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Feature Availability Analytics — Grouped Numeric Summary & Adjacent Row Changes
x402
Feature Availability Analytics — Grouped Numeric Summary & Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Runs two local analytical reports on feature availability data: a grouped numeric summary by dataset group and an adjacent row change analysis, for up to 200 rows at once.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Grouped numeric summary + Adjacent row changes: Grouped numeric summary + Adjacent row changes 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 grouped numeric summary aggregating populated_features or expected_features statistics by dataset_group, and (2) an adjacent row changes report showing deltas between consecutive rows for the selected field. No external lookups or predictions are made; all computation is performed locally on the supplied data.
Example use cases
Daily feature coverage audit by group
“I've got daily feature availability records for our ML pipeline across three dataset groups over the past month — each row has populated_features and expected_features. Can you give me a grouped numeric summary and show me how populated_features change between adjacent rows?”
Detect drops in expected feature counts
“Here are 150 rows of feature availability data with dates, dataset groups, and expected_features counts. Run the grouped summary and adjacent row changes report on expected_features so I can spot where counts dropped day over day.”
QA check on multi-group feature population
“I need to QA our feature store — I have records for group-a and group-b with populated_features and expected_features per day. Can you run both the grouped numeric summary and the adjacent row changes analysis on populated_features across all my rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-091?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 feature availability records with populated and expected feature counts and need both a grouped aggregate summary and a row-to-row delta analysis in a single API call. It is ideal for lightweight, local analytical computation on feature store data without needing an external database or analytics platform. Prefer it over general-purpose analytics APIs when you want two coordinated reports for $0.01 USDC on structured feature availability rows.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum row limit
- Missing required fields (row_id, dataset_group, date, populated_features, expected_features) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — rejected
- Invalid field enum value (must be 'populated_features' or 'expected_features') — error returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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