Smart Assertions

Smart Assertions represent a breakthrough in test automation logic. Instead of wrestling with brittle CSS selectors or complex XPath configurations, Smart Assertions allow you to define UI validations using simple, human-readable English.

You just describe what should be true about a selected UI element, and Robonito’s AI engine automatically translates your intent into robust validation logic under the hood.

Smart Assertion Dialog

How to Create a Smart Assertion

You can inject a Smart Assertion during an active recording session or while editing a saved test step.

Writing the Assertion Description

Provide a clear, declarative sentence explaining exactly what you expect from the selected UI element.

Examples of Good Smart Assertions:

  • "The login button should be visible and clickable."
  • "The error message should contain the text 'Invalid credentials'."
  • "The submit button should currently be disabled."

Note: The description box supports up to 500 characters, allowing for highly specific multi-condition sentences.

Best Practices for AI Validation

To ensure your Smart Assertions evaluate perfectly every time, follow these guidelines:

  1. Target Accuracy: Always click to accurately highlight the specific target UI element on the page before writing the rule.
  2. Be Explicit: Describe exactly what you want to verify. Avoid vague language like "It should work."
  3. Use Common Keywords: Robonito's engine responds exceptionally well to standard state keywords, including:
    • should be visible
    • should be clickable
    • should contain text
    • should be disabled or enabled
  4. Save and Execute: Click Save Assertion.

Robonito will evaluate this plain-English rule dynamically during test execution.

Why Use Smart Assertions?

Relying on Smart Assertions dramatically streamlines your automation workflow:

  • Zero Coding Required: Skip manual configuration and complex property dropdowns entirely.
  • Maximum Readability: Anyone on your team—from developers to business analysts—can read the test and immediately understand its intent.
  • Resilient Automation: Natural language assertions are far more resilient to minor frontend code changes (like changing a class name from .btn-blue to .btn-primary) because the AI interprets the behavior rather than just the code.