{"uid":"cap_fyTSuoi7C9bRdvOl1Wpvm","slug":"time-series-completeness-analyzer-record-quality-audit-deduplication-92cc5e59","name":"Time Series Completeness Analyzer — Record Quality Audit + Deduplication + Adjacent Row Changes","description":"Time series completeness — Record quality audit + Exact row deduplication + Adjacent row changes: Record quality audit + Exact row deduplication + Adjacent row changes for supplied time series completeness records (observed_points, expected_points). 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-analytics-16-217?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_AAqmo1P5D9SM2EYEEd8RA","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 analytical reports on time series completeness records: record quality audit, exact row deduplication, and adjacent row changes detection — all locally, up to 200 rows per call.","exampleAgentPrompt":"Audit these time series completeness records for data quality issues, exact duplicates, and adjacent row changes — I have rows with row_id, dataset_group, date, observed_points, and expected_points fields, up to 50 rows, and I want to analyze observed_points.","exampleUseCases":[{"title":"Pre-pipeline data quality gate","prompt":"Before I load this batch of time series completeness records into our warehouse, can you run a full quality audit, deduplication check, and adjacent row change analysis on these 80 rows? Each row has a date, dataset_group, row_id, observed_points, and expected_points — analyze the observed_points field."},{"title":"Detecting duplicate completeness logs","prompt":"I have 150 rows of daily completeness tracking data across several dataset groups and I suspect some rows got logged twice. Can you run exact deduplication plus the record quality audit on these rows? Fields are row_id, dataset_group, date, observed_points, and expected_points."},{"title":"Monitoring day-over-day completeness shifts","prompt":"I need to see how my expected_points values are shifting day over day across these completeness records — run the adjacent row changes report along with the quality audit for these 40 rows grouped by dataset_group and date."}],"resultDescription":"Returns three independent analytical reports for the submitted rows: (1) a record quality audit flagging malformed or problematic records, (2) an exact row deduplication report identifying duplicate entries, and (3) an adjacent row changes report showing value differences between consecutive rows — all computed locally without external lookups.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, observed_points, expected_points) causes row-level rejection","Invalid date format (non YYYY-MM-DD) fails pattern validation","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array is rejected (minItems: 1)","Payment failure via x402 protocol prevents execution"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical operations — quality audit, deduplication, and adjacent-row-change detection — on time series completeness data (observed vs expected points) in a single $0.01 call, without requiring any external data lookups or live predictions. Ideal for data engineering pipelines validating completeness logs before ingestion, or for monitoring dataset groups day-over-day.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:25.761Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-analyzer-record-quality-audit-deduplication-92cc5e59"}