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Time Series Completeness — Record Quality Audit + Keyed Dataset Comparison
x402
Time Series Completeness — Record Quality Audit + 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 2026-10-15).
Runs two local analytical reports on supplied time series completeness data: a record quality audit and a keyed dataset comparison between two datasets, each with observed vs. expected data points.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Record quality audit + Keyed dataset comparison: Record quality audit + Keyed dataset comparison 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 covering data completeness, anomalies, and validity issues in the supplied rows; and (2) a keyed dataset comparison highlighting differences between the primary and secondary datasets on matching row_ids, dates, and dataset_groups. All analysis is performed locally on the submitted data with no external lookups.
Example use cases
Daily sensor data completeness audit
“I have two days of sensor readings across groups A and B — can you audit the record quality for these completeness rows and also compare them against yesterday's baseline dataset? Each row has a date, observed_points, and expected_points.”
ETL pipeline output validation
“After running our ETL pipeline today, I want to verify that the observed data points match the expected points for each date and dataset_group. Run a quality audit on the primary output and compare it key-by-key against last week's run — here are both sets of records.”
Cross-team dataset discrepancy check
“Our data engineering team and analytics team each produced a completeness report for the same time period, but the numbers look different. Can you run a keyed comparison between these two datasets — up to 200 rows each — and flag where observed_points diverge from expected_points?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-018?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a record quality audit AND a keyed dataset comparison on time series completeness data in a single low-cost call. Ideal for batch validation of up to 200 rows where you already have the data locally and need structured analytical output without live lookups or external integrations. Best suited for data engineering pipelines, ETL validation, or periodic completeness checks across dataset groups.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, observed_points, expected_points) cause row-level errors
- Invalid date format (not YYYY-MM-DD) causes validation failure
- Null values in observed_points or expected_points may affect completeness calculations
- Mismatched row_ids between primary and secondary datasets reduce comparison coverage
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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