{"uid":"cap_l6W816aTZ6FC_Tm7at7tx","slug":"product-feature-telemetry-trailing-mean-series-7fb934f3","name":"Product Feature Telemetry – Trailing Mean Series","description":"Product feature telemetry - Trailing mean series: Trailing mean series for Product feature telemetry. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded trailing mean series report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-feature-telemetry-rolling?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","feature","date","events","unique_users"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"events":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"feature":{"type":"string","default":"","maxLength":80},"unique_users":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","events":10,"row_id":"row-1","feature":"group-a","unique_users":1},{"date":"2026-10-02","events":20,"row_id":"row-2","feature":"group-b","unique_users":2},{"date":"2026-10-03","events":15,"row_id":"row-3","feature":"group-a","unique_users":3},{"date":"2026-10-04","events":30,"row_id":"row-4","feature":"group-b","unique_users":4}],"maxItems":200,"minItems":1},"field":{"enum":["events","unique_users"],"type":"string","default":"events"},"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_bVNIXm09jCT032bHFt_tc","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 trailing (rolling) mean series over time-series product feature telemetry records, returning a smoothed time-series for events or unique users per feature group.","exampleAgentPrompt":"Take these 50 daily telemetry rows for our 'dark-mode' and 'search-v2' features and compute a trailing mean series over a 7-day window for the events field — I want to see the rolling average to smooth out the noise.","exampleUseCases":[{"title":"Smoothing noisy feature event spikes","prompt":"I have 120 rows of daily event counts for our 'checkout-redesign' feature and there are big spikes on weekends that make the trend hard to read — can you run a 7-day trailing mean on the events field so I can see the underlying trend?"},{"title":"Tracking unique user engagement over time","prompt":"Here are 90 days of daily unique-user counts for our 'onboarding-flow' and 'dashboard-v2' features. Compute a 14-day rolling mean on the unique_users field so I can compare smoothed engagement trends between the two groups."},{"title":"Pre-report analytics smoothing for stakeholder deck","prompt":"Before I put this feature telemetry data into my quarterly slide deck, can you run a 30-day trailing mean on the events column across all our feature groups? I have about 180 rows covering the last 6 months."}],"resultDescription":"A trailing mean series report containing smoothed metric values (events or unique_users) per feature over time, calculated using the specified rolling window. The report covers up to 200 input records and provides local descriptive analytics with no forecasting or external enrichment.","failureModes":["Fewer than 1 row supplied — minimum item count validation failure","Window size larger than the number of rows in a feature group — insufficient data for rolling calculation","Invalid date format not matching YYYY-MM-DD pattern — schema validation error","More than 200 rows supplied — exceeds maxItems limit","Numeric values out of allowed range (±1 trillion) — schema rejection","Missing required fields (row_id, feature, date, events, unique_users) — validation failure","Payment not processed — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need a fast, bounded rolling-mean smoothing computation over product feature telemetry (events or unique users) without requiring external enrichment, forecasting, or ML models. It is ideal for pre-processing noisy time-series data before visualization or reporting, especially when working with up to 200 records across multiple feature groups at low cost ($0.01 per call).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:46:34.877Z","isFirstParty":false,"canonicalSlug":"product-feature-telemetry-trailing-mean-series-7fb934f3"}