Test a specialized agent

  • Updated

Test your specialized agent in Optimizely Opal before deploying it or after editing it. Testing lets you verify that your agent responds correctly and catches configuration issues before users encounter them.

Tests run inside the agent editor. Single-shot agents run once and return a result. Multi-turn agents let you give follow-up instructions after the agent responds.

Access your agents

  1. Go to home.optimizely.com.
  2. Select your organization.
  3. Click Opal.

    Screenshot of the Optimizely home page showing the Opal option in the navigation
  4. Click Agents.

    Screenshot of the Agents page in Opal where the list of agents is displayed
  5. Click the Your Agents tab.

    Screenshot of the Agents page in Opal where the Your Agents tab is selected

Test your specialized agent

Follow these steps to run a Test Run on your specialized agent:

  1. Follow the steps in the Access your agents section.
  2. Click the agent name or click More actions (...) > Edit Agent.
  3. Click Test Run.

    Screenshot of the agent editor in Opal where the Test Run button is highlighted
  4. (Optional) Enter values for your agent's input variables (placeholders defined in the agent prompt that are filled in at runtime). To remove all values, click Clear All.
  5. Click Run.

The agent runs and displays the Execution Results. Click Stop Execution to end the Test Run

Test a multi-turn specialized agent

When you test a multi-turn specialized agent, the test run stays active after each response. This lets you continue the conversation across multiple turns.

  1. Follow the steps in the Access your agents section.
  2. Click the agent name or click More actions (...) > Edit Agent.
  3. Click Test Run.
  4. (Optional) Enter values for any input variables, then click Run.

    Screenshot of the Test Run panel for a multi-turn agent showing the Run button and no output yet
  5. Wait for the agent to complete Turn 1. An Agent response complete notification displays when the agent is ready for your reply.

    Screenshot of the Opal Chat interface where the Send and Done buttons display after the agent completes its first response
  6. Type your reply in the Type your message field and click Send to continue the conversation.

    Input variable values lock when the conversation starts. Click Reset to edit to change them and restart the test run.
  7. Continue replying across as many turns as needed. The Output section updates to show Execution Results (Turn X) after each turn. Execution Memory grows to reflect the full conversation history.
  8. Click Done to end the test run.

Execution results

The Execution Results include the following information:

  • Output – The agent's execution results for the current turn.
    • Execution ID – The unique identifier of the request.
    • Status – Whether the run was successful.
    • Agent's response – The agent's text response for the current turn. For single-shot agents, this is the final result returned to Opal Chat or a workflow agent. For multi-turn agents, the label displays as Execution Results (Turn X) and updates with each turn.
  • Execution Memory – Memory shows each step that Opal takes while executing the agent. Use this information to debug your agent and confirm that the outputs and steps are correct.
    • The first message shows the initial request, including the prompt template and variable values.
    • The last message is the final output returned to you.
    • Other messages in between are steps Opal takes to form its response, including tool calls in JSON format.
    • For multi-turn agents, memory grows with each turn and includes both User and Assistant chunks for the full conversation history.
       

      Screenshot of the Execution Results panel in Opal showing a truncated example of agent execution memory with step-by-step output and tool calls

The execution details also display in the specialized agent's logs.

If you use Opti ID, administrators can turn off generative AI in the Opti ID Admin Center. See Turn generative AI off across Optimizely applications.