Agent settings provide global configuration options that control how your agent behaves, what instructions it follows, and how it interacts with other agents. These settings are applied automatically in the agent runtime and can also be accessed or overridden via the SDK.
The General settings control basic agent configuration:
Configure your agent’s basic identity:
Agent Name: The name displayed in the interface and used in API calls
Status: Toggle between Active and Inactive (inactive agents cannot be called)
Choose the AI model powering your agent:
Model Provider: Select the provider (e.g., OpenAI)
Model Name: Choose the specific model (e.g., gpt-4o)
More powerful models like GPT-4o may produce better results but consume more tokens. Consider your use case carefully when selecting a model.
Configure who can access and use this agent:
Personal: Only you can access this agent
Organizational: All team members in your organization can access this agent
This setting is particularly important for agents that might access sensitive data or require specific permissions.
Convert your configured agent into a reusable template:
Enter a template name
Click “Create Template”
Templates allow you to quickly create new agents with the same configuration, saving time when building similar agents.
The General settings control basic agent configuration:
Configure your agent’s basic identity:
Agent Name: The name displayed in the interface and used in API calls
Status: Toggle between Active and Inactive (inactive agents cannot be called)
Choose the AI model powering your agent:
Model Provider: Select the provider (e.g., OpenAI)
Model Name: Choose the specific model (e.g., gpt-4o)
More powerful models like GPT-4o may produce better results but consume more tokens. Consider your use case carefully when selecting a model.
Configure who can access and use this agent:
Personal: Only you can access this agent
Organizational: All team members in your organization can access this agent
This setting is particularly important for agents that might access sensitive data or require specific permissions.
Convert your configured agent into a reusable template:
Enter a template name
Click “Create Template”
Templates allow you to quickly create new agents with the same configuration, saving time when building similar agents.
The Instructions settings define how your agent understands its purpose and behaves:
Define your agent’s identity and responsibilities:
You are the LinkedIn AI Agent, responsible for fetching posts, summarizing profiles, and providing insights based on LinkedIn data.
A clear role helps the agent understand its purpose and capabilities. Be specific about what domain the agent specializes in.
Define the primary objective of your agent:
Your goal is to assist users in gathering and summarizing information from LinkedIn, including posts and profiles, to enhance networking and professional insights.
Goals provide direction for the agent when deciding how to approach tasks.
Provide specific guidance on how the agent should behave:
Brand Voice: Maintain a tone that is [e.g., professional, conversational, authoritative, or witty—adjust based on brand identity]. Avoid jargon unless relevant. Target Audience: Always consider the intended audience, such as small business owners, executives, or job seekers.
Detailed instructions can include:
Tone and style guidelines
Response formatting preferences
Error handling procedures
Ethical considerations
Domain-specific knowledge
The Prompts section helps define example queries your agent should be prepared to handle:
Add example prompts that represent typical user requests:
“Fetch the latest posts from a specific company.”
“Summarize the profile of a user with username ‘john_doe’.”
“What are the recent posts related to ‘AI technology’?”
“Get the profile details of ‘Jane Smith’ including her skills and experience.”
“Show me the reposts of a specific LinkedIn post.”
In multi-agent workflows, these prompts help the router agent determine which specialized agent should handle the request. Choose examples that clearly demonstrate your agent’s capabilities.
Click the “Add” button to create new example prompts
Click the “X” icon next to a prompt to remove it
Ensure your prompts cover the full range of your agent’s capabilities
Well-crafted prompts help your agent understand the types of requests it should handle, especially in multi-agent environments.
The Delegation settings define how your agent interacts with other agents in a multi-agent workflow:
Choose how your agent delegates tasks to other agents:
Router: The agent evaluates incoming requests and routes them to the appropriate specialized agent
Sequence: The agent is part of a predetermined sequence of agents that process tasks in order
Delegation is essential in multi-agent layouts. When building complex workflows, you’ll need to configure delegation for each agent in the system.
When configured as a Router:
The agent analyzes incoming requests
It matches the request with the most appropriate specialized agent based on:
The specialized agent’s defined capabilities
Example prompts configured for each agent
Any routing rules you’ve defined
It forwards the request to the selected agent
Optionally, it can process and enhance the response before returning it to the user
Routers are ideal for creating “hub and spoke” architectures where a central agent directs traffic to specialized workers.
When configured as part of a Sequence:
The agent receives tasks in a predefined order
It processes its portion of the task
It passes the enhanced output to the next agent in the sequence
The final agent in the sequence returns the result to the user
Sequences are ideal for workflows where tasks need to be processed in specific stages, with each agent adding value in sequence.
Learn more about delegation and multi-agent teams in the Multi-Agent Teams section.
All agent settings can be accessed and modified programmatically using the xpander.ai SDK:
from xpander_sdk import XpanderClient# Initialize clientxpander_client = XpanderClient(api_key="your-api-key")# Get existing agentagent = xpander_client.agents.get("your-agent-id")# Update instructionsagent.update_instructions( role="You are the LinkedIn Research Assistant, specialized in finding and analyzing profile data.", goal="Help users discover relevant professionals and understand their background and experience.", instructions="Always maintain a professional tone. Prioritize accuracy over speed.")# Update model settingsagent.update_model(provider="openai", model="gpt-4o")# Configure delegationagent.configure_delegation(type="router")# Add example promptsagent.add_prompt("Find LinkedIn profiles of AI researchers in California")agent.add_prompt("Summarize the career trajectory of [username]")# Save changesagent.sync()
