{"uid":"cap_8olCS5fKZfLp00qwIGTxj","slug":"aggregation-checks-daily-sum-series-secondary-measure-weighted-mean-debf7255","name":"Aggregation Checks — Daily Sum Series + Secondary-Measure Weighted Mean","description":"Aggregation checks — Daily sum series + Secondary-measure weighted mean: Daily sum series + Secondary-measure weighted mean for supplied aggregation checks records (source_sum, aggregate_sum). 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-17-142?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_sum","aggregate_sum"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_sum":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"aggregate_sum":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_sum":10,"aggregate_sum":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_sum":20,"aggregate_sum":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_sum":15,"aggregate_sum":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_sum":30,"aggregate_sum":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["source_sum","aggregate_sum"],"type":"string","default":"source_sum"}}},"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_0z9bRz3ywDynuRHvhj7ue","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 time series and a secondary-measure weighted mean over up to 200 supplied aggregation check rows (source_sum, aggregate_sum), returning two analytical reports.","exampleAgentPrompt":"Can you run the daily sum series and weighted mean reports on these 4 aggregation check rows — row-1 through row-4 dated 2026-10-01 to 2026-10-04, with source_sum values 10, 20, 15, 30 and aggregate_sum values 1, 2, 3, 4 across group-a and group-b — using source_sum as the primary field?","exampleUseCases":[{"title":"Daily revenue aggregation validation","prompt":"I have 150 rows of daily sales aggregation checks with source_sum and aggregate_sum for each date from 2025-01-01 to 2025-05-31 across two dataset groups — can you compute the daily sum time series and weighted mean on the source_sum field so I can spot where totals diverge?"},{"title":"Weekly ETL pipeline audit","prompt":"Run the daily sum series and secondary-measure weighted mean on these 80 aggregation records from my ETL pipeline — dates range from 2025-06-01 to 2025-08-19, I have source_sum and aggregate_sum per row across groups 'raw' and 'processed', and I want to use aggregate_sum as the field for the weighted mean."},{"title":"Group-level data quality check","prompt":"I need to audit two dataset groups — 'north' and 'south' — using 60 daily aggregation rows from Q1 2025. Each row has a source_sum and aggregate_sum. Please give me the daily sum series and the secondary-measure weighted mean using source_sum so I can see which group has the bigger discrepancy."}],"resultDescription":"Returns two analytical reports: (1) a daily sum time series aggregating the selected field (source_sum or aggregate_sum) by date across all supplied rows, and (2) a secondary-measure weighted mean report. Both reports are computed locally from the supplied data (up to 200 rows) with no external lookups or live data sources.","failureModes":["Empty rows array — rejected if fewer than 1 row supplied","Rows exceeding 200 — returns error if maxItems exceeded","Invalid date format — must match YYYY-MM-DD pattern exactly","source_sum or aggregate_sum out of range (beyond ±1,000,000,000,000) — rejected","Missing required fields (row_id, dataset_group, date, source_sum, aggregate_sum) — validation error","Invalid field enum value — only 'source_sum' or 'aggregate_sum' accepted"],"whenToPreferThis":"Choose this endpoint when you have tabular aggregation check data with source_sum and aggregate_sum columns and need both a daily sum time series and a weighted mean in a single $0.01 call. It is ideal for data quality audits, ETL validation, or lightweight analytics on pre-supplied data without needing external data access or live lookups. Prefer it when your dataset is 200 rows or fewer and you want two reports bundled together cheaply.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:52.699Z","isFirstParty":false,"canonicalSlug":"aggregation-checks-daily-sum-series-secondary-measure-weighted-mean-debf7255"}