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Time Series Completeness — Record Quality Audit + Numeric Interval Filter
x402
Time Series Completeness — 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 2026-10-15).
Audits time series completeness records for quality issues and filters rows by a numeric interval across observed_points or expected_points, returning two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied time series completeness records (observed_points, expected_points). 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 flagging data issues in the supplied completeness records (observed_points, expected_points), and (2) a numeric interval filter report listing rows where the chosen field (observed_points or expected_points) falls within the specified minimum and maximum bounds. No external lookups or predictions are performed; all analysis is local.
Example use cases
IoT sensor coverage gap audit
“I have daily sensor completeness records for two device groups with observed_points and expected_points for each day in October — can you audit them for quality issues and also filter to only the rows where observed_points falls between 10 and 100?”
Data pipeline completeness validation
“We track expected vs observed data points per pipeline run per day. Can you run a quality audit on these completeness records and also filter the expected_points field to rows within the range 50 to 200? I have about 80 rows.”
Analytics coverage reporting
“I need two reports on my time series completeness dataset: a record quality audit and a filter showing which rows have observed_points between 0 and 1000. The dataset has about 150 rows across several dataset groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-008?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined quality audit and numeric range filter on time series completeness data (observed vs expected point counts) in a single paid call. It is purpose-built for completeness tracking data with date, group, and point-count fields, and delivers two reports at once for $0.01 USDC per call. Prefer this over general analytics tools when your data fits the observed_points/expected_points schema and you want both quality flagging and interval filtering without building custom logic.
Side effects
- More than 200 rows submitted — request rejected, reduce batch size
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, date, observed_points, expected_points) — schema error
- minimum greater than maximum — may return empty filter result or error
- Null numeric values may be excluded from interval filter results
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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