{"uid":"cap_zG11FEcCvDSF3VbYlGrtU","slug":"land-parcel-observations-record-quality-audit-numeric-interval-filter-1ea67a0d","name":"Land Parcel Observations — Record Quality Audit + Numeric Interval Filter","description":"Land parcel observations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied land parcel observations records (area_m2, perimeter_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-14-008?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_X-SpFOYaLKAgd6cgRyM1N","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 and filters land parcel observation rows by a numeric interval (area_m2 or perimeter_m) for up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you audit the quality of these 50 land parcel records and filter them to only keep rows where area_m2 is between 0 and 5000? Here are the rows with row_id, station_group, date, area_m2, and perimeter_m fields.","exampleUseCases":[{"title":"Pre-analysis parcel data quality check","prompt":"I have 120 land parcel survey records with area_m2 and perimeter_m values — can you run a quality audit on them and also filter to only rows where area_m2 falls between 100 and 50000?"},{"title":"Outlier perimeter removal for mapping","prompt":"Before I import these parcel boundaries into our GIS, can you audit the record quality and remove any rows where perimeter_m is outside the range 10 to 20000? I've got about 80 rows to check."},{"title":"Station group data validation for reporting","prompt":"We have land parcel observations from two station groups and need a quality report plus a filter showing only parcels where area_m2 is between 500 and 100000 — can you process all 200 rows?"}],"resultDescription":"Returns two reports: (1) a record quality audit identifying missing, null, or malformed values across the submitted rows; and (2) a numeric interval filter report listing which rows fall within the specified minimum–maximum range for the chosen field (area_m2 or perimeter_m). No external data sources are consulted; all analysis is performed on the supplied rows only.","failureModes":["More than 200 rows submitted — exceeds maximum batch size","Missing required fields (row_id, station_group, date, area_m2, or perimeter_m) on any row","Invalid date format (must match YYYY-MM-DD pattern)","Minimum value greater than maximum value in interval filter — logically inverted range","Non-numeric values passed for area_m2 or perimeter_m where a number is expected","Empty rows array submitted"],"whenToPreferThis":"Choose this endpoint when you need both a data quality audit and a numeric range filter on land parcel observation data (area_m2 or perimeter_m) in a single call, with up to 200 rows and no need for external lookups or predictions. It is especially useful as a preprocessing step before geospatial analysis or GIS import to catch bad records and bound datasets to valid numeric ranges.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:35:25.230Z","isFirstParty":false,"canonicalSlug":"land-parcel-observations-record-quality-audit-numeric-interval-filter-1ea67a0d"}