{"uid":"cap_rpu5vZ80o4Dq9re9BysBc","slug":"time-series-completeness-analytics-daily-sum-adjacent-row-changes-4f503a76","name":"Time Series Completeness Analytics — Daily Sum + Adjacent Row Changes","description":"Time series completeness — Daily sum series + Adjacent row changes: Daily sum series + Adjacent row changes 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-16-137?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_cssgjQ5_GsrI0ad11hUbm","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":"Computes a daily sum series and adjacent row-to-row change analysis for up to 200 time series completeness records (observed vs expected points) in two independent reports.","exampleAgentPrompt":"I have a completeness log with up to 50 rows — each row has a date, a dataset group, and observed vs expected data points. Can you run the daily sum series and adjacent row change reports on observed_points for me?","exampleUseCases":[{"title":"Pipeline completeness gap detection","prompt":"I have 90 rows of daily completeness data for my ETL pipeline — each with a date, dataset_group, observed_points, and expected_points. Can you compute the daily sum series and day-over-day changes for observed_points so I can spot where data gaps spiked?"},{"title":"Sensor network data quality review","prompt":"Here are 150 rows from our sensor network completeness log with dates ranging over the last quarter, grouped by sensor cluster. Run both the daily sum and adjacent row change analytics on expected_points so I can see how our collection targets shifted over time."},{"title":"Multi-group completeness comparison","prompt":"I've got completeness records for two dataset groups — group-alpha and group-beta — across 60 days. Can you generate the daily sum series and adjacent row changes for observed_points so I can compare collection trends between the two groups?"}],"resultDescription":"Returns two independent analytical reports: (1) a daily sum series aggregating the selected field (observed_points or expected_points) by date, and (2) an adjacent row change report showing value differences between consecutive rows — both computed locally from the supplied data, with no external lookups or predictions.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, date, observed_points, expected_points) cause validation errors","Date strings not matching YYYY-MM-DD format will fail schema validation","Null values in the selected field may produce null deltas in adjacent-row output","Payment not received or insufficient USDC balance blocks the call"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous analytical views — daily aggregation and row-to-row change detection — on time series completeness data (observed vs expected points) without any external data lookups, for up to 200 rows at a flat cost of $0.01 USDC. It is ideal for data engineers and monitoring pipelines that already have completeness records and need fast local computation rather than prediction or enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:52.630Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-analytics-daily-sum-adjacent-row-changes-4f503a76"}