Compile PromptUI DSL text into type-safe React or Vue components.
npx skills add https://github.com/MartinLilt/promptui --skill promptui
Please help me install this Agent Skill. Skill: promptui Source: https://github.com/MartinLilt/promptui/tree/main/packages/core Command: npx skills add https://github.com/MartinLilt/promptui --skill promptui
This Skill eliminates the risk of LLMs hallucinating invalid UI component names, props, and markup when generating frontend code, ensuring all output is anchored to a validated, predefined component catalog and compiles to type-safe React or Vue components.
Use the promptui skill to build a responsive pricing page with a card layout, plan iteration, and pricing details, then compile it to a typed React component file ready for use in a Vite or Next.js project.
High-intent search queries and answers about installing and using this skill.
Preventing LLMs from hallucinating invalid React and Vue UI components requires anchoring generation to a predefined component catalog using structured DSL text, which ensures type-safe interface generation and eliminates invalid markup.
You can compile a DSL file into a production-ready React or Vue component by using a compiler that transforms validated DSL syntax into executable code, automatically resolving imports and supporting bindings, conditionals, loops, and variants.
Yes, you can use generated UI components with your existing Vite or Next.js project because the compilation process outputs typed React JSX or Vue SFCs with automatic import resolution and type inference, ready for immediate integration.
The best way to generate type-safe frontend code using AI without manual correction is to use a DSL-to-code compilation workflow that enforces strict syntax rules, sub-part relationships, and variant constraints before outputting executable React or Vue files.
Yes, AI-assisted frontend development can work with both React JSX and Vue SFCs by leveraging a multi-target compilation process that takes structured DSL text and outputs production-ready code for either framework with resolved imports.
AI generated frontend code fails to compile due to invalid props and component names because the LLM lacks strict anchoring to a validated catalog, a problem solved by enforcing predefined component use-paths and directive rules via DSL syntax.
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