{"uid":"cap_otouUX2FS6fr4CeCPL23Q","slug":"time-series-completeness-record-quality-audit-exact-row-deduplication-6a88827e","name":"Time Series Completeness — Record Quality Audit + Exact Row Deduplication","description":"Time series completeness — Record quality audit + Exact row deduplication: Record quality audit + Exact row deduplication 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-16-002?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}}},"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_184ML_G0ahrTg1ZskQnfg","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":"Audits up to 200 time series completeness records (observed_points vs expected_points) for data quality issues and exact duplicate rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and exact row deduplication check on this batch of time series completeness data? I have rows for group-a and group-b from 2026-10-01 through 2026-10-04, each with observed_points and expected_points values — give me both reports.","exampleUseCases":[{"title":"Pre-load data integrity check","prompt":"Before I load this month's sensor completeness data into our warehouse, can you audit these 150 rows for quality issues and flag any exact duplicate records? Each row has a date, dataset_group, observed_points, and expected_points."},{"title":"Duplicate detection across dataset groups","prompt":"I have completeness records for three dataset groups spanning the last 90 days — can you run an exact row deduplication report on all 180 rows to identify any entries that appear more than once?"},{"title":"Pipeline QA for time series ingestion","prompt":"Our ETL pipeline sometimes produces bad completeness records — can you do a quality audit on these 200 rows of observed vs expected data points and also check for exact duplicates so I can clean up before reprocessing?"}],"resultDescription":"Returns two independent reports: (1) a record quality audit identifying issues in the supplied time series completeness records (e.g. nulls, format violations, anomalies), and (2) an exact row deduplication report flagging rows that are identical across all fields. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — exceeds maximum batch size","Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row — validation error","Date field not matching YYYY-MM-DD pattern — schema rejection","row_id or dataset_group exceeds 80 character limit — schema rejection","observed_points or expected_points outside allowed numeric range — schema rejection","Payment failure or insufficient USDC balance — request rejected"],"whenToPreferThis":"Choose this endpoint when you need both a record quality audit and exact deduplication report for time series completeness data (observed vs expected data points) in a single $0.01 call, without requiring any live lookups or external data. It is ideal for pre-ingestion data validation pipelines, ETL quality gates, or ad-hoc audits of up to 200 rows. Prefer alternatives if you need predictive analytics, outlier detection (IQR-based), or metrics beyond observed/expected point counts.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:35:58.096Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-record-quality-audit-exact-row-deduplication-6a88827e"}