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Time Series Completeness — Record Quality Audit + Trailing Mean Series
x402
Time Series Completeness — Record Quality Audit + Trailing Mean Series 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 time series completeness records (observed vs expected points) and produces two reports: a record quality audit and a trailing mean series, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series 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 for the submitted rows: (1) a record quality audit flagging anomalies or completeness issues per row based on observed vs expected points, and (2) a trailing mean series computed over the selected field (observed_points or expected_points) using the specified window size. No external lookups or predictions are made.
Example use cases
Daily pipeline completeness audit
“I have 30 days of pipeline data with observed and expected point counts per dataset group — can you run a record quality audit and a trailing mean series with a window of 7 on the observed_points field to spot completeness issues?”
Sensor coverage gap detection
“Audit the quality of these 50 sensor coverage records and give me a trailing mean with a window of 5 on expected_points — the rows span from 2025-01-01 to 2025-02-19 across two sensor groups.”
Data ingestion monitoring report
“I want to check the record quality and compute a rolling average completeness trend (window of 10) for our data ingestion logs — here are 100 rows with observed and expected point counts by date and ingestion group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-010?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two bundled analytical outputs — a data quality audit and a trailing mean series — on time series completeness data (observed vs expected point counts) in a single low-cost call. It is ideal for batch offline analysis of up to 200 rows without requiring external data sources or live lookups. Prefer it over single-report endpoints when you need both quality auditing and trend smoothing in one request for the same dataset.
Side effects
- Fewer than 1 or more than 200 rows submitted — validation error
- Missing required fields (row_id, date, observed_points, expected_points) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Window size outside allowed range (2–200) — validation error
- Null values in numeric fields may affect trailing mean computation
- Payment failure via x402 protocol — request not processed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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