{"uid":"cap_AwXc0K-h4jqXdRM3JfkWK","slug":"procurement-research-string-normalisation-and-exact-row-deduplication-c2fb017a","name":"Procurement Research String Normalisation and Exact Row Deduplication","description":"Procurement research — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied procurement research records (quoted_amount, quoted_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-company-11-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","quoted_amount","quoted_units"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"quoted_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"quoted_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","quoted_units":1,"company_group":"group-a","quoted_amount":10},{"date":"2026-10-02","row_id":"row-2","quoted_units":2,"company_group":"group-b","quoted_amount":20},{"date":"2026-10-03","row_id":"row-3","quoted_units":3,"company_group":"group-a","quoted_amount":15},{"date":"2026-10-04","row_id":"row-4","quoted_units":4,"company_group":"group-b","quoted_amount":30}],"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_PfEWIPUMqJAmARgu178JX","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 procurement research records containing quoted_amount and quoted_units fields, producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up this procurement dataset by normalising the string fields and removing any exact duplicate rows? I have up to 200 records with columns row_id, company_group, date, quoted_amount, and quoted_units, and I need 2 analytical reports back.","exampleUseCases":[{"title":"Deduplicating supplier quote spreadsheet","prompt":"I've exported our supplier quotes into rows with row_id, company_group, date, quoted_amount, and quoted_units — can you normalise the text fields and strip out any exact duplicate rows, then give me the two summary reports?"},{"title":"Cleaning procurement data before analysis","prompt":"Before I run my spend analysis, I need this procurement research data cleaned up — normalise all the string values and remove exact duplicate entries across the quoted_amount and quoted_units columns. Here are my 150 rows."},{"title":"Standardising vendor quote records","prompt":"We received vendor quotes from several company groups and the data has inconsistent formatting and some repeated rows. Can you normalise the strings and deduplicate exactly matching records for me? I'll give you the rows with row_id, company_group, date, quoted_amount, and quoted_units."}],"resultDescription":"Returns 2 independent analytical reports covering (1) string-normalised procurement records and (2) exact row deduplication results, processed entirely from the supplied data using local analytical engines with no external lookups or predictions.","failureModes":["Exceeding 200 row limit causes rejection","Missing required fields (row_id, company_group, date, quoted_amount, quoted_units) causes validation error","Invalid date format (not YYYY-MM-DD) causes schema error","quoted_amount or quoted_units values outside ±1,000,000,000,000 range cause validation failure","Empty rows array causes rejection"],"whenToPreferThis":"Choose this endpoint when you need offline, deterministic string normalisation and exact duplicate removal on procurement records (quoted_amount, quoted_units) with no live data lookup or external dependencies, and want two analytical report outputs for up to 200 rows at a flat cost of $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:43.389Z","isFirstParty":false,"canonicalSlug":"procurement-research-string-normalisation-and-exact-row-deduplication-c2fb017a"}