Test Agents

This article applies to:	New Testing Center in Agentforce Studio (Beta)
This article doesn't apply to:	Legacy Agentforce Testing Center in Setup

Available in: Lightning Experience

Available in: Enterprise, Performance, Unlimited, and Developer Editions. Required add-on licenses vary by agent type.

Testing agents in Agentforce Studio Testing Center lets you simulate conversations at scale and evaluate how your agent responds across many inputs at once. Instead of testing one scenario at a time, you build a test suite, provide test cases, and run the whole set together. Scorers automatically evaluate each response so you can quickly identify where your agent is falling short before it reaches users.

To build test cases, you can fast-track with AI-generated scenarios based on your agent's specific subagents and actions, or use data linked through an Agentforce Data Library. You can also manually craft and upload your own test cases, or automate test runs using the Testing Center API to integrate testing into your development workflow.

After generating test cases, select from built-in scorers or develop custom scorers tailored to your business needs. Track test history and manage all your test suites from the same spreadsheet-inspired interface.

• Create a Test Suite
  A test suite is the starting point for evaluating your agent. Name your test suite, select the agent to test, and choose whether you're evaluating individual responses or full end-to-end conversations.
• Define Test Conditions
  Choose how your agent accesses data during testing and configure optional conditions like conversation history and context variables to simulate more realistic interactions.
• Select Your Test Data
  Evaluate your agent's performance by using AI-generated test cases or uploading your own test cases in a CSV template. AI-generated test cases offer two data options: generating tests based on subagents and actions, or generating tests based on the knowledge available to the agent via an Agentforce Data Library.
• Select Scorers
  Scorers measure your AI agent’s performance across key areas. Default scorers are always tested, but you can select quality metrics to focus your tests on specific areas.