{"uid":"cap_tHvYkF5Gu2huyOSM_7CA4","slug":"water-service-coverage-string-normalisation-duplicate-key-report-ad4602f8","name":"Water Service Coverage — String Normalisation + Duplicate Key Report","description":"Water service coverage — String normalisation + Duplicate key report: String normalisation + Duplicate key report for supplied water service coverage records (served_households, total_households). 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-19-021?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","served_households","total_households"],"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},"total_households":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"served_households":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","total_households":1,"served_households":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","total_households":2,"served_households":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","total_households":3,"served_households":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","total_households":4,"served_households":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_QRxDcWm87r3g6fxhCtT9z","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 string normalisation and duplicate key detection on water service coverage records (served_households, total_households) for up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you run string normalisation and a duplicate key check on my water service coverage records — I have up to 200 rows with fields like row_id, region, date, served_households, and total_households, and I need two separate reports flagging any string inconsistencies and duplicate keys?","exampleUseCases":[{"title":"Pre-analysis data cleaning for coverage dataset","prompt":"I've got a batch of water service coverage records — around 150 rows with region names, dates, and household counts — and before I start any analysis I need to normalise the strings and flag any duplicate row IDs. Can you run both reports?"},{"title":"Utility reporting data validation","prompt":"We're preparing a quarterly water utility report and our coverage dataset has messy region strings and possibly repeated row keys. Can you audit the served_households and total_households records for string normalisation issues and duplicate keys across all our rows?"},{"title":"ETL pipeline data quality gate","prompt":"Before we load our water service coverage data into the warehouse, I want to catch duplicate row_ids and any non-standard region strings. We have about 80 rows with date, region, served_households, and total_households — can you run the duplicate key and string normalisation checks?"}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report identifying inconsistencies or non-standard formatting in text fields such as region names, and (2) a duplicate key report flagging rows with repeated row_id, region, or date combinations — all derived locally from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows causes rejection — trim input to at most 200 records","Missing required fields (row_id, region, date, served_households, total_households) on any row causes validation error","Invalid date format (must match YYYY-MM-DD) causes schema rejection","row_id values exceeding 80 characters are rejected","Payment of 0.01 USDC not supplied or rejected causes 402 response","Empty rows array (minItems: 1 violated) causes error"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and duplicate key detection in a single call for water service coverage data with served_households and total_households fields. It is ideal for pre-analysis data cleaning, ETL quality gates, or utility reporting pipelines where you want two bundled reports at minimal cost ($0.01 USDC) without any external lookups or predictions. Prefer alternatives if you need other report types (e.g. numeric summaries, histograms) or if your dataset exceeds 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:36:02.362Z","isFirstParty":false,"canonicalSlug":"water-service-coverage-string-normalisation-duplicate-key-report-ad4602f8"}