zouroboros-introspect

Multi-agent system health monitoring aggregates weighted metrics for memory recall, graph connectivity, routing accuracy, and episode velocity into a 0–100 composite score, generating a ranked scorecard with HEALTHY/WARNING/CRITICAL statuses and recommended remediation actions.

Autonomous swarm introspection tracks memory recall, knowledge graph connectivity, routing accuracy, evaluation calibration, procedure freshness, and episode velocity, outputting per-metric diagnostics with trends and threshold-based status classifications.

Yes, system health scorecards export to JSON and optionally persist as episodic memories, feeding downstream prescription engines for automated evolution and prioritized playbook recommendations.

Daily health checks for multi-agent orchestration run on-demand or scheduled introspection, measuring subsystem degradation across memory, knowledge graph, swarm routing, and evaluation calibration to produce ranked improvement scorecards.

Prioritize fixes by running an introspection scorecard that ranks systemic degradation across subsystems, assigning per-metric scores and remediation actions so engineers can address CRITICAL issues before failures cascade.

Composite health scoring may not suit environments lacking episodic memory storage or metrics pipelines, as it depends on aggregating memory recall, graph connectivity, routing accuracy, and procedure freshness data to produce actionable diagnostics.