{"uid":"cap_Z7SSC7hOJUU5Qnj9wSO4e","slug":"supplier-delivery-evidence-string-normalisation-exact-row-deduplication-8f471f6f","name":"Supplier Delivery Evidence — String Normalisation & Exact Row Deduplication","description":"Supplier delivery evidence — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied supplier delivery evidence records (deliveries, on_time_deliveries). 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-company-15-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","deliveries","on_time_deliveries"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"deliveries":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"on_time_deliveries":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","deliveries":10,"company_group":"group-a","on_time_deliveries":1},{"date":"2026-10-02","row_id":"row-2","deliveries":20,"company_group":"group-b","on_time_deliveries":2},{"date":"2026-10-03","row_id":"row-3","deliveries":15,"company_group":"group-a","on_time_deliveries":3},{"date":"2026-10-04","row_id":"row-4","deliveries":30,"company_group":"group-b","on_time_deliveries":4}],"maxItems":200,"minItems":1}}},"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_JDpC4rPI1bph0f1CiUFcc","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 strings and removes exact duplicate rows from supplier delivery evidence records (deliveries and on-time deliveries) for up to 200 rows across 2 reports.","exampleAgentPrompt":"Can you clean up this supplier delivery dataset — normalise the company group strings and remove any exact duplicate rows? I have up to 200 rows with fields like row_id, company_group, date, deliveries, and on_time_deliveries.","exampleUseCases":[{"title":"Deduplicating merged supplier delivery feeds","prompt":"I've merged two supplier delivery exports and there are a bunch of duplicate rows — can you deduplicate them and normalise the company group names? Here are the rows with row_id, company_group, date, deliveries, and on_time_deliveries fields."},{"title":"Cleaning on-time delivery records before KPI reporting","prompt":"Before I run our on-time delivery KPI report, I need to clean the raw evidence data — strip duplicate rows and standardise the supplier name strings. The dataset has about 150 rows with deliveries and on_time_deliveries counts per company group per day."},{"title":"Standardising supplier names across delivery evidence","prompt":"Our delivery evidence file has inconsistent company group name formatting and some repeated rows — can you normalise the strings and deduplicate it? I'll give you the rows with row_id, date, company_group, deliveries, and on_time_deliveries."}],"resultDescription":"Two cleaned reports for the supplied delivery evidence dataset: one covering string-normalised records and one covering exact-row-deduplicated records, processed locally without any external lookup or live data enrichment. Up to 200 input rows are supported per call.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, company_group, date, deliveries, on_time_deliveries) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Numeric values for deliveries or on_time_deliveries outside allowed range cause errors","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and exact row deduplication specifically on supplier delivery evidence data (deliveries and on_time_deliveries columns) for datasets of up to 200 rows, and do not need live lookups, predictive analytics, or external enrichment. It is cost-effective at $0.01 USDC for two reports per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T00:51:54.618Z","isFirstParty":false,"canonicalSlug":"supplier-delivery-evidence-string-normalisation-exact-row-deduplication-8f471f6f"}