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Feature Availability Analytics — Grouped Numeric Summary & Keyed Dataset Comparison
x402
Feature Availability Analytics — Grouped Numeric Summary & Keyed Dataset Comparison 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 keyed dataset comparison for supplied feature availability records (populated_features vs expected_features) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Grouped numeric summary + Keyed dataset comparison: Grouped numeric summary + Keyed dataset comparison 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 or expected_features statistics by dataset_group, and (2) a keyed dataset comparison contrasting the primary and secondary supplied datasets row by row. Both reports are computed locally from supplied data with no external lookups.
Example use cases
Feature completeness audit by group
“I have 150 rows of feature availability data split across two groups — 'model-a' and 'model-b' — with populated_features and expected_features values by date. Can you give me a grouped numeric summary and compare the two datasets so I can see where features are missing?”
ML pipeline data quality check
“Before my model training run, can you analyze these feature availability records across my pipeline stages? I need a grouped summary of populated_features and a comparison between last week's and this week's datasets to catch any drops in feature coverage.”
Monitoring feature drift between dataset versions
“I want to compare two versions of my feature store snapshot — each up to 200 rows with dataset_group, date, populated_features, and expected_features — can you run both a grouped numeric summary and a keyed comparison on the expected_features field to flag where drift has occurred?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-098?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a grouped statistical summary and a side-by-side keyed comparison of two feature availability datasets in a single $0.01 call, with no external data dependencies. Ideal for data quality audits, ML feature store monitoring, and pipeline completeness checks where you already have the raw records and want offline analytics on up to 200 rows.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, dataset_group, date, populated_features, expected_features) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (-1T to +1T) — rejected
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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