Agents
An Agent action in Lleverage allows you to create AI-powered automation that can perform multiple steps and make decisions to complete complex tasks. Agents use the actions you provide to work through problems autonomously until the specified objective is achieved.
Key Features
Decision-making capabilities to determine the best approach to a task
Action selection from tools you provide
Iterative processing that continues until instructions are fulfilled
Dynamic variable integration for workflow context
How to Add an Agent Action
Open the Add Action menu using one of three methods:
Click the "Add Action" button in the top left corner
Click on a connection circle on an existing action card
Click and drag from one action to create a connection
Select "AI" from the categories or find "Agent" in the options
Click on "Agent" to add it to your canvas
💡 The Agent action appears similar to the Prompt action in the workflow canvas.
How to Configure the Agent Action Card
Locate the Agent card on your canvas which includes:
Header with the action name
Variable chip in the top left corner for referencing outputs
Control buttons for expanding/collapsing and running the agent
Connection points for inputs and outputs
Configure the basic settings:
Model selection: Choose from Balanced (default), Fastest, or Smartest options
Instructions: Add your agent's objective in the instructions box
Provide clear instructions for what the agent needs to accomplish
⚠️ Be specific with instructions as this determines how the agent will operate.
How to Add Actions to Your Agent
Below the instructions section, locate the "Actions" area
Click "Add Action" to open the action picker
Select actions from the list that your agent will be able to use
The agent will automatically have access to these capabilities during execution
💡 The agent will attempt to automatically configure actions when possible, using context from your instructions.
How the Agent Action Works
The agent analyzes your instructions to understand the objective
It selects appropriate actions from those you've provided
It executes actions in sequence, making decisions based on results
The process continues until the agent determines the instructions have been fulfilled
The final output is passed to the next action in your workflow
⚠️ If action configurations have been previously specified in your workflow, the agent will follow those rules rather than creating its own configuration.
Writing Effective Agent Instructions
Be clear about the specific goal the agent needs to achieve
Specify any constraints or requirements for the solution
Reference any variables the agent should use with proper syntax
Focus on the "what" (goal) rather than the "how" (specific steps)
💡 For best results, provide context that helps the agent understand the problem scope.
Testing Your Agent Action
Click the "Run" button on the Agent card to test it with current workflow variables
Review the final output to ensure it meets your requirements
Adjust instructions or available actions if necessary to improve results
⚠️ Agents may take longer to execute than standard prompts because they perform multiple steps to complete a task.
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