{"uid":"cap_fYVEG5w-0yp7ZgOUrQ8Xf","slug":"building-footprint-observations-numeric-row-ordering-adjacent-row-e2d319d9","name":"Building Footprint Observations — Numeric Row Ordering + Adjacent Row Changes","description":"Building footprint observations — Numeric row ordering + Adjacent row changes: Numeric row ordering + Adjacent row changes 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-16-116?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_oxsbowe0OioCaKlVeVcdY","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":"Performs numeric row ordering and adjacent row change analysis on up to 200 building footprint observation records (footprint_m2 or height_m fields).","exampleAgentPrompt":"I have 50 building footprint observations with footprint_m2 and height_m values — can you run a numeric row ordering report and adjacent row change analysis on them so I can see how footprint_m2 values rank and shift row by row?","exampleUseCases":[{"title":"Rank buildings by footprint size","prompt":"I have a dataset of 80 building records with dates, footprint areas, and heights — can you order them numerically by footprint_m2 and show me how each row's value changes compared to the one before it?"},{"title":"Detect height anomalies in sequential data","prompt":"Here are 120 building height observations grouped by station — run the numeric row ordering and adjacent row changes analysis on the height_m field so I can spot any unusual jumps between consecutive entries."},{"title":"Track footprint changes across construction phases","prompt":"I've got 30 building footprint records from different construction phases across groups A and B — run both the numeric ordering and adjacent row change reports on footprint_m2 so I can see the progression."}],"resultDescription":"Returns two analytical reports: (1) a numeric row ordering report ranking the supplied rows by the selected field (footprint_m2 or height_m), and (2) an adjacent row changes report showing the delta between each consecutive row for the selected field, covering up to 200 input records.","failureModes":["Missing required row fields (row_id, date, station_group, footprint_m2, height_m) causes validation error","More than 200 rows submitted exceeds the maximum and will be rejected","Invalid date format (not YYYY-MM-DD) triggers a pattern mismatch error","Numeric field values outside the allowed range cause schema rejection","Empty rows array returns an error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need to quickly apply two complementary analytical passes — numeric ordering and sequential delta computation — to a batch of building footprint or height observations without any external data lookup or live prediction. It is ideal for offline analysis of structured building datasets of up to 200 rows where both ranking and row-to-row change detection are needed simultaneously in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:33:32.913Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-numeric-row-ordering-adjacent-row-e2d319d9"}