Add test cases to evaluate your agent’s performance by either generating them with AI
or uploading your own scenarios. AI-generated test cases offer two data options: generating
based on subagents and actions, or generating from knowledge available to the agent via the
Agentforce Data Library.
Use the subagents and actions method when you want to test how well your agent handles specific
intents or workflows, especially after updates or before launch. This approach helps confirm
the agent triggers the correct behaviors based on user utterances. Alternatively, choose the
knowledge-based method to validate your agent’s ability to provide accurate, content-driven
responses using connected knowledge sources like articles or PDFs. For full control, you can
also upload a CSV file with your own test scenarios which is ideal for custom testing needs or
validating specific business logic. Each approach allows you to simulate real-world
interactions and identify improvement areas before deploying your agent.
Generate Tests from Subagents and Actions Evaluate how well your agent handles key subagents and actions before launch. Generate relevant, test-ready utterances using your subagent and action metadata as well as information from connected data libraries. Simply choose the subagents you want to test, define the test focus with a brief description, and let the system generate up to 100 test cases.
Generate Tests from Knowledge Sources When your agent is connected to an Agentforce Data Library, you can generate test scenarios directly from the content linked to that library including articles and knowledge fields or uploaded files. Testing center generates up to 100 question-and-answer style test cases based on the knowledge content available to the agent.
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