{"uid":"cap_YbP2-U_OLTyP0rOx0C4Rz","slug":"forecast-verification-inputs-record-quality-audit-string-ab036afb","name":"Forecast Verification Inputs — Record Quality Audit + String Normalisation + Secondary-Measure Weighted Mean","description":"Forecast verification inputs — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied forecast verification inputs records (forecast_value, observed_value). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 ro","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-24-205?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_LR7d_3vAbELmtbFoBDMWp","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":"Runs three local analytical reports (record quality audit, string normalisation, and secondary-measure weighted mean) on up to 200 forecast verification rows containing forecast and observed values.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and secondary-measure weighted mean on my forecast verification records? I have 4 rows — row-1 for station group-a on 2026-10-01 with forecast 10 and observed 1, row-2 for group-b on 2026-10-02 with forecast 20 and observed 2, row-3 for group-a on 2026-10-03 with forecast 15 and observed 3, and row-4 for group-b on 2026-10-04 with forecast 30 and observed 4 — use forecast_value as the primary field.","exampleUseCases":[{"title":"Pre-analysis quality check on forecast data","prompt":"I have a batch of 50 weather station forecast vs observed readings for October. Can you audit them for record quality issues, normalise the station group strings, and give me a weighted mean of the forecast_value field? Here are the rows with row IDs, station groups, dates, forecast values, and observed values."},{"title":"Weighted mean summary for observed values","prompt":"Run the three analytical reports — record quality audit, string normalisation, and weighted mean — on these 30 forecast verification rows using observed_value as the field for the weighted mean calculation."},{"title":"Data hygiene check before model evaluation","prompt":"Before I hand off these forecast verification records to our model evaluation pipeline, can you check them for quality issues, normalise any inconsistent station group strings, and compute the secondary-measure weighted mean? I'll supply up to 200 rows with their row IDs, dates, station groups, forecasts, and observed values."}],"resultDescription":"Three separate analytical reports: (1) a record quality audit flagging issues in the input rows, (2) a string normalisation report cleaning up station_group and other string fields, and (3) a secondary-measure weighted mean computed over the specified numeric field (forecast_value or observed_value) across all submitted rows. All processing is performed locally with no external lookups.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, station_group, date, forecast_value, observed_value) — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema validation failure","Field selector not one of 'forecast_value' or 'observed_value' — enum validation error","All numeric values null — weighted mean cannot be computed meaningfully","Payment not completed — endpoint returns 402 or similar payment-required error"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous local analytical operations — quality audit, string normalisation, and weighted mean — on forecast/observed value pairs in a single $0.01 call. It is purpose-built for forecast verification data with station_group and date dimensions. Prefer it over single-report endpoints when you need all three reports together for up to 200 rows without any live external data fetching or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:46:11.153Z","isFirstParty":false,"canonicalSlug":"forecast-verification-inputs-record-quality-audit-string-ab036afb"}