Agent Action

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Capabilities

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When to use Agent Action

• The task requires judgment or adaptation
• Multiple steps need to happen based on what’s found
• You need to combine browser automation with data processing
• The exact steps depend on page content

• You need pure data transformation without browser context (Process Data)
• You want to make a direct HTTP call (API Request)
• You need to branch or loop (If/Else, Loop)

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Creating an Agent Action node

1. In the builder, click + Add Node and select Agent Action
2. Write a prompt describing what the agent should do
3. Define outputs the agent should produce
4. Optionally attach skills and integrations

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Writing effective prompts

Extract all invoice numbers and amounts from the current page.

1. Look for a table or list of invoices
2. For each invoice found, capture:
   - Invoice number (usually starts with "INV-")
   - Amount (numeric value with currency)
   - Date if visible
3. If pagination exists, note that more pages are available
   but don't navigate to them

Return the data as a list of objects.

• Break complex tasks into numbered steps
• Specify what success looks like
• Mention edge cases or constraints
• Don’t over-specify - let the agent adapt

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Defining outputs

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Advanced features

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Network request inspection

The table shows applicant names but the IDs aren't in the HTML.

1. Navigate to the applicants page
2. Use get_network_requests to find the API call that loads the table
3. Use get_network_response_body to get the JSON response
4. Extract the applicant IDs from the API response
5. Build the detail URLs: /applicants/{id}

• get_network_requests(url_pattern, method) - Find captured requests
• get_network_response_body(request_id) - Get response content

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Attaching skills

1. Open the Agent Action node
2. Find the Skills section
3. Select skills that apply to this task

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Toolsets

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Using integrations

1. In the node editor, find Integrations
2. Select which connected accounts to allow
3. Describe the integration work in your prompt

Using the connected Google Sheets account:
1. Open the spreadsheet "Monthly Reports"
2. Find the sheet named "January"
3. Add a new row with today's date and the extracted totals

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Visual references

1. Expand Advanced > Visual References
2. Upload or paste screenshots
3. Label them clearly (e.g., “Login page”, “Success state”)

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Combining with other nodes

Login → Agent Action → Process Data → File Output

• Use Login to authenticate with stored credentials
• Use Agent Action for browser automation, data extraction, and adaptive steps
• Use Process Data to transform or reformat captured variables
• Use File Output or Email Send to deliver results

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Troubleshooting

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Agent doesn’t find elements

• Add visual references showing the expected UI
• Be more specific about element descriptions
• Mention in the prompt that the agent should wait for dynamic content to load

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Outputs are empty

• Verify output names match what’s declared
• Check the run logs for what the agent captured
• Ensure the agent prompt asks for the data explicitly

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Integration calls fail

• Verify the integration is connected in Settings > Integrations
• Check that the task has the integration enabled
• Review the integration’s required scopes/permissions

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Best practices

1. Start simple: Write a basic prompt, run it, then refine
2. Use skills for patterns: Extract repeated guidance into skills
3. Declare all outputs: Don’t rely on implicit variables
4. Add verification: Include verification steps in the prompt or use Process Data to validate outputs
5. Check run logs: The execution view shows exactly what the agent did