What is multi-agent-architecture-reference?
Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths Source: oimiragieo/agent-studio.
Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths
Quickly install multi-agent-architecture-reference AI skill to your development environment via command line
Source: oimiragieo/agent-studio.
Canonical reference for multi-agent topology selection — provides a 6-topology decision matrix with token economics, failure modes, escalation paths, and links to existing agent-studio patterns.
| Topology | Token Cost | Best For | Failure Modes | Existing Skill |
| Conductor | 6x | Sequential phases, ordered agent steps, default agent-studio pattern | Orchestrator overload (SE-M01) | master-orchestrator.md | | Supervisor | 5x | Known task types, specialist agents, deterministic routing | Single point of failure; router miscalibration (SE-M01) | Built into Router |
Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths Source: oimiragieo/agent-studio.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/oimiragieo/agent-studio --skill multi-agent-architecture-referenceDecision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths Source: oimiragieo/agent-studio.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/oimiragieo/agent-studio --skill multi-agent-architecture-reference Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/oimiragieo/agent-studio