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Overview

Aster Agents makes it easy to create custom AI agents that can perform specific tasks, access your data, and integrate with your workflows. Whether you need a customer support agent, data analyst, or specialized assistant, you can build exactly what your team needs.

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Getting Started

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Creating Your First Agent

  1. Navigate to Control Hub → Agents
  2. Click “Create New Agent”
  3. Configure the basic settings:
    • Name: What your team will call this agent
    • Description: What this agent does and when to use it
    • Stage: Development (for testing) or Released (for team use)

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Agent Configuration

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System Prompt

The system prompt defines your agent’s personality, expertise, and behavior:
  • Role Definition: What kind of expert is this agent?
  • Behavioral Guidelines: How should it respond and interact?
  • Task Specifications: What specific tasks should it focus on?
  • Communication Style: Formal, casual, technical, friendly?
Example System Prompts: 
Customer Support Specialist: You are a helpful customer support agent for our SaaS platform. Always be polite, empathetic, and solution-oriented. If you can't solve an issue immediately, escalate appropriately and keep the customer informed.

Data Analyst: You are an expert data analyst specializing in business intelligence. When analyzing data, always provide clear insights, visualizations when helpful, and actionable recommendations. Explain your methodology and assumptions.

Technical Writer: You are a technical documentation specialist. Create clear, comprehensive documentation that is easy to follow. Use proper formatting, include examples, and structure information logically.

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Model Selection

Choose the AI model that powers your agent:
  • Default Models: Use your organization’s default chat model
  • Specialized Models: Select specific models for different capabilities
  • Reasoning Models: Use advanced models like o1 for complex problem-solving
  • Performance Models: Balance speed and capability based on your needs

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Prompt Variables

Customize your agent’s behavior with dynamic variables:
  • {{USER_NAME}}: Personalizes responses with the user’s name
  • {{ORG_NAME}}: References your organization name
  • {{CURRENT_DATE}}: Includes today’s date for time-sensitive responses
  • Custom Variables: Define your own organization-specific variables

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Tools & Capabilities

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Built-in Tools

Give your agent access to powerful capabilities: Web & Research
  • Web Search: Find current information online
  • URL Scraping: Extract content from specific websites
  • Ask Web: Get AI-powered answers from web sources
Data & Analysis
  • Execute Python: Run code for data analysis and processing
  • Database Queries: Connect to Postgres, Snowflake, and other databases
  • Knowledge Base Search: Access your organization’s documents
Communication & Productivity
  • Send Email: Automate email communications
  • Generate PowerPoint: Create presentations from data
  • API Calls: Integrate with external services
Social Media & Content
  • Reddit Search: Research discussions and communities
  • TikTok Search: Find relevant video content
  • Google Sheets: Read and update spreadsheets

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Multi-Agent Capabilities

Create sophisticated workflows with agent collaboration:
  • Call Agent Tool: Let agents work together on complex tasks
  • Agent Hierarchies: Design workflows where specialized agents handle specific parts
  • Task Delegation: Route different types of requests to appropriate agents

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Integrations

Connect your agent to your existing tools and data:
  • Database Connections: Postgres, Snowflake, and more
  • Cloud Storage: Access files and documents
  • Third-party APIs: Connect to your business systems
  • Knowledge Bases: Search your organization’s documents

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Advanced Configuration

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Agent Stages

Manage your agent development lifecycle:
  • Development: Test and iterate on agent behavior
  • Released: Deploy to your team for production use
  • Visual Grouping: Development agents appear separately in selection menus

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Multi-Agent Workflows

Design complex workflows with multiple specialized agents: Example Workflow:
  1. Research Agent: Gathers information from web and databases
  2. Analysis Agent: Processes data and identifies insights
  3. Presentation Agent: Creates formatted reports and presentations
  4. Review Agent: Quality checks and finalizes deliverables

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Knowledge Base Integration

Connect your agents to your organization’s knowledge:
  • Selective Access: Choose which knowledge bases each agent can search
  • Automatic Discovery: Agents find relevant information during conversations
  • Context Awareness: Search results inform agent responses naturally

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Custom Metadata

Organize and track your agents with custom metadata:
  • Categories: Group agents by department, function, or use case
  • Tags: Add searchable labels for easy discovery
  • Ownership: Track which team or person manages each agent

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Best Practices

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Effective System Prompts

  1. Be Specific: Clear, detailed instructions produce better results
  2. Include Examples: Show the agent how to handle different scenarios
  3. Set Boundaries: Define what the agent should and shouldn’t do
  4. Iterate: Test and refine based on real usage

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Tool Selection

  1. Start Simple: Begin with basic tools and add complexity gradually
  2. Match Capabilities to Tasks: Choose tools that align with your agent’s purpose
  3. Consider Performance: More tools can slow down response time
  4. Test Thoroughly: Verify tools work as expected in your environment

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Deployment Strategy

  1. Development Phase: Test with a small group first
  2. Feedback Collection: Gather input from early users
  3. Iterative Improvement: Refine based on real usage patterns
  4. Gradual Rollout: Expand access as confidence grows

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Use Case Examples

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Customer Support Agent

Purpose: Handle customer inquiries and support tickets Tools: Knowledge Base Search, Send Email, Web Search System Prompt: Focus on helpfulness, escalation procedures, and solution-oriented responses

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Sales Research Agent

Purpose: Research prospects and prepare sales materials Tools: Web Search, Database Queries, Generate PowerPoint, Call API System Prompt: Emphasize thoroughness, data accuracy, and professional communication

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Content Creation Agent

Purpose: Create marketing content and social media posts Tools: Web Search, Execute Python (for image processing), Ask Web System Prompt: Focus on brand voice, creativity, and audience engagement

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Data Analysis Agent

Purpose: Analyze business data and create reports Tools: Database Queries, Execute Python, Generate PowerPoint, Knowledge Base Search System Prompt: Emphasize accuracy, insight generation, and clear explanations

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Monitoring & Optimization

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Performance Tracking

Monitor your agent’s effectiveness:
  • Usage Analytics: See how often agents are used
  • User Feedback: Collect thumbs up/down ratings
  • Conversation Analysis: Review interactions for improvement opportunities
  • Error Monitoring: Track and resolve issues quickly

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Continuous Improvement

Keep your agents performing at their best:
  • Regular Reviews: Assess agent performance monthly
  • Prompt Refinement: Update system prompts based on usage patterns
  • Tool Optimization: Add or remove tools based on actual needs
  • User Training: Help your team get the most from their agents

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Scaling Considerations

As your agent usage grows:
  • Resource Planning: Monitor token usage and costs
  • Access Management: Implement proper user permissions
  • Version Control: Track changes to agent configurations
  • Backup & Recovery: Maintain copies of successful configurations
Building effective AI agents is an iterative process. Start with clear goals, test thoroughly, and continuously refine based on user feedback and performance data. With Aster Agents, you have all the tools needed to create powerful, specialized assistants that transform how your team works.