{"uid":"cap__41i_2XrD6tk1uDBodqY5","slug":"water-service-coverage-record-quality-audit-string-normalisation-79c7ded0","name":"Water Service Coverage Record Quality Audit & String Normalisation","description":"Water service coverage — Record quality audit + String normalisation: Record quality audit + String normalisation 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-19-001?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_nDBInT1KyOqXKflWun3Ht","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":"Audits water service coverage records for quality issues and normalises region/date strings, producing two independent reports for up to 200 rows of household data.","exampleAgentPrompt":"Can you audit these water service coverage records for data quality issues and normalise the region and date strings? I have 4 rows: row-1 with region 'group-a', date '2026-10-01', served_households 10, total_households 1; row-2 with region 'group-b', date '2026-10-02', served_households 20, total_households 2; row-3 with region 'group-a', date '2026-10-03', served_households 15, total_households 3; and row-4 with region 'group-b', date '2026-10-04', served_households 30, total_households 4.","exampleUseCases":[{"title":"Municipal water audit before reporting","prompt":"I need to quality-check our quarterly water service coverage data before submitting to the regulator — can you run a record quality audit and string normalisation on these 50 rows? Each row has a row_id, region name, date, served_households, and total_households."},{"title":"Detect impossible coverage ratios","prompt":"Some of our water coverage records look off — served_households is higher than total_households in several rows. Can you audit these 120 records for data quality problems and flag anything that looks wrong?"},{"title":"Normalise region strings across datasets","prompt":"We merged water coverage data from three field teams and the region names are inconsistently formatted — things like 'North Zone', 'north-zone', and 'NORTH ZONE'. Can you run string normalisation on these 80 rows so we have consistent region labels?"}],"resultDescription":"Two independent analytical reports: (1) a record quality audit identifying issues such as null values, impossible ratios (served > total households), out-of-range numbers, malformed dates, and missing fields across up to 200 rows; (2) a string normalisation report showing standardised/cleaned versions of region and date string fields. Reports are generated locally with no external lookups or live data access.","failureModes":["Input array is empty (minItems:1 violation) — request rejected","More than 200 rows submitted (maxItems:200 violation) — request rejected","Row missing required fields (row_id, region, date, served_households, total_households) — validation error","Date string not matching YYYY-MM-DD pattern — row-level error flagged","Numeric values outside allowed range (-1T to +1T) — schema rejection","Payment not provided or insufficient (x402 protocol) — 402 response"],"whenToPreferThis":"Choose this endpoint when you have water service coverage tabular data (served_households, total_households per region and date) and need both a data quality audit and string normalisation in a single low-cost call. It is purpose-built for water utility/infrastructure coverage records specifically, as opposed to generic CSV validators. Best when batch processing up to 200 rows in one shot at fixed cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:27.767Z","isFirstParty":false,"canonicalSlug":"water-service-coverage-record-quality-audit-string-normalisation-79c7ded0"}