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Product Feature Telemetry – Trailing Mean Series
x402
Product Feature Telemetry – Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
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.
Price / call$0.01
Success—
StatusUnknown
How this service works
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.
Output
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.
Example use cases
Smoothing noisy feature event spikes
“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?”
Tracking unique user engagement over time
“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.”
Pre-report analytics smoothing for stakeholder deck
“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.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-feature-telemetry-rolling?utm_source=zero.xyzWhen to prefer
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).
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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