{"uid":"cap_E6YWCZ7xymA0fESlUNTwf","slug":"coordinate-quality-checks-string-normalisation-keyed-dataset-comparison-8ea818e8","name":"Coordinate Quality Checks — String Normalisation + Keyed Dataset Comparison","description":"Coordinate quality checks — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied coordinate quality checks records (checked_points, flagged_points). 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-23-036?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","checked_points","flagged_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station_group":{"type":"string","default":"","maxLength":80},"checked_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"flagged_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","checked_points":10,"flagged_points":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","checked_points":20,"flagged_points":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","checked_points":15,"flagged_points":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","checked_points":30,"flagged_points":4}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","checked_points","flagged_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station_group":{"type":"string","default":"","maxLength":80},"checked_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"flagged_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","checked_points":10,"flagged_points":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","checked_points":21,"flagged_points":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","checked_points":17,"flagged_points":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","checked_points":33,"flagged_points":4}],"maxItems":200,"minItems":0}}},"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_3WKbTvNNot_pw4KC4KcFQ","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":"Performs string normalisation and keyed dataset comparison on two supplied sets of coordinate quality check records (checked_points, flagged_points), producing 2 independent analytical reports for up to 200 rows.","exampleAgentPrompt":"Compare these two batches of coordinate quality check records for station groups group-a and group-b across October 2026 — the first dataset has rows with checked_points and flagged_points from our primary run, and the second dataset has slightly different values from a secondary run — give me the string normalisation and keyed comparison reports for both.","exampleUseCases":[{"title":"Audit two QA runs for weather stations","prompt":"I have two sets of coordinate quality check results from our weather station network for October 2026 — the primary sweep covered groups alpha and beta with checked_points and flagged_points per day, and the secondary sweep has slightly different counts. Can you normalize the station group strings and compare the two datasets row by row to show me where they diverge?"},{"title":"Validate coordinate data before pipeline merge","prompt":"Before I merge these two coordinate QA datasets into our pipeline, can you run a keyed comparison on them? Both have up to 150 rows with row_id, station_group, date, checked_points, and flagged_points — I need to see a normalised string report and a side-by-side diff of any discrepancies."},{"title":"Spot flagged point anomalies across station groups","prompt":"I've got two snapshots of coordinate quality checks for our sensor grid — each snapshot has about 80 rows with station_group, date, checked_points, and flagged_points. Can you normalize the group names and compare the two snapshots to highlight where flagged_points differ significantly between them?"}],"resultDescription":"Returns 2 independent analytical reports: a string normalisation report (standardising station_group and other string fields) and a keyed dataset comparison report (matching rows by row_id/station_group/date and surfacing differences in checked_points and flagged_points between the two supplied datasets). No external lookups or live data are involved.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, station_group, date, checked_points, flagged_points) cause validation error","Date fields not matching YYYY-MM-DD pattern result in schema rejection","Both 'rows' and 'other' arrays must be provided; omitting either causes incomplete comparison","Null numeric values in checked_points or flagged_points may affect comparison accuracy"],"whenToPreferThis":"Choose this endpoint when you have two structured datasets of coordinate quality check records and need both string normalisation and a keyed row-by-row comparison in a single call. It is best suited for offline/batch analytical use cases where no live geospatial lookup, external API calls, or real-time predictions are needed. Prefer alternatives if you need live coordinate validation, geocoding, or professional assessment services.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:54.058Z","isFirstParty":false,"canonicalSlug":"coordinate-quality-checks-string-normalisation-keyed-dataset-comparison-8ea818e8"}