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Feature Availability Analytics — Numeric Interval Filter + Daily Sum Series
x402
Feature Availability Analytics — Numeric Interval Filter + Daily Sum 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).
Runs two local analytical reports on feature availability data: filters rows by a numeric interval and produces a daily sum time series for populated_features or expected_features.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Numeric interval filter + Daily sum series: Numeric interval filter + Daily sum 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 analytical reports: (1) a numeric interval filter report listing rows where the selected field falls within the specified minimum–maximum range, and (2) a daily sum time series aggregating the selected field (populated_features or expected_features) by date. Up to 200 input rows supported per call.
Example use cases
Daily feature completeness trend check
“I have feature availability logs for October — each row has a date, dataset group, and counts of populated vs expected features. Can you filter rows where populated_features is between 5 and 30 and show me the daily sum series for populated_features? Rows: row-1 2026-10-01 group-a expected=10 populated=8, row-2 2026-10-02 group-b expected=20 populated=25, row-3 2026-10-03 group-a expected=15 populated=12.”
Expected features interval audit
“Run an interval filter on expected_features between 2 and 50 and give me the daily totals as a time series. My data: row-1 on 2026-10-01 group-a expected=5 populated=10, row-2 on 2026-10-02 group-b expected=45 populated=60, row-3 on 2026-10-03 group-c expected=100 populated=90.”
Cross-group feature gap monitoring
“I want to see which days and groups fall within my acceptable feature range — filter rows where populated_features is between 15 and 50, and give me a daily sum series too. Here's my data: row-1 2026-10-01 group-alpha expected=20 populated=18, row-2 2026-10-02 group-beta expected=30 populated=45, row-3 2026-10-03 group-alpha expected=25 populated=22, row-4 2026-10-04 group-beta expected=10 populated=50.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-125?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to perform both an interval-based filter AND a daily sum aggregation on feature availability data (populated vs expected features) in a single paid call. It is best suited for data quality monitoring workflows where you want to identify out-of-range feature counts and understand day-by-day totals without connecting to an external database or running your own analytics engine. Not suitable for real-time lookups, predictions, or datasets larger than 200 rows per call.
Side effects
- Input array is empty or exceeds 200 rows — validation error returned
- Date field does not match YYYY-MM-DD pattern — row rejected
- populated_features or expected_features values outside ±1,000,000,000,000 — schema violation
- minimum greater than maximum — may return empty filter results with no error
- Missing required fields (row_id, date) — request rejected
- Payment of 0.01 USDC not completed — 402 response with payment details
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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