{"uid":"cap_lbJZy-T2xfMwrx1Aqdr3A","slug":"geospatial-tile-processing-string-normalisation-exact-row-deduplication-f8f183a0","name":"Geospatial Tile Processing — String Normalisation + Exact Row Deduplication","description":"Geospatial tile processing — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied geospatial tile processing records (tile_count, processing_seconds). 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-21-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","tile_count","processing_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"tile_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80},"processing_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","tile_count":10,"station_group":"group-a","processing_seconds":1},{"date":"2026-10-02","row_id":"row-2","tile_count":20,"station_group":"group-b","processing_seconds":2},{"date":"2026-10-03","row_id":"row-3","tile_count":15,"station_group":"group-a","processing_seconds":3},{"date":"2026-10-04","row_id":"row-4","tile_count":30,"station_group":"group-b","processing_seconds":4}],"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_jRi8nvSzFhrsVhY_Opcxw","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 deduplicates exact rows in geospatial tile processing records (tile_count, processing_seconds), returning 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up my geospatial tile processing records by normalising the station group strings and removing any exact duplicate rows? I have about 150 records with fields like row_id, station_group, date, tile_count, and processing_seconds — I need 2 analytical reports back.","exampleUseCases":[{"title":"Deduplicating satellite tile pipeline logs","prompt":"I have 180 rows of satellite tile processing logs with station_group names, tile_count, and processing_seconds per date — can you normalise the string fields and strip out any exact duplicate rows, then give me 2 reports summarising the cleaned data?"},{"title":"Cleaning station group label inconsistencies","prompt":"My geospatial pipeline exports records where the station_group field has inconsistent capitalisation and spacing. Can you normalise those strings and deduplicate the exact matching rows across about 120 records dated from 2026-09-01 to 2026-09-30?"},{"title":"Pre-analysis deduplication of tile metrics","prompt":"Before I run my downstream analysis, I need to clean up 200 tile processing records — row IDs, station groups, dates, tile counts, and processing seconds — by normalising strings and removing any exact duplicate entries. Please give me 2 reports on what was found."}],"resultDescription":"Returns 2 independent analytical reports based on the supplied geospatial tile processing records, covering string normalisation outcomes and exact row deduplication results across up to 200 input rows. No live lookups or external data are used; all analysis is performed locally on the supplied data.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Missing required fields (row_id, station_group, date, tile_count, processing_seconds) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Empty rows array (minItems:1 not met) returns error","Numeric fields outside allowed range (-1e12 to 1e12) rejected"],"whenToPreferThis":"Choose this endpoint when you have geospatial tile processing records (with tile_count and processing_seconds fields) that need string normalisation and exact duplicate row removal in a single call, and you want two analytical reports for up to 200 rows at minimal cost. It is ideal for pre-processing pipeline outputs before downstream analytics, with no dependency on external data sources or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:07.094Z","isFirstParty":false,"canonicalSlug":"geospatial-tile-processing-string-normalisation-exact-row-deduplication-f8f183a0"}