Observe Metrics
Skill Verifiziert AktivAggregate and display system metrics with anomaly detection for a time period
To provide users with a clear and actionable snapshot of system health by aggregating metrics and identifying anomalies, enabling quick detection of performance degradation.
Funktionen
- Aggregate system metrics (counters, gauges, histograms)
- Detect anomalies based on historical baselines
- Report on metric deviations, direction, and severity
- Compute overall health score
- Store metric patterns for future reference
Anwendungsfälle
- Monitor swarm performance by tracking task completion and error rates
- Detect degradation in active agent counts or memory usage
- Identify unusual token consumption patterns
- Analyze time-series data for performance trends
Nicht-Ziele
- Real-time, second-by-second monitoring
- Long-term trend analysis beyond the specified period
- Automated remediation of detected anomalies
Workflow
- Retrieve metrics using `mcp__claude-flow__memory_search` or `memory_list` for the specified period.
- Aggregate counters, gauges, and histograms.
- Compute baselines using `mcp__claude-flow__agentdb_pattern-search`.
- Flag anomalies based on deviation from baselines.
- Store patterns using `mcp__claude-flow__agentdb_pattern-store` or `memory_store`.
- Display metric name, value, baseline, deviation, trend, anomaly flag, and overall health score.
Praktiken
- Observability
- Anomaly Detection
- System Monitoring
Voraussetzungen
- Claude Code environment
- Access to `mcp__claude-flow__memory_search`
- Access to `mcp__claude-flow__memory_list`
- Access to `mcp__claude-flow__agentdb_pattern-search`
- Access to `mcp__claude-flow__agentdb_pattern-store`
Installation
Zuerst Marketplace hinzufügen
/plugin marketplace add ruvnet/ruflo/plugin install ruflo-observability@rufloQualitätspunktzahl
VerifiziertVertrauenssignale
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