{"uid":"cap_16RXQqhNt4VpB14hC--Wg","slug":"data-freshness-analytics-trailing-mean-series-adjacent-row-changes-11a6819c","name":"Data Freshness Analytics — Trailing Mean Series + Adjacent Row Changes","description":"Data freshness — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes for supplied data freshness records (age_minutes, record_count). 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-06-146?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","age_minutes","record_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"age_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"record_count":{"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","age_minutes":10,"record_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","age_minutes":20,"record_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","age_minutes":15,"record_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","age_minutes":30,"record_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["age_minutes","record_count"],"type":"string","default":"age_minutes"},"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_plxrrYBJmxUYRtya-Y_M1","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 two analytical reports on data freshness records: a trailing moving-average series and adjacent row-to-row delta changes, for up to 200 rows of age_minutes or record_count data.","exampleAgentPrompt":"I have 50 rows of data freshness records with date, age_minutes, and record_count — can you run both a trailing mean series and adjacent row change report on the age_minutes field using a window size of 5?","exampleUseCases":[{"title":"Freshness drift trend detection","prompt":"I've got a week's worth of daily freshness snapshots for two dataset groups — can you compute a trailing mean series and adjacent row changes for the age_minutes field with a window of 3, so I can see if data is getting staler over time?"},{"title":"Record count volatility analysis","prompt":"Here are 80 rows of ingestion batch records with record_count values — run both a rolling mean with window 7 and adjacent row deltas on the record_count field so I can spot unusual jumps between batches."},{"title":"Multi-group freshness comparison","prompt":"I have freshness data across several dataset_groups over 30 dates — give me the trailing mean series and adjacent row changes for age_minutes using a window of 4 so I can compare stability across groups."}],"resultDescription":"Returns two independent analytical reports: (1) a trailing mean series showing the rolling average of the selected field (age_minutes or record_count) over the specified window, and (2) adjacent row changes showing the difference between each consecutive row's values. Both reports are computed locally with no external lookups.","failureModes":["Fewer rows than window size causes incomplete or no trailing mean values at the start of the series","Missing or null age_minutes/record_count values may produce null deltas or means for affected rows","Rows exceeding the 200-row limit will be rejected","Invalid date format (not YYYY-MM-DD) causes validation error","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of data freshness records (age_minutes, record_count) and need both a trailing moving-average time series and adjacent row-to-row delta analysis in a single call. It is ideal for lightweight, offline analytical summaries of freshness metrics without requiring a full data warehouse or streaming pipeline. Prefer it over general-purpose analytics tools when cost efficiency ($0.01 for two reports) and deterministic local computation are priorities.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:03.707Z","isFirstParty":false,"canonicalSlug":"data-freshness-analytics-trailing-mean-series-adjacent-row-changes-11a6819c"}