{"uid":"cap_KwbuVBwL2x36qeb6v3Gfi","slug":"forecast-verification-inputs-numeric-row-ordering-date-by-category-553246f3","name":"Forecast Verification Inputs — Numeric Row Ordering + Date by Category Pivot","description":"Forecast verification inputs — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot for supplied forecast verification inputs records (forecast_value, observed_value). 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-24-122?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","forecast_value","observed_value"],"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},"forecast_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","forecast_value":10,"observed_value":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","forecast_value":20,"observed_value":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","forecast_value":15,"observed_value":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","forecast_value":30,"observed_value":4}],"maxItems":200,"minItems":1},"field":{"enum":["forecast_value","observed_value"],"type":"string","default":"forecast_value"}}},"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_ahPw1VcRomX6KavhvBLgU","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 forecast verification data (forecast vs observed values) by producing two local reports: numeric row ordering and a date-by-category pivot, for up to 200 rows.","exampleAgentPrompt":"I have forecast verification records for two station groups over four dates — row-1 through row-4, group-a and group-b, with forecast values 10, 20, 15, 30 and observed values 1, 2, 3, 4 — can you run the numeric row ordering and date-by-category pivot reports on the forecast_value field for me?","exampleUseCases":[{"title":"Weather station forecast accuracy review","prompt":"I've got forecast vs observed temperature readings for three weather station groups across October — about 80 rows with dates, row IDs, and station group labels. Can you give me a numeric ordering of the forecast_value field and a date-by-category pivot grouped by station group?"},{"title":"Daily model verification batch summary","prompt":"Here are 150 forecast verification records from our NWP model run, each with a date, station_group, forecast_value, and observed_value. Please produce the numeric row ranking and the date-by-category pivot for the observed_value field so I can check where the model drifted."},{"title":"Forecast QA pivot for two regions","prompt":"I need two quick analytical reports on this set of 60 forecast verification rows covering group-north and group-south across two weeks — rank them numerically by forecast_value and show me how the values pivot across dates by category."}],"resultDescription":"Returns two analytical reports computed locally on the supplied data: (1) a numerically ordered ranking of rows by the selected field (forecast_value or observed_value), and (2) a date-by-category pivot table cross-tabulating values by date and station_group. No external data is fetched; all analysis is performed on the provided rows (up to 200).","failureModes":["Missing required row fields (row_id, date, station_group, forecast_value, observed_value) causes validation error","Date strings not matching YYYY-MM-DD pattern are rejected","More than 200 rows submitted exceeds the maxItems limit","Invalid field enum value (not 'forecast_value' or 'observed_value') causes rejection","Null numeric values may affect ordering and pivot aggregation results","Empty rows array (minItems:1 violated) returns error"],"whenToPreferThis":"Choose this endpoint when you have forecast verification tabular data (forecast vs observed numeric values with dates and group labels) and need both a ranked numeric ordering and a date-by-category pivot in a single low-cost call. Ideal for weather model verification workflows, batch QA pipelines, or any scenario where you supply your own data and need two complementary analytical views without live lookups or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:38:42.922Z","isFirstParty":false,"canonicalSlug":"forecast-verification-inputs-numeric-row-ordering-date-by-category-553246f3"}