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Feature Availability — Record Quality Audit + Numeric Interval Filter
x402
Feature Availability — Record Quality Audit + Numeric Interval Filter 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 records: a record quality audit and a numeric interval filter for populated_features or expected_features fields, covering up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter 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 record quality audit highlighting data issues in the supplied feature availability rows, and (2) a numeric interval filter report showing which rows fall within the specified minimum/maximum range for the chosen field (populated_features or expected_features). Results are based entirely on the supplied data with no external lookups.
Example use cases
ML feature store data quality check
“I need to audit the quality of my feature availability records and flag any rows where populated_features falls outside 0 to 500 — here are my rows with row_id, dataset_group, date, populated_features, and expected_features. Run both the quality audit and the interval filter for me.”
Expected vs populated feature gap analysis
“Can you check my feature availability dataset for quality issues and filter the expected_features field to only show rows between 1 and 50? I have about 150 rows with date, row_id, dataset_group, populated_features, and expected_features.”
Dataset pipeline completeness validation
“I'm validating a pipeline output — please run a record quality audit and a numeric interval filter on these feature availability rows, filtering populated_features between 10 and 1000, and flag any records that look problematic.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-008?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous analytical passes on feature availability data — a quality audit and a numeric interval filter — within a single low-cost ($0.01 USDC) call, without requiring any external lookups or live data sources. Ideal for batch data pipeline validation, ML feature store QA, or dataset completeness checks where the data is already available locally.
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — exceeds row limit
- Missing required fields (row_id, date, populated_features, expected_features) — validation error
- Date field not in YYYY-MM-DD format — schema rejection
- Minimum value greater than maximum value — ambiguous interval
- Null values in numeric fields may affect interval filter results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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