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Data Validation Results – Trailing Mean Series
x402
Data Validation Results – 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 2026-10-17).
Computes a rolling/trailing mean time series over data validation metrics (checked_records or failed_records) grouped by rule, for up to 200 supplied records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data validation results - Trailing mean series: Trailing mean series for Data validation results. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded trailing mean series report.
Output
Returns a trailing mean series report: for each record in the input, a smoothed rolling average value computed over the specified window for the selected field (checked_records or failed_records), grouped by rule, with one bounded trailing mean series report per call. No enrichment or forecasting is included — purely local descriptive analytics.
Example use cases
Monitor validation failure trends over time
“I've got daily data validation logs for the past 3 months, each row has a date, a rule name, how many records were checked, and how many failed. Can you compute a trailing mean with a window of 14 over the failed_records so I can see the smoothed trend?”
Spot-check data pipeline health by rule
“Here are 80 validation records broken out by rule group — can you run a rolling average with a window of 5 over checked_records so I can see which rules are consistently processing fewer records than expected?”
Smooth noisy validation metrics for reporting
“My daily validation results are pretty noisy. Can you apply a trailing mean with window 10 to my failed_records series so I can present a cleaner trend line in my data quality report?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-validation-results-rolling?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, local rolling/trailing mean computation on your own data validation metrics (checked_records or failed_records) without sending data to a full analytics platform. It is ideal for smoothing noisy daily validation counts, spotting trends in rule-level failure rates, or generating a clean time series for reporting — all at very low cost ($0.01 per call) and with no external data enrichment or forecasting. Prefer alternatives if you need forecasting, anomaly detection, or enrichment beyond descriptive rolling statistics.
Side effects
- Fewer than 1 row supplied returns a validation error
- More than 200 rows supplied exceeds the maxItems limit
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Window size larger than the number of records for a given rule yields sparse or missing mean values
- Non-numeric or null values in the selected field may produce null averages for affected windows
- Malformed row_id or rule strings exceeding maxLength are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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