{"uid":"cap_PADYGIJfSNfQI4xzhxcL8","slug":"building-footprint-observations-record-quality-audit-string-d5faafdc","name":"Building Footprint Observations — Record Quality Audit + String Normalisation + Trailing Mean Series","description":"Building footprint observations — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series 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-16-199?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_E83Zp_xdjSddjEByr67Rd","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 three local analytical reports (record quality audit, string normalisation, and trailing mean series) on up to 200 rows of building footprint observation data (footprint_m2, height_m).","exampleAgentPrompt":"Run a record quality audit, string normalisation, and trailing mean series (window size 3, field footprint_m2) on my building footprint dataset: row-1 / group-a / 2026-10-01 / footprint_m2=120 / height_m=15, row-2 / group-b / 2026-10-02 / footprint_m2=200 / height_m=22, row-3 / group-a / 2026-10-03 / footprint_m2=null / height_m=18.","exampleUseCases":[{"title":"Urban dataset pre-processing quality check","prompt":"I have 50 building footprint records from our urban survey — can you audit their quality, normalise the station group strings, and compute a trailing mean (window 4) on footprint_m2 so I can see trends before loading into our database? Here are the rows: row-1, site-north, 2026-09-01, 300, 12; row-2, Site North, 2026-09-02, 310, 13 ... (and so on up to row-50)."},{"title":"Height data rolling average for construction portfolio","prompt":"Please run a trailing mean analysis with a window of 5 on the height_m field for these 30 building observation records, and also give me the quality audit and string normalisation reports so I can spot any dirty data before my report."},{"title":"Footprint anomaly detection prep","prompt":"I need to clean up and summarise 80 building footprint observation rows — run the record quality audit to find bad values, normalise the station_group strings, and compute a trailing mean series on footprint_m2 with window size 6. I'll paste the rows now."}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging missing, out-of-range, or malformed values across rows; (2) a string normalisation report standardising station_group and other string fields; and (3) a trailing mean series for the selected numeric field (footprint_m2 or height_m) computed over the specified window. All computed locally with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Invalid date format (not YYYY-MM-DD) causes schema rejection","Missing required fields (row_id, station_group, date, footprint_m2, height_m) causes per-row validation failure","Window size outside 2–200 range causes parameter rejection","Non-numeric values for footprint_m2 or height_m (unless null) cause processing errors","Payment failure via x402 protocol blocks request"],"whenToPreferThis":"Choose this endpoint when you need three combined analytical operations — quality audit, string normalisation, and trailing mean series — on building footprint data in a single low-cost call. It is ideal for pre-processing pipelines that need to validate and clean small-to-medium datasets (up to 200 rows) without any external data lookups or live predictions. Prefer it over general-purpose analytics tools when the dataset is specifically building footprint observations with footprint_m2 and height_m fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:50:50.083Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-record-quality-audit-string-d5faafdc"}