When to configure
Before your first prompt. This is the ideal time. Configuration shapes how Megumi interprets your prompt — a Full coverage depth with Integration scope will produce significantly different output than a Minimal depth with Feature scope from the same prompt. Mid-session. You can change settings and re-prompt at any point. Megumi will adjust its approach based on the new configuration. Useful when you start with a quick smoke pass and then want to go deeper. Per recipe. Each recipe stores its own configuration. You do not need to reconfigure every time you open a recipe — settings persist. If you are unsure what to set, leave the defaults. They work well for most scenarios.Coverage Depth
Controls how comprehensive the generated tests are.
When to use Full: Before a major release, for any flow that handles payment or personal data, or when a feature has a history of regression bugs.
Test Scope
Sets the type of tests Megumi generates.
These are not mutually exclusive — you can run multiple recipes with different scopes on the same feature. A Feature recipe and a Flow recipe for the same checkout module will produce complementary, non-overlapping coverage.
Platform
Sets whether Megumi generates tests for iOS, Android, or both.
If you are testing a feature that behaves differently on each platform — like biometric authentication, file picker behaviour, or notification handling — generate separate recipes per platform rather than using Both.
Priority Levels
Controls which priority tiers Recipe includes in its output.
For a smoke suite, use Critical only. For a regression suite, enable all tiers. For exploratory coverage, start with Critical and High, then add Medium once the core is solid.
Validations
Controls whether Recipe adds assertion steps to generated tests — verifying that the expected outcome actually occurred, not just that the steps ran.
Multiple validation types can be active simultaneously. For most cases, enabling Functional and Visual together produces well-rounded test cases. Add Data when you need to verify specific values, especially in flows involving pricing, counts, or form data.
When validations are off, Recipe generates tests that confirm steps were executed but do not verify the outcome. This is useful for exploratory or navigation-focused tests where you are checking coverage rather than correctness.