{"uid":"cap_LmeX3fWR8c7-qmmQzDunq","slug":"building-footprint-observations-record-quality-audit-string-2a68c34b","name":"Building Footprint Observations — Record Quality Audit + String Normalisation + Adjacent Row Changes","description":"Building footprint observations — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied building footprint observations records (footprint_m2, height_m). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-16-200?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_aslh3Wkk6-SwMVP16FcGY","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 record quality, normalises strings, and detects adjacent row changes for up to 200 rows of building footprint observation data (footprint_m2, height_m), returning 3 independent analytical reports.","exampleAgentPrompt":"Can you run the record quality audit, string normalisation, and adjacent row changes analysis on these 50 building footprint records — I need all three reports for the footprint_m2 field across station groups A and B from October 2026?","exampleUseCases":[{"title":"Building dataset pre-processing audit","prompt":"I have 120 rows of building footprint observations from our urban survey, each with a footprint_m2 and height_m. Can you audit their quality, normalise any string inconsistencies in station_group labels, and flag where footprint_m2 changes between adjacent rows?"},{"title":"Construction project data validation","prompt":"Before we submit our building measurements to the planning authority, can you run a quality audit and adjacent row change detection on these 80 rows of height_m data across our three station groups, covering dates from 2026-09-01 to 2026-09-30?"},{"title":"Real estate footprint inventory check","prompt":"We've got 200 building footprint records from our property inventory — can you check them for record quality issues, normalise the station_group strings, and show us where the footprint_m2 values shift between consecutive rows?"}],"resultDescription":"Three independent analytical reports for the submitted building footprint rows: (1) a record quality audit identifying missing values, format issues, and data integrity problems; (2) a string normalisation report standardising station_group and other string fields; (3) an adjacent row changes report highlighting where footprint_m2 or height_m values differ between consecutive rows. All computed locally with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, station_group, date, footprint_m2, height_m) in any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Payment not provided or insufficient — 402 Payment Required","field enum value not one of footprint_m2 or height_m — validation error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 building footprint observation rows and need three bundled local analytical reports — quality audit, string normalisation, and adjacent row change detection — in a single low-cost call ($0.01 USDC). It is ideal for pre-processing building measurement datasets before downstream analysis, submission, or storage, and when no live lookup, prediction, or external data enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:11:10.341Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-record-quality-audit-string-2a68c34b"}