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Vellira’s component generator turns an explicit component description into a planned set of repository files and registrations for React, React Native, or both. It can scaffold far more than an implementation: exports, tests, stories, metadata, documentation plumbing, tokens, registries, and website examples may also be involved. The important boundary is that generation makes repeatable structure predictable; engineers still decide whether the component’s API, semantics, accessibility, and behavior are right.
Vellira describes this workflow in its September 5, 2026 article, “From Scaffold to Production: How Vellira Generates Components”. Its central design question is: what information is known before generation that should deterministically drive every repeatable surface?
1. Describe the component’s intent
The documented entry point is pnpm create:component. Positional inputs identify the component name, platform, layer, and category; options can describe its structural profile and capabilities. The generator is meant to use those declarations to make a plan, rather than infer architecture from a component’s name.
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Depending on the component, the command can also take inputs for control kind, capabilities, public parts, icons, tokens, and token strategy. Options such as --dry-run, --check, and --force govern inspection, freshness checking, and regeneration. The article names these options but does not give a complete command invocation or option-by-option syntax, so consult Vellira’s article for the precise interface before using them.
Why profiles and parts matter
A profile is useful when it expresses reusable structure, not when it simply encodes a component name. Tabs, for example, is a compound component: its declared parts can include Root, List, Trigger, and Content, while its capabilities can identify controlled and uncontrolled state, keyboard behavior, and focus management. That intent can then shape the targets and review evidence.
This is more explicit than asking a generator to guess what a name like “Tabs” implies. The declarations tell the workflow which structures and baseline expectations apply; they do not prove that the resulting interaction design is complete.
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Choosing both means planning separate React and React Native targets, including locations under packages/react/... and packages/react-native/.... The targets share the component’s identity and high-level intent, but they need not share identical implementation details.
That distinction matters because browser and native environments do not have the same presentation or accessibility mechanisms. A web implementation may rely on DOM focus or portals; a native implementation needs behavior appropriate to its platform. The generator’s model allows those differences in implementation, API extensions, tests, styles, accessibility, and interaction instead of treating one implementation as a universal fit.
3. Generate the repository surface
Depending on the profile and target platform, generation may produce or update several kinds of artifacts. The exact set is conditional; not every component receives every surface.
| Surface | What it supports |
|---|---|
| Implementation and public API | Component source, public types, local exports, and package or layer exports. |
| Review and examples | Baseline tests, machine-readable test contracts, and Storybook stories. |
| Documentation and metadata | Component metadata, documentation contracts, registries, and API-documentation targets. |
| Platform and structural files | Platform styles, compound-part directories, tokens, and shared form-control types where applicable. |
| Website surfaces | Generated usage and component examples, accessibility content, API data, playground schema and UI, React and React Native demos, and catalog registration. |
The top-level generator can invoke a website component-page generator, so component creation can reach beyond a package directory into the site’s examples and catalog. This broader output is the reason to think of the operation as a repository contract, not merely a source-file template.
4. Create review evidence from declared intent
The generator derives a test contract from the profile, control kind, effective capabilities, and target platform, then uses that contract to create baseline tests. A Tabs component and an Input component declare different intent, so the tests and expectations should differ as well.
Platform specificity remains important here: browser keyboard requirements should not be copied mechanically into native tests. Generated tests and contracts establish a starting point for review; they do not substitute for tests of the component’s real edge cases or prove that every interaction works correctly.
5. Validate and protect existing work
Generation can modify multiple files and registries, so the workflow’s safety rules are part of its value. Existing targets are rejected by default; --force is the explicit authorization to regenerate them. Before writes, preflight checks can inspect package barrels and registries, profile-and-parts combinations, required Root parts for compound components, requested canonical icons and tokens, and target conflicts.
If a requested resource is missing, the plan should be blocked rather than silently substituting a guess. A dry run validates and reports planned creates and updates without writing. The workflow also describes stable serialization, canonical ordering and duplicate detection, preservation of manually owned tests, and check modes that allow CI to detect stale generated output.
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6. Keep engineering decisions with engineers
Templates are suited to repeatable infrastructure: repository placement, exports and registrations, baseline tests and contracts, starter stories, metadata scaffolding, documentation plumbing, and rules for overwrites and freshness. They can make those surfaces more consistent, but they cannot determine whether a particular component is the right product behavior.
- Engineers still own: product semantics, nuanced API decisions, component-specific accessibility details, complex interactions, visual refinement, and meaningful edge-case tests.
- The generator can scaffold: the repeatable structure and baseline evidence that make those decisions easier to implement and review.
In other words, a generated scaffold is not a completed design or an approval of the API. Treat generated output as a structured starting point: inspect the plan, review the public surface, validate platform behavior, and add tests for the cases that matter to the component.
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