{"uid":"cap_nOE1O73_IGGF4rKV3yHsQ","slug":"elevation-samples-string-normalisation-adjacent-row-changes-7e087f31","name":"Elevation Samples — String Normalisation + Adjacent Row Changes","description":"Elevation samples — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied elevation samples records (elevation_m, sample_weight). 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-13-029?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","elevation_m","sample_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"elevation_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"sample_weight":{"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","elevation_m":10,"sample_weight":1,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","elevation_m":20,"sample_weight":2,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","elevation_m":15,"sample_weight":3,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","elevation_m":30,"sample_weight":4,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["elevation_m","sample_weight"],"type":"string","default":"elevation_m"}}},"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_2BjMoMVWRirXL6dxb6iOl","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":"Analyzes elevation sample records by normalising string fields and detecting adjacent row changes for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"I have a batch of elevation sample records with station groups and dates — can you normalize the string fields and show me where adjacent rows change in elevation_m for these 4 rows: row-1 group-a 2026-10-01 10m weight 1, row-2 group-b 2026-10-02 20m weight 2, row-3 group-a 2026-10-03 15m weight 3, row-4 group-b 2026-10-04 30m weight 4?","exampleUseCases":[{"title":"Audit elevation station string consistency","prompt":"I have 50 elevation sample records from different stations and I want to normalize the station_group strings and see where adjacent rows change — can you run both reports on the elevation_m field for rows like row-1 through row-50 across group-a and group-b?"},{"title":"Detect consecutive elevation measurement shifts","prompt":"Can you analyze these 10 elevation readings and tell me which adjacent rows show changes in elevation_m? I also need the string fields normalized. Here are the records: row-1 group-north 2026-01-01 500m weight 1.5, row-2 group-south 2026-01-02 520m weight 2.0, and so on up to row-10."},{"title":"Quality check sample_weight adjacent transitions","prompt":"Run string normalization and adjacent row change detection on my elevation sample dataset using sample_weight as the field — I have 20 rows across station groups alpha and beta from 2026-03-01 to 2026-03-20 with weights ranging from 1 to 10."}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report covering the station_group and other string fields across all submitted rows, and (2) an adjacent row changes report identifying where consecutive rows differ in the selected numeric field (elevation_m or sample_weight). Both reports are computed locally without 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, elevation_m, sample_weight) returns an error","Null values for both numeric fields may limit adjacent-change analysis","Field enum value outside 'elevation_m' or 'sample_weight' is rejected","Payment failure via x402 protocol blocks the request"],"whenToPreferThis":"Choose this endpoint when you have elevation sample tabular data (up to 200 rows) and need both string field normalisation and adjacent row change detection in a single call for $0.01. Prefer this over general-purpose data tools when your data specifically contains elevation_m and sample_weight columns with station_group identifiers, and you want two bundled reports without external API dependencies or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:38:47.069Z","isFirstParty":false,"canonicalSlug":"elevation-samples-string-normalisation-adjacent-row-changes-7e087f31"}