From design-agent-orchestration
Maps multi-agent system architecture: inventories agents with roles, communication graphs, authority matrix, dependencies, risks, and recommendations.
How this command is triggered — by the user, by Claude, or both
Slash command
/design-agent-orchestration:map-agents [multi-agent system or agentic product to map]The summary Claude sees in its command listing — used to decide when to auto-load this command
You are mapping the agent architecture of a multi-agent system. Use only skills from the design-agent-orchestration plugin. Follow this process: ## Step 1: Inventory the Agents List every agent in the system (or planned for the system): - What is each agent called? - What is its stated purpose? - What tools and data does it have access to? ## Step 2: Define Roles Formally Using **agent-role-design**: - For each agent, create a complete role card - Identify role patterns (specialist, router, orchestrator, validator, fallback) - Check for gaps: are there tasks no agent covers? - Check for ove...
You are mapping the agent architecture of a multi-agent system. Use only skills from the design-agent-orchestration plugin. Follow this process:
List every agent in the system (or planned for the system):
Using agent-role-design:
Using handoff-protocols:
Using agent-role-design and human-in-the-loop:
Using state-management and task-decomposition:
Using failure-recovery:
Deliver a complete agent map:
npx claudepluginhub owl-listener/ai-design-skills --plugin design-agent-orchestration/plan-systemInvokes rcc:planning-agent-systems skill to plan agent system components with traceability and reuse analysis.
/planejar-sistemaPlans agentic system architecture by generating a complete blueprint with agents, data flow, and contracts. Produces a BLUEPRINT.md file before any artifact creation, solving circular dependency between agent and orchestrator design.
/orchestratorDispatches requests to specialized agents and coordinates multi-agent collaboration for complex or ambiguous tasks.
/strategic-thinkerOrchestrates multi-agent strategies for complex task analysis, decomposition, and coordination to deliver optimized enterprise solutions.
/ai-agents-testTests multi-agent system by running a provided task through agent network, displaying handoffs, performance metrics (time, count), and coordination validation.