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Time Series Completeness — Record Quality Audit + Category Frequencies
x402
Time Series Completeness — Record Quality Audit + Category Frequencies 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 analytical reports on supplied time series completeness records: a record quality audit and a category frequency breakdown, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Record quality audit + Category frequencies: Record quality audit + Category frequencies 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
Two independent analytical reports: (1) a record quality audit flagging issues such as missing values, out-of-range counts, or suspicious ratios of observed to expected points, and (2) a category frequency summary showing how often each dataset_group appears and the distribution of completeness metrics across categories. Results are computed locally with no external lookups.
Example use cases
Daily pipeline completeness check
“I need a quality audit and category frequency breakdown for my daily pipeline completeness logs — I have 30 rows, each with a date, dataset group, and observed vs expected data points. Can you analyze them and tell me which groups look incomplete or anomalous?”
Multi-group completeness comparison
“Can you run a record quality audit and frequency report across my three dataset groups — alpha, beta, and gamma — using these 60 rows of time series completeness data with observed and expected point counts for each date in January 2024?”
Weekly data quality review
“I want to review the quality of my time series completeness records for last week. Here are 100 rows with row IDs, dataset groups, dates, and observed vs expected data point counts — please give me a record quality audit and show me how category frequencies break down across the groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-006?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 time series completeness records (with observed and expected point counts) and need both a record-level quality audit and a category/group frequency summary in a single cheap call. It is ideal for lightweight, self-contained analytics on completeness logs without needing a full data warehouse or external data science service. Avoid if you need predictive modeling, live data ingestion, or more than 200 rows.
Side effects
- Fewer than 1 row or more than 200 rows supplied — request rejected
- Missing required fields (row_id, date, observed_points, expected_points) on any row — validation error
- Date strings not matching YYYY-MM-DD format — schema validation failure
- Numeric values outside allowed range — rejection
- Payment not processed — 402 response before analysis runs
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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