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Time Series Completeness — Record Quality Audit & Duplicate Key Report
x402
Time Series Completeness — Record Quality Audit & Duplicate Key Report 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).
Performs a record quality audit and duplicate key detection report on up to 200 supplied time series completeness rows (observed_points, expected_points), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Record quality audit + Duplicate key report: Record quality audit + Duplicate key report 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 reports: (1) a record quality audit highlighting issues such as null values, out-of-range numbers, or malformed fields across the supplied rows, and (2) a duplicate key report identifying rows sharing the same key combinations (e.g. row_id, date, dataset_group). Both reports are produced locally without external lookups.
Example use cases
IoT sensor data completeness audit
“I have 80 rows of IoT sensor time series data with observed_points and expected_points per day for groups 'temp-sensor' and 'humidity-sensor' from 2025-03-01 through 2025-04-20 — can you run a full record quality audit and flag any duplicate row IDs or date-group combinations?”
Financial reporting data integrity check
“Before I finalize my monthly report, can you audit these 150 time series completeness records for our 'revenue' and 'expense' dataset groups across Q1 2025 — I need a quality audit and a duplicate key report to catch any bad or repeated rows?”
ETL pipeline output validation
“Our ETL pipeline just produced 200 time series rows with observed_points and expected_points for dataset groups 'pipeline-run-A' and 'pipeline-run-B' — can you check the data quality and identify any duplicate keys before we load it into the warehouse?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-003?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, local, low-cost ($0.01 USDC) dual-report — quality audit plus duplicate key detection — on batches of up to 200 time series completeness records with observed and expected point counts, without requiring any live data lookups, predictions, or external integrations. Ideal for pre-load validation in ETL pipelines, periodic data hygiene checks, or auditing completeness datasets before downstream analysis.
Side effects
- Exceeding 200 rows causes rejection — only up to 200 rows accepted per call
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern will fail schema validation
- Empty rows array (minItems: 1 not satisfied) will be rejected
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) will fail schema validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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