{"uid":"cap_xZNKkdKjg5-8V_D8r835j","slug":"data-reconciliation-analytics-numeric-distribution-trailing-mean-series-017396cd","name":"Data Reconciliation Analytics — Numeric Distribution + Trailing Mean Series","description":"Data reconciliation — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied data reconciliation records (source_total, target_total). 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-11-076?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_total","target_total"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_total":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"target_total":{"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_total":10,"target_total":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_total":20,"target_total":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_total":15,"target_total":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_total":30,"target_total":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["source_total","target_total"],"type":"string","default":"source_total"},"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_J2tuFd0MtzIPP9QSCVmza","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 numeric distribution statistics and a trailing mean time series for source_total and target_total reconciliation data, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run the numeric distribution and trailing mean series reports on my reconciliation data? I have 4 rows: row-1 for group-a on 2026-10-01 with source_total 10 and target_total 1, row-2 for group-b on 2026-10-02 with source_total 20 and target_total 2, row-3 for group-a on 2026-10-03 with source_total 15 and target_total 3, and row-4 for group-b on 2026-10-04 with source_total 30 and target_total 4 — use source_total as the field and a window of 2.","exampleUseCases":[{"title":"ETL pipeline reconciliation health check","prompt":"I have 50 daily reconciliation records comparing our data warehouse source_total to the target_total after ETL. Can you run the numeric distribution and trailing mean series with a window of 7 on the source_total field so I can see if there's drift or skew?"},{"title":"Finance team source-vs-target variance profiling","prompt":"Our finance team needs to profile this quarter's reconciliation data — 120 rows across two dataset groups, each with a source_total and target_total. Please compute both the numeric distribution and the trailing mean series using target_total and a window of 5 so we can spot outliers."},{"title":"Data quality audit across grouped datasets","prompt":"I'm auditing data quality for two dataset groups over the past 90 days. Here are 90 reconciliation rows with source_total and target_total values — run the numeric distribution report and a trailing mean series with window size 10 on source_total so I can compare trends across groups."}],"resultDescription":"Two analytical reports computed locally from the supplied rows: (1) a numeric distribution report showing descriptive statistics (e.g. min, max, mean, median, spread) for the chosen field across all rows; and (2) a trailing mean series showing rolling averages over the specified window size, indexed by date. Both reports are derived purely from the input data with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum 1 row required","More than 200 rows supplied — exceeds maximum batch size","Missing required fields (row_id, dataset_group, date, source_total, target_total) on any row","Invalid date format — must match YYYY-MM-DD pattern","Window size less than 2 or greater than 200","source_total or target_total outside the range -1,000,000,000,000 to 1,000,000,000,000","Payment failure — 0.01 USDC not received or insufficient balance"],"whenToPreferThis":"Choose this endpoint when you need both a distributional profile and a rolling mean time series from reconciliation records in a single low-cost call. It is ideal for ETL validation, financial data quality audits, or any workflow comparing source vs target totals across time-stamped, grouped rows — without needing external data, predictions, or live lookups. Prefer it over general-purpose analytics tools when you want a lightweight, deterministic, offline computation on up to 200 rows at minimal cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:45:34.318Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-analytics-numeric-distribution-trailing-mean-series-017396cd"}