{"uid":"cap_uu-i6JbjjptUFGxPpdFvj","slug":"time-series-completeness-duplicate-key-report-daily-sum-series-3bea06ef","name":"Time Series Completeness — Duplicate Key Report + Daily Sum Series","description":"Time series completeness — Duplicate key report + Daily sum series: Duplicate key report + Daily sum series for supplied time series completeness records (observed_points, expected_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-analytics-16-060?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","observed_points","expected_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_points":1,"observed_points":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_points":2,"observed_points":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_points","expected_points"],"type":"string","default":"observed_points"}}},"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_yLwmGJNaCLxWuxs3sw-Wm","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 supplied time series completeness records to produce a duplicate key report and a daily sum series for observed or expected data points, for up to 200 rows.","exampleAgentPrompt":"Can you run a duplicate key report and daily sum series on my time series completeness data? I have up to 50 rows with row_id, dataset_group, date, observed_points, and expected_points — analyze the observed_points field.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I have daily completeness records for two dataset groups — 'pipeline-a' and 'pipeline-b' — with observed and expected point counts for the past 30 days. Can you check for duplicate row IDs and give me a daily sum of observed_points across all rows?"},{"title":"Sensor data gap detection","prompt":"We're tracking sensor readings completeness across multiple groups. Can you run both a duplicate key check and a daily sum series on our expected_points field for these 120 rows of completeness records?"},{"title":"ETL job monitoring report","prompt":"My ETL job produces daily completeness logs with observed_points and expected_points per dataset group. Can you analyze these records — up to 80 rows — for any duplicate keys and compute the daily sum totals for observed_points?"}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying rows with duplicate row_id/date/dataset_group combinations, and (2) a daily sum series aggregating the chosen field (observed_points or expected_points) by date — all computed locally with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, observed_points, expected_points) cause validation errors","Invalid date format (not YYYY-MM-DD) causes schema rejection","Empty rows array returns an error","Numeric values outside allowed range (-1T to 1T) are rejected"],"whenToPreferThis":"Choose this endpoint when you need both a duplicate key audit and a daily sum aggregation on time series completeness records in a single call. It is ideal for data engineering pipelines, ETL monitoring, and completeness auditing workflows where you have up to 200 rows of observed/expected point data and want two complementary reports for the cost of one call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:02.806Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-duplicate-key-report-daily-sum-series-3bea06ef"}