{"uid":"cap_rFwkTcg6o42KxBQGQLtyu","slug":"data-freshness-record-quality-audit-trailing-mean-series-feff5d2b","name":"Data Freshness Record Quality Audit + Trailing Mean Series","description":"Data freshness — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series 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-06-010?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_ECT3BLUUBu3vSafuFXREq","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":"Runs two analytical reports—a record quality audit and a trailing mean series—on supplied data freshness records (age_minutes and record_count fields), returning local analytics with no external lookups.","exampleAgentPrompt":"Can you run a record quality audit and trailing mean series on my data freshness records? Here are up to 200 rows with row_id, dataset_group, date, age_minutes, and record_count — use age_minutes as the field with a window of 3.","exampleUseCases":[{"title":"Pipeline freshness monitoring audit","prompt":"I have a list of daily data pipeline records with age_minutes and record_count — can you run a record quality audit and a trailing mean series on age_minutes with a window of 5 to spot any quality issues or trends?"},{"title":"Dataset group freshness comparison","prompt":"Can you audit my data freshness records for two dataset groups — 'warehouse' and 'retail' — and give me a trailing mean of record_count over a window of 7 days so I can compare how fresh each group's data has been?"},{"title":"Data ingestion quality check","prompt":"I've got about 150 rows of ingestion log records, each with a date, age_minutes, and record_count. Please run both the record quality audit and trailing mean series on record_count using a window of 4 and tell me where quality drops off."}],"resultDescription":"Returns two analytical reports: (1) a record quality audit that flags issues, anomalies, or quality signals in the supplied freshness records; and (2) a trailing mean series showing rolling averages over the specified window for the chosen field (age_minutes or record_count), all computed locally without external lookups.","failureModes":["Fewer than 1 row supplied returns a validation error","More than 200 rows supplied exceeds the row limit and is rejected","Window size larger than number of rows may yield empty or partial trailing mean series","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Missing required fields (row_id, dataset_group, date) cause request rejection","Non-numeric values in age_minutes or record_count outside the allowed range cause errors"],"whenToPreferThis":"Choose this endpoint when you need two combined analytical reports—quality audit and trailing mean—on data freshness records in a single low-cost call, without requiring any external data lookup, live prediction, or professional assessment. It is especially suited for monitoring data pipeline freshness metrics (age_minutes, record_count) across dataset groups over time, and for lightweight batch analysis of up to 200 rows at $0.01 per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:33.242Z","isFirstParty":false,"canonicalSlug":"data-freshness-record-quality-audit-trailing-mean-series-feff5d2b"}