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Feature Availability Analytics: Category Frequencies & Adjacent Row Changes
x402
Feature Availability Analytics: Category Frequencies & 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).
Analyzes feature availability records to produce two reports: category frequency distributions and adjacent row changes, for up to 200 rows of populated/expected feature data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Category frequencies + Adjacent row changes: Category frequencies + 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 independent analytical reports computed locally: (1) category frequencies showing how often each dataset_group category appears in the supplied records, and (2) adjacent row changes showing the delta between consecutive rows for the selected field (populated_features or expected_features). No external lookups or predictions are made.
Example use cases
ML dataset feature completeness audit
“I have 150 rows of ML dataset records with populated_features and expected_features columns across two groups, 'train' and 'test' — can you give me the category frequency distribution by group and show me how populated_features changes between consecutive rows?”
Daily feature pipeline health check
“Here are my daily feature pipeline records from the past 30 days with dates, dataset_group labels, and counts for populated_features and expected_features — run the category frequencies and adjacent row changes report on the populated_features field so I can see where drops occur.”
Multi-group feature availability comparison
“I've got feature availability data for 4 dataset groups over the last quarter, up to 200 rows total — analyze the expected_features field to get me the category frequencies per group and flag where values shift significantly between adjacent rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-104?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical summaries of feature availability records — specifically category frequency counts and row-to-row delta analysis — without requiring any external data lookups, predictions, or ML inference. Ideal for data quality pipelines, feature store audits, and batch monitoring of up to 200 rows at $0.01 per call covering both reports.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, populated_features, expected_features) on any row causes validation failure
- Date field not matching YYYY-MM-DD pattern causes schema rejection
- Null values in the selected field may affect adjacent change calculations
- Invalid field enum value (not 'populated_features' or 'expected_features') causes error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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