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Time Series Completeness — Duplicate Key Report + Grouped Numeric Summary
x402
Time Series Completeness — Duplicate Key Report + Grouped Numeric Summary 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).
Analyzes up to 200 time series completeness records to produce a duplicate key report and a grouped numeric summary of observed vs. expected data points.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Duplicate key report + Grouped numeric summary: Duplicate key report + Grouped numeric summary 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 duplicate key report identifying any repeated row_id values within the submitted records, and (2) a grouped numeric summary of the selected field (observed_points or expected_points) aggregated by dataset_group — both computed locally with no external lookups.
Example use cases
Daily pipeline completeness audit
“I have 150 daily completeness records for two dataset groups — each with a row_id, date, observed_points, and expected_points. Can you find any duplicate row IDs and give me a grouped numeric summary of observed_points by dataset_group?”
Detecting repeated keys in data quality logs
“Here are my time series completeness logs with fields row_id, dataset_group, date, observed_points, and expected_points — can you run a duplicate key report and a grouped summary of expected_points to help me spot data ingestion issues?”
Comparing completeness across sensor groups
“I've got completeness data for three sensor groups across the past month — up to 200 rows with row_id, date, observed_points, and expected_points. Please check for duplicate keys and summarize the observed_points statistics grouped by dataset_group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-056?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary data quality reports — duplicate key detection and grouped numeric statistics — on time series completeness data (observed vs. expected points) in a single low-cost call. It is ideal for data engineers auditing pipeline completeness logs by group, without needing any external data enrichment, predictions, or live lookups.
Side effects
- Fewer than 1 row submitted — minimum item count not met
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, observed_points, or expected_points) on any row
- Date field does not match YYYY-MM-DD format
- Numeric values outside the allowed range (-1e12 to 1e12)
- Invalid field enum value supplied (must be 'observed_points' or 'expected_points')
- Payment of 0.01 USDC not provided — x402 payment required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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