multi-agent-collaboration
Multi-Agent Collaboration
Multi-Agent Collaboration (MAC) involves a team of agents, each with a specific role, tools, and persona. They work together by exchanging messages, handing off tasks, or debating solutions. This mimics human organizational structures (e.g., a software team with a PM, Dev, and QA).
When to Use
- Separation of Concerns: To keep prompts simple and focused. Complex prompts often confuse models; specialized agents are more reliable.
- Role-Playing: When specific expertise or persona is needed (e.g., "Act as a grumpy editor").
- Scalability: Adding new capabilities is as simple as adding a new agent to the team.
- Simulating User Behavior: Modeling market dynamics, social networks, or game theory scenarios.
Use Cases
- Software Dev Team: Product Manager -> Developer -> Reviewer -> QA.
- Debate: Proposition Agent vs. Opposition Agent -> Moderator synthesizes.
- Creative Writing Room: Idea Generator -> Plot Outliner -> Dialogue Specialist -> Editor.
Implementation Pattern
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reflection
A recursive pattern where an agent evaluates and critiques its own output to iteratively improve quality and catch errors. Use when user asks to "add self-reflection", "agent introspection", "self-critique", or mentions self-evaluation, meta-cognition, or quality self-assessment.
18human-in-the-loop
A hybrid pattern where the system pauses execution to request human approval, input, or disambiguation before proceeding with critical actions. Use when user asks to "add human approval", "require human review", "human-in-the-loop", or mentions approval workflows, human oversight, or escalation.
18planning
A high-level cognitive pattern where an agent formulates a structured sequence of actions (a plan) before executing any of them, ensuring goal-directed behavior. Use when user asks to "add planning to my agent", "task planning", "agent planning", or mentions plan generation, plan execution, or step-by-step planning.
14parallelization
A concurrency pattern where multiple agent tasks are executed at the same time to speed up processing or gather diverse perspectives. Use when user asks to "run agents in parallel", "parallelize tasks", "concurrent execution", or mentions parallel processing, fan-out, or batch execution.
13routing
A control flow pattern where a central component classifies an input request and directs it to the most appropriate specialized agent or tool. Use when user asks to "route between agents", "agent routing", "task dispatch", or mentions classifier routing, intent detection, or agent selection.
12adaptation
A dynamic pattern where an agent system modifies its own behavior, prompts, or tools over time based on feedback or performance metrics. Use when user asks to "make my agent adaptive", "add learning capabilities", "self-improving agent", or mentions adaptive behavior, online learning, or feedback loops.
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