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From design-agent-orchestration
Guides observability design for multi-agent workflows, covering execution traces, decisions, handoffs, metrics, and audience-specific dashboards for debugging and improvement.
How this skill is triggered — by the user, by Claude, or both
Slash command
/design-agent-orchestration:observability-designThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You can't improve what you can't see. Observability design makes the internal workings of multi-agent systems visible — so designers can understand user experience problems, developers can debug failures, and teams can improve the system over time.
You can't improve what you can't see. Observability design makes the internal workings of multi-agent systems visible — so designers can understand user experience problems, developers can debug failures, and teams can improve the system over time.
For designers:
Too much data is as bad as too little:
npx claudepluginhub owl-listener/ai-design-skills --plugin design-agent-orchestrationDesigns observability for multi-agent systems with per-agent metrics, aggregate stats, agent cards, and event streams to monitor execution, track costs, log activities, and debug workflows.
Design observability (metrics, logs, traces) for understanding system behavior in production. Use when debugging distributed systems or building monitoring.
Evaluates and monitors AI agents with Opik observability. Covers architecture patterns, tracing, evaluation metrics, and production monitoring for reliable agents.