{"uid":"cap_G9csRCKBs9Ihaf5o0bu6O","slug":"business-event-participation-string-normalisation-exact-row-c33b143b","name":"Business Event Participation — String Normalisation + Exact Row Deduplication","description":"Business event participation — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied business event participation records (attendee_count, company_count). 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-19-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","attendee_count","company_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"attendee_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_count":1,"company_group":"group-a","attendee_count":10},{"date":"2026-10-02","row_id":"row-2","company_count":2,"company_group":"group-b","attendee_count":20},{"date":"2026-10-03","row_id":"row-3","company_count":3,"company_group":"group-a","attendee_count":15},{"date":"2026-10-04","row_id":"row-4","company_count":4,"company_group":"group-b","attendee_count":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_eD2UYlF665cIYOGeWgDyA","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 business event participation records containing attendee and company counts, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up my business event participation data — I have up to 200 rows with fields like row_id, company_group, date, attendee_count, and company_count, and I need string normalisation plus exact duplicate row removal, with two separate reports back?","exampleUseCases":[{"title":"Conference attendance deduplication","prompt":"I have a list of about 150 rows from our annual conference registration system — each row has a row_id, company_group, date, attendee_count, and company_count. Can you normalise the string fields and strip out any exact duplicate rows, and give me two reports showing what was cleaned up?"},{"title":"Event data pipeline quality check","prompt":"Before we load our business event participation records into the data warehouse, can you run string normalisation and exact deduplication on these rows? There are around 80 entries with company_group, date, attendee_count, and company_count fields, and I need two separate quality reports."},{"title":"Trade show data cleanup","prompt":"We collected participation data from three trade shows — about 120 rows total with company groups, dates, and attendee plus company counts — can you normalise the strings and remove any rows that are exact duplicates, returning two clean analytical reports?"}],"resultDescription":"Two independent reports per call: one covering string normalisation results (e.g. trimmed/standardised company_group and date strings) and one covering exact row deduplication results (identifying and removing fully identical rows), applied to the supplied event participation records of up to 200 rows.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, company_group, date, attendee_count, company_count) causes rejection","Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure","Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) cause rejection","Empty rows array (minItems:1 not met) causes validation error"],"whenToPreferThis":"Choose this endpoint when you need offline, local-engine string normalisation and exact row deduplication specifically for business event participation data (attendee_count and company_count fields) without any live lookup, prediction, or external action. It is cost-effective at $0.01 USDC for two reports on up to 200 rows and is well-suited for lightweight pre-processing or data quality pipelines where no internet-dependent enrichment is required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:18.843Z","isFirstParty":false,"canonicalSlug":"business-event-participation-string-normalisation-exact-row-c33b143b"}