From design-agent-orchestration
Guides state management in multi-agent systems, covering state types, architecture patterns like centralized and event-sourced, conflict resolution, and user-facing designs.
npx claudepluginhub owl-listener/ai-design-skills --plugin design-agent-orchestrationThis skill uses the workspace's default tool permissions.
In a multi-agent system, state is the shared truth about what's happened, what's in progress, and what's been decided. Without state management, agents work with stale or conflicting information.
Guides multi-agent LLM architectures with supervisor, swarm, and hierarchical patterns for context isolation, handoffs, and parallel execution.
Designs multi-agent LLM architectures using supervisor, swarm, and hierarchical patterns for context isolation, parallel tasks, and coordination beyond single-agent limits.
Designs multi-agent LLM architectures for complex tasks exceeding single-agent context limits, decomposing into subtasks, or requiring agent specialization.
Share bugs, ideas, or general feedback.
In a multi-agent system, state is the shared truth about what's happened, what's in progress, and what's been decided. Without state management, agents work with stale or conflicting information.
Users have expectations about what the system remembers:
When multiple agents modify state simultaneously: