Detect anomalies in HR-IMS login, API, stock, and event logs.
npx skills add https://github.com/Arnutt-N/hr-ims --skill anomaly-detection-arnutt-n
Please help me install this Agent Skill. Skill: anomaly-detection Source: https://github.com/Arnutt-N/hr-ims/tree/main/.claude/skills/anomaly-detection Command: npx skills add https://github.com/Arnutt-N/hr-ims --skill anomaly-detection-arnutt-n
Detects anomalies in HR-IMS system activity to identify unusual patterns and alert teams.
Configure and run hourly anomaly checks to continuously monitor events and deliver alerts.
High-intent search queries and answers about installing and using this skill.
To detect anomalies in backend API usage and login activity, you apply rule-based detection against configurable baselines and thresholds. This monitors event logs to surface unusual patterns and raises alerts when threshold breaches occur.
Yes, anomaly detection supports configurable windows and baselines to tailor thresholds to your environment. You set custom rule parameters to define severity levels and trigger alerts for specific operational contexts.
Automated alerting for detected system anomalies works by persisting anomaly records in a Prisma-backed data store and routing notifications through admin dashboards. This escalates unusual patterns to relevant teams for intervention.
The best way to monitor stock levels for threshold breaches is running hourly anomaly checks against established baselines. This continuously evaluates operational logs to identify unusual inventory patterns and alert teams.
Yes, this anomaly detection approach requires a Prisma data store setup to persist detected anomalies and manage alerting workflows. The Prisma backend handles data storage for the rule-based detection engine.
michaelsvanbeekDetect unusual patterns in time-series, logs, and metric data.
OliverOuyangMonitor Guanyuan dashboard metrics and trigger alerts on rule violations.
Arnutt-NConsolidate real-time HR-IMS audit events into a unified monitoring dashboard.
htafollaAnalyze log streams, detect patterns, and trigger threshold-based alerts.
