{"uid":"cap_PASrIHfuI1e8S6AVP57HT","slug":"building-footprint-observations-string-normalisation-numeric-row-f9ad4400","name":"Building Footprint Observations — String Normalisation + Numeric Row Ordering","description":"Building footprint observations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied building footprint observations records (footprint_m2, height_m). 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-weather-16-025?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","footprint_m2","height_m"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"height_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"footprint_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","height_m":1,"footprint_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","height_m":2,"footprint_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","height_m":3,"footprint_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","height_m":4,"footprint_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["footprint_m2","height_m"],"type":"string","default":"footprint_m2"}}},"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_n9_kw_Emihd4SOFNw9Dwf","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 orders rows numerically for building footprint observation records (footprint_m2, height_m) across up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Can you run string normalisation and numeric row ordering on my building footprint observations? I have 4 rows with footprint_m2 and height_m values for two station groups — group-a and group-b — dated from 2026-10-01 to 2026-10-04, and I want the reports ordered by footprint_m2.","exampleUseCases":[{"title":"Urban survey data cleanup","prompt":"I have 150 building footprint observation records from our urban survey with station groups and dates — can you normalise the string fields and sort the rows by footprint_m2 so I get two clean analytical reports?"},{"title":"Building height dataset ordering","prompt":"I need to sort my building height observation records numerically by height_m and clean up the station group strings — there are about 80 rows across multiple groups and dates, can you run both reports?"},{"title":"Pre-analysis footprint data preparation","prompt":"Before I hand off these building footprint records to our analyst, can you normalise the text fields and apply numeric row ordering on the footprint_m2 column? It's around 200 rows with row IDs, dates, and station groups."}],"resultDescription":"Two analytical reports covering: (1) string-normalised versions of the submitted building footprint observation records (cleaning station_group and other text fields), and (2) numerically ordered rows based on the selected numeric field (footprint_m2 or height_m). No external lookups or predictions are included — all processing is local and analytical.","failureModes":["More than 200 rows submitted — endpoint rejects input exceeding maxItems limit","Missing required fields (row_id, date, footprint_m2, height_m, station_group) causes validation error","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Numeric values outside allowed range (±1,000,000,000,000) rejected","Invalid field selector (not 'footprint_m2' or 'height_m') causes enum validation error","Payment not provided or insufficient USDC causes x402 payment-required response"],"whenToPreferThis":"Choose this endpoint when you have building footprint observation records (with footprint_m2 and height_m fields) that need text/string normalisation and numeric sorting as a data preparation step, and you want both operations delivered as two reports in a single API call for $0.01 USDC. It is purpose-built for this specific combination of operations on building observation data and avoids the overhead of general-purpose ETL pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:37:51.998Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-string-normalisation-numeric-row-f9ad4400"}