{"uid":"cap_-SgqxnTHZv4CriED8PJyB","slug":"land-parcel-observations-record-quality-audit-string-normalisation-f63dc11a","name":"Land Parcel Observations — Record Quality Audit + String Normalisation + Grouped Numeric Summary","description":"Land parcel observations — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied land parcel observations records (area_m2, perimeter_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-14-194?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","area_m2","perimeter_m"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"area_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"perimeter_m":{"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","area_m2":10,"perimeter_m":1,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","area_m2":20,"perimeter_m":2,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","area_m2":15,"perimeter_m":3,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","area_m2":30,"perimeter_m":4,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["area_m2","perimeter_m"],"type":"string","default":"area_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_wXXeTaKgoiacUxzzddsow","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 on up to 200 land parcel observation records: a record quality audit, string normalisation, and a grouped numeric summary of area or perimeter measurements.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and grouped numeric summary on my land parcel observations? I have 4 rows with fields row_id, station_group, date, area_m2, and perimeter_m — please analyse the area_m2 field for the grouped summary.","exampleUseCases":[{"title":"Parcel survey data quality check","prompt":"I've got 150 rows of land parcel observations with area_m2 and perimeter_m values collected in the field — can you audit them for quality issues, normalise the station_group strings, and give me a grouped numeric summary of area_m2 by station group?"},{"title":"Cleaning messy station group labels","prompt":"My parcel dataset has inconsistently formatted station_group labels across 80 rows. Can you run the string normalisation and quality audit reports on these records so I know what needs fixing before I load them into the database?"},{"title":"Grouped perimeter analysis by zone","prompt":"I need a grouped numeric summary of perimeter_m values across my land parcel records — 60 rows broken into different station groups. Can you also run the quality audit at the same time to flag any bad rows?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging malformed, missing, or out-of-range values; (2) string normalisation output for the station_group field; and (3) a grouped numeric summary (statistics by station_group) for the selected numeric field (area_m2 or perimeter_m). All processing is local — no external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, station_group, date, area_m2, perimeter_m) causes schema rejection","Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error","Selecting an invalid field value (not 'area_m2' or 'perimeter_m') returns an enum error","Empty rows array is rejected (minItems: 1)","Numeric values outside ±1,000,000,000,000 are rejected"],"whenToPreferThis":"Choose this endpoint when you have up to 200 land parcel observation records and need three bundled analytical reports — quality audit, string normalisation, and grouped numeric summary — in a single low-cost call. It is ideal for pre-ingestion data validation or exploratory analysis of field survey data where no external lookup, live data, or predictive modelling is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:57.557Z","isFirstParty":false,"canonicalSlug":"land-parcel-observations-record-quality-audit-string-normalisation-f63dc11a"}