> ## Documentation Index > Fetch the complete documentation index at: https://docs.asteragents.com/llms.txt > Use this file to discover all available pages before exploring further. # Multi-Agent Workflows > Create collaborative workflows where specialized agents work together on complex tasks ## Overview Multi-agent workflows in Aster Agents allow you to create collaborative systems where specialized agents call each other to handle complex, multi-step tasks. Instead of building one agent that tries to do everything, you can create focused agents that excel at specific functions and coordinate their work automatically. ## How It Works Multi-agent coordination is powered by the `call_agent` tool. When you configure an agent to work with others, Aster Agents handles the wiring automatically. The calling agent receives information about available agents in its system prompt. Agents can continue conversations across multiple interactions. Information flows seamlessly between agents in the workflow. Only allows calls to explicitly configured agents. ### The Call Agent Tool The `call_agent` tool enables agents to: * Send messages to other specific agents * Continue existing conversation threads * Delegate specialized tasks * Build complex workflows through agent collaboration ## Setting Up Multi-Agent Workflows In the Control Hub when creating or editing an agent: * **Enable the Call Agent Tool**: Add `call_agent` to your agent's available tools * **Select Callable Agents**: Choose which other agents this agent can invoke from your organization's agent list * **Automatic Integration**: Agent details are automatically added to the system prompt When an agent has callable agents configured, they automatically receive: * **Agent Names**: Human-readable identifiers for each callable agent * **Agent IDs**: Technical identifiers needed for the `call_agent` tool * **Agent Descriptions**: Understanding of each agent's capabilities and specializations This information appears in the system prompt like this: ``` You have access to the following agents that you can call using the call_agent tool: - Data Analyst (ID: 123) Description: Specializes in analyzing sales data and creating insights - Report Writer (ID: 456) Description: Creates professional reports and presentations from data analysis When using the call_agent tool, you must provide the agent_id from the list above. ``` Plan how agents will work together: * **Define Roles**: What specific task does each agent handle? * **Map Information Flow**: What information needs to pass between agents? * **Plan Entry Points**: Which agent do users interact with first? * **Consider Threading**: When should agents continue existing conversations vs. start new ones? ## Common Workflow Patterns Agents work in a defined order, each building on the previous agent's work. **Example: Research to Report Pipeline** 1. **Research Agent** → Gathers information from web and knowledge bases 2. **Analysis Agent** → Processes findings and identifies key insights 3. **Writer Agent** → Creates formatted report from analysis 4. **Review Agent** → Quality checks and provides final output A primary agent delegates specific subtasks to specialized agents. **Example: Customer Support Triage** 1. **Support Agent** receives customer inquiry 2. Based on issue type, calls: * **Technical Agent** for product issues * **Billing Agent** for payment questions * **Account Agent** for user management 3. **Support Agent** synthesizes response for customer Multiple agents work simultaneously, with results combined by a coordinator. **Example: Market Research Workflow** 1. **Coordinator Agent** breaks down research request 2. Calls multiple agents in parallel: * **Web Research Agent** → Industry trends * **Data Agent** → Internal sales data * **Competitor Agent** → Competitive analysis 3. **Coordinator Agent** combines all findings into comprehensive report Agents work together through multiple rounds to refine outputs. **Example: Content Creation Loop** 1. **Writer Agent** creates initial draft 2. **Editor Agent** provides feedback and suggestions 3. **Writer Agent** revises based on feedback (using thread ID to continue conversation) 4. Process repeats until quality standards are met ## Practical Examples ``` Prospect Researcher (Entry Point) ├── Data Collector → Gathers company information ├── Social Media Analyst → Reviews social presence ├── News Tracker → Finds recent company updates └── Sales Strategist → Combines insights into outreach plan ``` ``` Content Manager (Entry Point) ├── Topic Researcher → Identifies trending subjects ├── Writer → Creates initial content ├── SEO Optimizer → Enhances for search ├── Social Media Adapter → Creates platform-specific versions └── Publisher → Schedules and distributes content ``` ``` Data Coordinator (Entry Point) ├── Data Collector → Extracts from databases/APIs ├── Cleaner → Processes and validates data ├── Analyst → Performs statistical analysis ├── Visualizer → Creates charts and graphs └── Reporter → Compiles findings into presentation ``` ## Best Practices 1. **Single Purpose**: Each agent should excel at one specific type of task 2. **Clear Descriptions**: Write detailed agent descriptions since these appear in system prompts 3. **Consistent Interfaces**: Design agents to work well together 4. **Error Handling**: Consider what happens when agents can't complete tasks 1. **Start Simple**: Begin with 2-3 agents and expand gradually 2. **Map Dependencies**: Understand which agents need outputs from others 3. **Plan for Failures**: What happens if an agent in the chain fails? 4. **Test Thoroughly**: Run complete workflows manually before deploying 1. **Clear Handoffs**: Agents should know exactly what information to pass along 2. **Context Preservation**: Use thread IDs to maintain conversation context when needed 3. **Status Updates**: Keep users informed about multi-step progress 4. **Result Integration**: Plan how final outputs get assembled and presented 1. **Parallel vs Sequential**: Choose based on dependencies and urgency 2. **Thread Management**: Use conversation threads strategically to maintain context 3. **Token Efficiency**: Monitor cumulative token usage across agent calls 4. **User Experience**: Balance thoroughness with response time ## Managing Multi-Agent Systems * **Agent Permissions**: Carefully control which agents can call which others * **Role Clarity**: Ensure each agent's purpose is clearly defined and documented * **Version Control**: Track changes to agent configurations and relationships * **Workflow Performance**: Monitor how long complete workflows take * **Agent Utilization**: Track which agents are called most frequently * **Success Rates**: Measure how often workflows complete successfully * **User Feedback**: Collect input on workflow quality and usefulness * **Context Loss**: Information getting lost between agent handoffs * **Circular Calls**: Agents calling each other in loops * **Permission Errors**: Agents trying to call agents they don't have access to * **Thread Management**: Confusion about when to start new threads vs continue existing ones ## Getting Started ### Your First Multi-Agent Workflow Choose something that naturally breaks into distinct phases. Build 2-3 agents that handle different aspects. Set up which agents can call which others. Run through the complete workflow manually. Improve based on results and add complexity gradually. ### Simple Starter Workflows Great for information gathering and synthesis. Perfect for content creation and quality control. Ideal for data analysis tasks. Excellent for customer support scenarios. *** Multi-agent workflows unlock the full potential of AI collaboration, allowing you to create sophisticated systems that handle complex tasks through intelligent coordination between specialized agents.