{"uid":"cap_5DL01-nduxYN9A-dEreOW","slug":"time-series-completeness-duplicate-key-report-numeric-interval-filter-484c11f5","name":"Time Series Completeness — Duplicate Key Report + Numeric Interval Filter","description":"Time series completeness — Duplicate key report + Numeric interval filter: Duplicate key report + Numeric interval filter 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-16-059?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_YBAklVB-6Rog1McGbZADT","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 time series completeness records to produce a duplicate key report and a numeric interval filter report for observed/expected data points across up to 200 rows.","exampleAgentPrompt":"Check my time series completeness records for duplicate row keys and also filter for rows where observed_points falls between 5 and 50 — here are the rows: row-1 for group-a on 2026-10-01 with 10 observed and 1 expected, row-2 for group-b on 2026-10-02 with 20 observed and 2 expected, row-3 for group-a on 2026-10-03 with 15 observed and 3 expected.","exampleUseCases":[{"title":"Auditing completeness logs for duplicate entries","prompt":"I have a batch of 50 time series completeness records with row IDs, dataset groups, and daily observed vs expected point counts — can you run a duplicate key report on them to find any rows that share the same identifier?"},{"title":"Filtering completeness data by observed point range","prompt":"From my time series completeness dataset, filter down to only the rows where expected_points is between 10 and 100 — I have about 80 records across group-a and group-b spanning October 2026."},{"title":"Data quality check before pipeline ingestion","prompt":"Before I ingest these 150 completeness records into our pipeline, can you check for any duplicate row IDs and also flag which rows have observed_points outside the range of 0 to 500 so I can clean them up first?"}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying rows with repeated row_id or key combinations within the supplied dataset, and (2) a numeric interval filter report listing rows where the selected numeric field (observed_points or expected_points) falls within the specified minimum–maximum range. Up to 200 input rows are processed locally with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, dataset_group, observed_points, or expected_points) cause row-level errors","Invalid date format (not YYYY-MM-DD) triggers validation failure","Minimum value greater than maximum value may produce empty interval filter results","Non-numeric values in observed_points or expected_points fields cause parsing errors"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous local analytical reports — a duplicate key check and a numeric range filter — on time series completeness data (observed vs expected points) without any external data lookups or predictions. It is ideal for data quality auditing of completeness logs before pipeline ingestion, at $0.01 USDC for both reports on up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:28.198Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-duplicate-key-report-numeric-interval-filter-484c11f5"}