{"uid":"cap_SedATXQwzLj-Oh-KSaU3P","slug":"tourism-observations-string-normalisation-duplicate-key-report-efc6adc2","name":"Tourism Observations — String Normalisation + Duplicate Key Report","description":"Tourism observations — String normalisation + Duplicate key report: String normalisation + Duplicate key report for supplied tourism observations records (visitor_count, overnight_stays). 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-economics-14-021?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","visitor_count","overnight_stays"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"visitor_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"overnight_stays":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","visitor_count":10,"overnight_stays":1},{"date":"2026-10-02","region":"group-b","row_id":"row-2","visitor_count":20,"overnight_stays":2},{"date":"2026-10-03","region":"group-a","row_id":"row-3","visitor_count":15,"overnight_stays":3},{"date":"2026-10-04","region":"group-b","row_id":"row-4","visitor_count":30,"overnight_stays":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_tRMWf6vW4M0fcj5mYHmCu","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":"Analyzes up to 200 tourism observation rows (visitor_count, overnight_stays) producing two local reports: string normalisation and duplicate key detection.","exampleAgentPrompt":"Can you run string normalisation and a duplicate key check on my tourism observations? I have about 50 rows with fields like row_id, region, date, visitor_count, and overnight_stays — here they are.","exampleUseCases":[{"title":"Pre-load tourism data quality check","prompt":"I'm about to import 120 rows of regional tourism data into our dashboard — can you normalize the region strings and flag any duplicate row IDs before I load it? Each row has a row_id, region, date, visitor_count, and overnight_stays."},{"title":"Monthly visitor dataset deduplication","prompt":"We just received our monthly tourism report with 80 observations across different regions and dates. Can you check it for duplicate keys and normalise the string fields so everything is consistent?"},{"title":"Audit overnight stays dataset for ETL pipeline","prompt":"Before we push this batch of 150 tourism records into the ETL pipeline, can you run a duplicate key report and string normalisation on them? The rows have region names, dates, visitor counts, and overnight stay figures."}],"resultDescription":"Returns two independent analytical reports for the submitted tourism rows: (1) a string normalisation report identifying and correcting inconsistent or malformed string values in fields like region and date, and (2) a duplicate key report flagging any rows that share the same key identifiers (e.g. row_id), all processed locally without external lookups.","failureModes":["Payload exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, region, date, visitor_count, overnight_stays) cause row-level validation errors","Malformed date strings not matching YYYY-MM-DD pattern may be flagged or rejected","Numeric values outside the allowed range (-1e12 to 1e12) may cause schema validation failures","Empty rows array returns an error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need two specific data quality operations — string normalisation and duplicate key detection — on tourism observation data (visitor_count, overnight_stays) in a single affordable call. Prefer it over general-purpose data cleaning tools when your dataset is bounded (≤200 rows), you want local analytical processing with no external data lookups, and cost predictability at $0.01 per call matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:24.388Z","isFirstParty":false,"canonicalSlug":"tourism-observations-string-normalisation-duplicate-key-report-efc6adc2"}