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Feature Availability Analytics — Daily Sum Series + Adjacent Row Changes
x402
Feature Availability Analytics — Daily Sum Series + 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 2026-10-20).
Runs two analytical reports on feature availability data: a daily sum time series and adjacent row change detection, for up to 200 rows of populated/expected feature counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Daily sum series + Adjacent row changes: Daily sum series + 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
Two analytical report outputs computed locally from the supplied rows: (1) a daily sum series aggregating the selected field (populated_features or expected_features) by date, and (2) an adjacent row change report showing differences between consecutive rows — all derived from the provided data with no external lookups.
Example use cases
Daily feature completeness trend audit
“I have 120 rows of feature availability records with dates, dataset groups, and populated vs expected feature counts — can you compute the daily sum series and show me how the populated_features totals change day over day?”
Spotting sudden drops in populated features
“Run the adjacent row change report on my feature availability data so I can see where populated_features jumped or dropped significantly between consecutive records — here are the rows with their dates and dataset groups.”
Comparing expected vs populated feature volumes
“I want to analyze expected_features instead of populated_features — can you run both the daily sum series and the adjacent row change reports on my 80 feature availability records to see how expected volumes trend over the date range?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-137?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 feature availability records with date, group, and numeric feature counts and need both a daily aggregated time series and adjacent row change detection in a single low-cost call. It is best for offline/supplied-data analysis where no live lookup or external data enrichment is needed. Prefer alternatives if you need more than 200 rows, real-time data fetching, prediction, or more than two report types.
Side effects
- Fewer than 1 row supplied — minimum array size is 1
- More than 200 rows supplied — maximum exceeded
- Missing required fields (row_id, dataset_group, date, populated_features, expected_features) on any row
- Invalid date format — must match YYYY-MM-DD pattern
- Numeric values outside allowed range (±1,000,000,000,000)
- Invalid field enum value — must be 'populated_features' or 'expected_features'
- Payment not provided or insufficient — $0.01 USDC required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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