{"uid":"cap_o2LO0l7LEufVnF9uY39gv","slug":"land-use-observations-string-normalisation-exact-row-deduplication-c8cf2f0d","name":"Land Use Observations — String Normalisation + Exact Row Deduplication","description":"Land use observations — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied land use observations records (area_hectares, parcel_count). 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-economics-22-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","area_hectares","parcel_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"parcel_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"area_hectares":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","parcel_count":1,"area_hectares":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","parcel_count":2,"area_hectares":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","parcel_count":3,"area_hectares":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","parcel_count":4,"area_hectares":30}],"maxItems":200,"minItems":1}}},"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_W0APHvGXb5eAB21XXDlum","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":"Normalises strings and removes exact duplicate rows from land use observation records containing area_hectares and parcel_count fields, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a batch of up to 200 land use observation records with region names, dates, area_hectares, and parcel_count values — can you clean them up by normalising the strings and removing any exact duplicate rows, then give me two analytical reports on the results?","exampleUseCases":[{"title":"Deduplicating regional land survey records","prompt":"I've got 150 land use observation rows from our regional survey — regions like 'group-a' and 'group-b', each with area in hectares and parcel counts — can you normalise all the string fields and strip out any exact duplicates, then give me the two reports?"},{"title":"Pre-analysis data cleaning for parcel dataset","prompt":"Before we run our land planning analysis, can you take these 80 land use records with area_hectares and parcel_count and clean them up — normalise the region and date strings and deduplicate any identical rows?"},{"title":"Audit land use data quality before reporting","prompt":"We need to submit a land use report but our data has messy strings and possible duplicate entries — can you run string normalisation and exact row deduplication on our 200 observation records and produce the two analytical reports?"}],"resultDescription":"Two independent analytical reports summarising the results of string normalisation and exact row deduplication applied to the submitted land use observation records (area_hectares, parcel_count) for up to 200 rows. Reports are generated locally with no external lookups or predictions.","failureModes":["Exceeding 200 row limit returns a validation error","Missing required fields (row_id, region, date, area_hectares, parcel_count) causes rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Numeric values outside allowed range cause input rejection","Empty rows array returns an error","Payment not included or insufficient USDC triggers x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have land use observation data (area_hectares, parcel_count) up to 200 rows and need both string normalisation and exact row deduplication performed together in two analytical reports, with no need for live lookups, predictions, or external data enrichment. It is cost-effective at $0.01 USDC for two reports and suits batch data cleaning workflows before downstream analysis.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:37:17.448Z","isFirstParty":false,"canonicalSlug":"land-use-observations-string-normalisation-exact-row-deduplication-c8cf2f0d"}