{"uid":"cap_4eFXRGSzx-doT9hqHNLwB","slug":"damaged-stock-quality-audit-and-base-100-index-series-55ed9654","name":"Damaged Stock Quality Audit and Base-100 Index Series","description":"Damaged stock — Record quality audit + Base-100 series: Record quality audit + Base-100 series 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-18-012?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"},"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_7M1K5F2ky2OnAHQcspAvR","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 supplied damaged stock data: a data quality audit and a base-100 index series, for up to 200 rows of handled/damaged unit records.","exampleAgentPrompt":"Run a quality audit and base-100 index series on my damaged stock data — here are 4 rows for store groups 'group-a' and 'group-b' from October 2026, with handled_units and damaged_units filled in; use handled_units as the field and row 0 as the base index.","exampleUseCases":[{"title":"Retail chain damage rate quality check","prompt":"I have 150 rows of daily damaged stock records across 10 store groups for Q3 — can you run a quality audit on them to flag any data issues, and also produce a base-100 index series for damaged_units starting from the first row?"},{"title":"Warehouse handling data normalization","prompt":"Run a base-100 index series on my handled_units data for these 80 warehouse rows from January through March, using row 0 as the base, and include the quality audit report so I can see if anything looks off."},{"title":"Store group damage trend audit","prompt":"I need to check the data quality of this damaged stock dataset for our two store groups — 'east-region' and 'west-region' — across 60 date rows, and get an indexed view of damaged_units normalized to base 100 starting at index 0."}],"resultDescription":"Two independent analytical reports: (1) a data quality audit flagging issues such as missing values, out-of-range figures, or formatting problems in the supplied rows; and (2) a base-100 index series for the selected field (handled_units or damaged_units), computed relative to the specified base row. No external data or predictions are involved — all analysis is performed on the supplied data only.","failureModes":["Rows array empty or missing — validation error returned","More than 200 rows supplied — request rejected with max-items error","Invalid date format (not YYYY-MM-DD) — schema validation failure","base_index out of range (>= number of rows supplied) — computation error","null values in handled_units or damaged_units may affect index calculations","Malformed row objects missing required fields — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of retail damaged stock records (handled_units, damaged_units) and need both a data quality audit and a base-100 indexed series in a single low-cost call. It is purely analytical with no external lookups, predictions, or side effects — ideal for offline data validation and normalization workflows. Prefer it over general-purpose analytics when you specifically need the combination of quality auditing and base-indexed series for the handled/damaged units domain.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:31:37.890Z","isFirstParty":false,"canonicalSlug":"damaged-stock-quality-audit-and-base-100-index-series-55ed9654"}