{"uid":"cap_drLE4qvw6eUfTjntssxnd","slug":"forecast-verification-inputs-record-quality-audit-exact-row-2afe3ac6","name":"Forecast Verification Inputs — Record Quality Audit + Exact Row Deduplication + Daily Sum Series","description":"Forecast verification inputs — Record quality audit + Exact row deduplication + Daily sum series: Record quality audit + Exact row deduplication + Daily sum series 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 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-24-215?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_dfoHE5GLwjj5nK4xxcY4L","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, exact row deduplication, and daily sum series) on up to 200 forecast verification input rows containing forecast and observed values.","exampleAgentPrompt":"Can you run a record quality audit, exact duplicate check, and daily sum series on my forecast verification data? Here are up to 200 rows with row_id, station_group, date, forecast_value, and observed_value fields — I want all three reports on the forecast_value column.","exampleUseCases":[{"title":"Weather forecast accuracy data cleanup","prompt":"I have 150 rows of forecast vs observed temperature readings across two station groups with dates in October 2026. Can you audit the record quality, flag any exact duplicate rows, and give me a daily sum series for the forecast_value field?"},{"title":"Daily observed value aggregation by date","prompt":"Take these forecast verification records — each has a row_id, station_group, date, forecast_value, and observed_value — and run the three reports focusing on observed_value so I can see the daily totals, spot duplicates, and check overall data quality."},{"title":"Pre-analysis QA for forecast dataset","prompt":"Before I start my model evaluation, I need to validate this batch of 80 forecast verification rows. Please do a full record quality audit, deduplicate exact matches, and compute a daily sum series on forecast_value so I know what I'm working with."}],"resultDescription":"Three independent analytical reports on the supplied forecast verification rows: (1) a record quality audit flagging null values, out-of-range entries, and structural issues; (2) an exact row deduplication report identifying and listing duplicate records; and (3) a daily sum series aggregating either forecast_value or observed_value by date across all rows.","failureModes":["Empty rows array or more than 200 rows causes validation failure","Rows missing required fields (row_id, date, forecast_value, observed_value) are rejected","Malformed date strings not matching YYYY-MM-DD pattern cause schema validation errors","Invalid field selector (not 'forecast_value' or 'observed_value') returns an error","Payment failure via x402 protocol blocks execution"],"whenToPreferThis":"Use this endpoint when you need a combined three-in-one batch analysis pass over forecast verification data without any external lookups or live predictions. It is ideal when you already have paired forecast and observed numeric records and want simultaneous quality auditing, deduplication, and daily aggregation in a single low-cost call. Prefer this over building individual analysis pipelines when your dataset is under 200 rows and turnaround speed matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:49:55.990Z","isFirstParty":false,"canonicalSlug":"forecast-verification-inputs-record-quality-audit-exact-row-2afe3ac6"}