Real, runnable examples that ship in the Qontinui repositories
Every example below lives in source control and runs out of the box. The demo workflows are seeded into Qontinui Runner on first launch (or created by a setup script), and the configuration samples demonstrate execution modes for the Python library. Use them to learn the verification-agentic loop and the model-based automation patterns hands-on.
In each demo you define what needs to be true (verification checks — tests, linters, type checkers), and the AI figures out how to make it true. The runner loops the verification and agentic phases until all checks pass.
Three end-to-end demos in the runner repository. Each has a setup phase that creates its workspace, a verification phase that runs a test suite, and an agentic phase where the AI fixes or implements the code.
Demonstrates: The verification-agentic loop on a focused bug fix.
Demonstrates: Building code from a test specification — true test-driven development.
Demonstrates: Validating computed output against expected values across a multi-step pipeline.
Running them: The demos are seeded automatically on the runner's first launch. If they're missing, run the create_demo_workflows.ps1 script in the examples/demo-workflows directory. They require Python and the Claude CLI to be installed.
The runner repository also ships standalone configuration files that demonstrate the library's execution modes and patterns. Each is a complete JSON config you can load directly.
config-mock-mode.jsonRuns a click / wait / type workflow with executionMode set to mock — waits resolve instantly and no real GUI is touched.
config-real-mode.jsonThe same patterns executed against the live GUI through the hardware abstraction layer.
config-screenshot-mode.jsonMatches against captured screenshots rather than the live display for reproducible scene testing.
config-recursive-verify.jsonDemonstrates the verification loop that re-checks state after each action until conditions hold.
config-task-continuation.jsonShows how a multi-step task carries context forward across continuation points.
notepad_automation.jsonA classic visual-automation example driving the Windows Notepad application.
To use Qontinui programmatically, explore the core Python library source. It includes the mock subsystem, the find/action engine, and the state-management model that power every example above.
Python source for the visual automation engine — model, mock, actions, and state management. See the in-repo Python examples and module READMEs.