 damage log entries from our supplier with row IDs, dates, store groups, handled units, and damaged units. Can you audit the data quality to catch any issues and give me a numeric ordering by handled_units?"},{"title":"Monthly store group damage ranking","prompt":"Here are 35 rows of our monthly damaged stock report — each row has a row ID, store group, date, handled_units, and damaged_units. Please run the quality audit on them and rank the rows by damaged_units so I know which store groups are performing worst."}],"resultDescription":"Two independent local reports: (1) a data quality audit identifying issues such as missing values, out-of-range numbers, or malformed dates across the submitted rows; and (2) a numeric row ordering ranking rows by the specified field (handled_units or damaged_units). Results cover up to 200 input rows and are computed entirely from the supplied data with no external lookups.","failureModes":["Input exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, date, handled_units, damaged_units) cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern rejected","Numeric values outside allowed range cause schema errors","Empty rows array returns error","Invalid field enum value (not handled_units or damaged_units) causes rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of damaged stock records (with handled_units and damaged_units) and need both a data quality audit and a numeric ordering in a single low-cost call. It is well-suited for retail and warehouse contexts where you want to validate data integrity and rank records locally without any external API calls, predictions, or professional assessments. At $0.01 USDC for two reports, it is cost-effective for batch validation of damage logs from multiple store groups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:32:35.932Z","isFirstParty":false,"canonicalSlug":"damaged-stock-quality-audit-and-numeric-row-ordering-143610af"}