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Feature Availability Analytics: Numeric Distribution + Trailing Mean Series
x402
Feature Availability Analytics: Numeric Distribution + 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 2026-10-20).
Computes a numeric distribution report and a trailing mean time series for feature availability data (populated_features and expected_features) supplied by the caller, using local analytical engines with no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied feature availability records (populated_features, expected_features). 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.
Output
Returns two independent analytical reports: (1) a numeric distribution summarizing the statistical spread of the selected feature availability field across submitted rows, and (2) a trailing mean time series computed over the specified rolling window — both derived entirely from the supplied data using local analytical engines.
Example use cases
Feature completeness audit for ML dataset
“I have daily feature availability records for two dataset groups over the past quarter — each row has a date, populated_features count, and expected_features count. Can you give me the numeric distribution and a trailing mean series with a window of 14 days for populated_features so I can audit completeness trends?”
Monitoring feature fill rate over time
“Run a distribution report and trailing mean series on my feature availability logs — I've got 80 rows with row_id, dataset_group, date, populated_features, and expected_features. Use a window of 5 and focus on the expected_features field so I can see how our fill rate is trending.”
Comparing feature population across groups
“I want to compare how populated_features are distributed across my dataset groups over time. I have 150 rows of feature availability data with dates and group labels — can you compute the numeric distribution and a trailing mean series with window 10 for the populated_features field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-076?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of feature availability records and need both a distribution summary and a rolling mean time series in a single call for a flat $0.01 USDC fee. It is ideal for lightweight, self-contained statistical analysis of feature completeness or population rate metrics when no external data lookups, predictions, or professional assessments are needed.
Side effects
- Fewer than 1 row provided — request rejected
- More than 200 rows submitted — exceeds maximum batch size
- Invalid date format (must be YYYY-MM-DD) — validation error
- Numeric field values outside allowed range (-1T to +1T) — validation error
- Window size smaller than 2 or larger than 200 — rejected
- Missing required fields (row_id, date, populated_features, expected_features) — schema error
- Payment not included or insufficient — x402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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