{"uid":"cap_OdrY-r0tYFWcSuAojJu_R","slug":"aggregation-checks-numeric-row-ordering-trailing-mean-series-d6a3e013","name":"Aggregation Checks — Numeric Row Ordering + Trailing Mean Series","description":"Aggregation checks — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series 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-17-115?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_YcbiYvMh0w9cey86mL0cd","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 aggregation check records by computing numeric row ordering and a trailing mean series for source_sum or aggregate_sum values across up to 200 rows.","exampleAgentPrompt":"Can you run numeric row ordering and a trailing mean series (window size 3) on my aggregation check data for the source_sum field? Here are my rows: row-1 2026-10-01 group-a source_sum=10 aggregate_sum=1, row-2 2026-10-02 group-b source_sum=20 aggregate_sum=2, row-3 2026-10-03 group-a source_sum=15 aggregate_sum=3.","exampleUseCases":[{"title":"Detect ordering issues in pipeline sums","prompt":"I have 50 rows of aggregation output from my ETL pipeline with dates, source_sum, and aggregate_sum values. Can you rank them by numeric ordering and compute a trailing mean with a window of 5 on the source_sum field so I can spot where values go out of sequence?"},{"title":"Rolling average for grouped budget data","prompt":"I've got budget aggregation records grouped by department across 30 dates. Run a trailing mean series with window size 4 on the aggregate_sum column for me so I can see the smoothed trend for each group."},{"title":"QA check on aggregation reconciliation data","prompt":"Can you take my 80-row aggregation reconciliation dataset and generate both a numeric row ordering report and a 7-day trailing mean on the source_sum field? I want to see if the sums are progressing sensibly."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric row ordering report ranking rows by the selected field, and (2) a trailing mean series computed over the specified window size for the chosen field (source_sum or aggregate_sum), covering all supplied rows (up to 200). No external lookups or predictions are performed.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Window size exceeds number of rows — trailing mean may be undefined for early rows","Invalid date format (not YYYY-MM-DD) — schema validation error","source_sum or aggregate_sum values outside ±1,000,000,000,000 — schema rejection","Missing required fields (row_id, dataset_group, date) — validation failure","Payment not completed (x402 protocol) — 402 response, no report generated"],"whenToPreferThis":"Choose this endpoint when you need both a numeric ordering check and a rolling/trailing mean analysis on aggregation sum data in a single call, with up to 200 rows and no need for external data lookup or prediction. It is cost-effective at $0.01 USDC for two bundled reports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:05.991Z","isFirstParty":false,"canonicalSlug":"aggregation-checks-numeric-row-ordering-trailing-mean-series-d6a3e013"}