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Time Series Completeness — Exact Row Deduplication + Keyed Dataset Comparison
x402
Time Series Completeness — Exact Row Deduplication + 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 2026-10-24).
Performs exact row deduplication and keyed dataset comparison on two sets of time series completeness records (observed_points vs 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 — Exact row deduplication + Keyed dataset comparison: Exact row deduplication + 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
Two independent analytical reports: (1) an exact row deduplication report identifying duplicate records within the supplied dataset(s), and (2) a keyed dataset comparison report highlighting rows that differ between the two supplied datasets based on observed_points and expected_points values — all computed locally without any external lookups or predictions.
Example use cases
Daily pipeline completeness audit
“I have two snapshots of my daily data pipeline completeness records — each with about 30 rows covering dates in October 2026, dataset groups 'group-a' and 'group-b', and observed vs expected point counts. Can you deduplicate each snapshot and show me which rows differ between them?”
Sensor feed gap detection
“I'm monitoring two sensor feed datasets for missing data points. Each has up to 100 rows with a date, a sensor group name, observed readings, and expected readings. Can you run exact duplicate removal on both and then compare them row-by-row to highlight any keyed differences?”
ETL job output validation
“We ran two ETL jobs and got two result sets of completeness records — around 80 rows each, with row IDs, dataset groups, dates, and observed vs expected counts. Please deduplicate both and give me a comparison report showing where the outputs diverge.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-053?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need deterministic, purely local deduplication and cross-dataset comparison on time series completeness records (observed vs expected data points) with up to 200 rows, and you want two independent reports in a single $0.01 call — without requiring live data lookup, ML prediction, or external enrichment.
Side effects
- Exceeding 200 rows per dataset triggers a validation error
- Missing required fields (row_id, date, dataset_group, observed_points, expected_points) causes rejection
- Invalid date format (non YYYY-MM-DD) fails schema validation
- Empty rows array (minItems:1 not met) returns an error
- Numeric values outside allowed range (-1e12 to 1e12) are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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