Auto-Generated List and Form Screens
Every data object you work with needs at minimum two screens: a list to browse records and a form to create or edit them. Setting those screens up manually — defining columns, wiring data sources, configuring actions, setting up navigation between them — takes time that rarely produces unique value. It's configuration that needs to happen, but it doesn't differentiate your application.
Now when you define a new data object, Swifty generates both screens automatically.
What You Get Immediately
The moment a new object type is defined, two screens are created without any additional steps:
The list screen includes all text and number fields as sortable columns, status fields rendered as colored badges, date fields with appropriate formatting, and pagination. A search bar and basic filters are active by default. A "New" button in the header opens the create form.
The form screen includes all defined fields in their appropriate input types: text inputs, dropdowns for option fields, date pickers, relation selectors, and toggle switches for boolean fields. Validation runs before save. A save button commits changes. A delete button (with confirmation) removes the record.
Navigation Is Wired
The list and form screens are connected automatically. Clicking a record in the list opens its detail/edit form. The form's back navigation returns to the list. If you're creating a record, the form redirects to the new record's detail after save.
You don't configure these links. They're established as part of the scaffolding.
A Starting Point, Not a Ceiling
Auto-generated screens are defaults, not constraints. The builder remains fully available to customize everything the scaffold created. Rearrange the form layout, add custom columns to the list, adjust which fields are visible in each view, add action buttons, introduce sub-panels.
Every generated element is a normal component in the builder. The scaffold just saves you from starting with a blank canvas.
Instant Functional Prototypes
One of the most useful applications of auto-generation is prototyping. Define your data model, and within minutes you have functional screens that let you create real records, test validation, and evaluate the data structure against actual workflows.
The feedback loop between "I defined this object" and "I'm working with real data" compresses to minutes. Changes to the object definition propagate to the screens. Testing an iteration is as fast as saving a definition change.