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Feature Availability Analytics — Grouped Numeric Summary + Base-100 Series
x402
Feature Availability Analytics — Grouped Numeric Summary + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes a grouped numeric summary and a Base-100 indexed time series from supplied feature availability records (populated_features vs expected_features) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Grouped numeric summary + Base-100 series: Grouped numeric summary + Base-100 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 grouped numeric summary aggregating populated_features and/or expected_features statistics by dataset_group, and (2) a Base-100 time series indexing the selected field relative to the specified base row. No external lookups or predictions are made; all computation uses the supplied rows only.
Example use cases
Data completeness audit by group
“I have up to 50 rows of feature availability data across three dataset groups with dates and both populated and expected feature counts. Can you give me a grouped numeric summary broken down by group so I can see where feature coverage is weakest?”
Base-100 trend indexing for feature population
“I want to track how my populated_features metric has changed over time relative to the first observation — can you run a base-100 series on my feature availability records using row index 0 as the baseline?”
Pipeline monitoring report for feature completeness
“My data pipeline emits daily records with populated_features and expected_features for each dataset group. Can you produce both a grouped summary and a base-100 indexed series for expected_features across all 120 rows so I can spot drops in feature completeness?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-092?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw feature availability records (populated vs expected feature counts) segmented by group and date, and need both a grouped aggregate summary and a Base-100 normalized time series in a single low-cost call. Ideal for data quality monitoring, pipeline health reporting, or feature completeness audits where you supply all data locally and need no external lookups or predictions.
Side effects
- Fewer than 1 or more than 200 rows submitted — validation error
- Missing required fields (row_id, dataset_group, date, populated_features, expected_features) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- base_index out of range (>=number of submitted rows) — index error
- Null values in numeric fields may affect aggregate computations
- field enum value not one of 'populated_features' or 'expected_features' — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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