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Time Series Gap and Anomaly Checker

Checks CSV time series (metrics, sensor readings, sales by hour) for data problems before you chart or alert on them: missing intervals, duplicate or out-of-order timestamps, empty values, flatlines from stuck exporters, robust median/MAD spikes, and counter resets. Use when a dashboard looks wrong, before training a forecast, or when asking "is this data complete?". Includes a stdlib Python checker with --self-test.

F
@f
about 4 hours agoOctober 28, 2026 at 12:02 PM
Agent Skill•PythonData AnalysisData Quality
SRE
Monitoring
Metrics
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