{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-aquilalabs-superflex","slug":"superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude","name":"Superflex: AI Frontend Assistant, Figma to React/Vue/NextJS/Angular (Powered by GPT & Claude)","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=aquilalabs.superflex","page_url":"https://unfragile.ai/superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude","categories":["code-editors","deployment-infra"],"tags":["agent","agentic","ai","ai agent","ai assistant","angular","anthropic","blackbox","chat","Claude","cline","code generation","codeium","cody","components","continue","copilot","css","design to code","figma","figma to angular","figma to code","figma to css","figma to html","figma to javascript","figma to nextjs","figma to react","figma to tailwind","figma to typescript","figma to vue","frontend","frontend tools","generate components","GPT","html","image to code","javascript","keybindings","nextjs","openai","react","refactor","screenshot","screenshot to code","sketch","sketch to code","Sonnet","superflex","tailwind","typescript","ui assistant","ui components","vue"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-aquilalabs-superflex__cap_0","uri":"capability://code.generation.editing.figma.design.to.code.transpilation.with.framework.selection","name":"figma design-to-code transpilation with framework selection","description":"Converts Figma design files into production-ready component code by uploading designs directly into the chat interface, then routing the design through Claude or GPT with framework-specific code generation templates. The system preserves design tokens, layout hierarchy, and responsive breakpoints from Figma's design system, outputting clean, reusable components in React, Vue, Next.js, or Angular with proper TypeScript typing and CSS/Tailwind styling.","intents":["I want to convert a Figma mockup into a working React component without manually coding the layout","I need to generate multiple page templates from a design system in Next.js quickly","I want to maintain design consistency when converting Figma specs into Angular components","I need to scaffold a Vue component library from existing Figma designs"],"best_for":["Frontend developers working with design systems in Figma","Teams using design-driven development workflows","Solo developers building MVPs from Figma mockups","Design-to-code automation specialists"],"limitations":["Design system adherence mechanism is undocumented — unclear how design tokens or custom design rules are enforced in generated code","No support for complex Figma interactions, animations, or prototyping logic — only static layout conversion","Limited to React, Vue, Next.js, and Angular; no support for Svelte, Solid, or other frameworks","Styling approach (CSS-in-JS vs Tailwind vs CSS Modules) is not configurable — defaults unknown","No documented support for Figma components with overrides or complex nested structures","Figma file complexity limits unknown — may fail on very large or deeply nested designs"],"requires":["VSCode 1.80+ (minimum version not documented, inferred from extension standards)","Figma design file accessible and uploadable to chat","OpenAI API key or Anthropic API key (authentication mechanism unknown — may use Superflex backend)","Internet connection for design upload and code generation"],"input_types":["Figma design file (upload via chat interface)","Design system context (optional, mechanism unknown)","Framework preference (React/Vue/Next.js/Angular)","Custom styling preferences (undocumented)"],"output_types":["TypeScript/JavaScript component code","CSS or Tailwind utility classes","HTML structure with semantic markup","Responsive layout code with breakpoints"],"categories":["code-generation-editing","design-to-code"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_1","uri":"capability://code.generation.editing.screenshot.and.image.to.code.generation","name":"screenshot and image-to-code generation","description":"Converts UI screenshots, mockups, or hand-drawn sketches into functional component code by uploading images to the chat interface and processing them through vision-capable AI models (Claude or GPT). The system analyzes visual layout, typography, spacing, and color information from the image, then generates corresponding HTML/CSS/JavaScript code with responsive design considerations.","intents":["I have a screenshot of a competitor's UI and want to quickly recreate it as a React component","I want to convert a hand-drawn sketch into a working HTML prototype","I need to generate code from a mobile app screenshot for web adaptation","I want to turn a design mockup image into a Vue component"],"best_for":["Rapid prototyping and MVP development","Developers without design tool access","Teams converting legacy UI screenshots to modern code","Designers who sketch interfaces and want instant code"],"limitations":["Image quality and resolution directly impact code accuracy — low-quality screenshots may produce incorrect layouts","No support for extracting actual design tokens or colors from images — uses visual approximation only","Cannot infer interactive behavior or state management from static images","Hand-drawn sketches require reasonable clarity and structure — abstract or illegible sketches will fail","No built-in image preprocessing or enhancement — user must provide clear, well-lit images","Generated code may require manual refinement for pixel-perfect accuracy"],"requires":["VSCode 1.80+ with Superflex extension installed","Image file (PNG, JPG, WebP) or screenshot capability","OpenAI API key or Anthropic API key","Internet connection for image upload and processing"],"input_types":["PNG, JPG, or WebP image files","Screenshots from any source","Hand-drawn sketches (photographed or scanned)","Design mockup images","Mobile app screenshots"],"output_types":["HTML markup with semantic structure","CSS styling (inline, external, or Tailwind)","JavaScript/TypeScript for interactivity","React/Vue/Angular component code"],"categories":["code-generation-editing","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_10","uri":"capability://code.generation.editing.responsive.design.and.mobile.first.code.generation","name":"responsive design and mobile-first code generation","description":"Generates components with built-in responsive design and mobile-first CSS, automatically including media queries, breakpoints, and mobile-optimized layouts. The system generates code that works across device sizes without requiring manual responsive design implementation. Supports Tailwind responsive utilities and CSS media queries depending on the project's styling approach.","intents":["I want to generate a component that's responsive across mobile, tablet, and desktop","I need a mobile-first component that scales up to larger screens","I want to generate a layout that adapts to different viewport sizes automatically","I need a component with touch-friendly interactions for mobile devices"],"best_for":["Mobile-first development teams","Projects requiring cross-device compatibility","Responsive design systems and component libraries","Teams building progressive web apps"],"limitations":["Responsive design approach is not documented — unclear if mobile-first or desktop-first is default","Breakpoint configuration is not customizable — uses default breakpoints (likely Tailwind defaults)","Touch interactions are not automatically generated — requires manual implementation","No built-in testing for responsive behavior — developers must test across devices manually","Generated media queries may not match project's responsive design strategy","No support for advanced responsive techniques like container queries or aspect-ratio utilities"],"requires":["VSCode 1.80+ with Superflex extension","Tailwind CSS or CSS media query support in project","OpenAI API key or Anthropic API key","Internet connection for code generation"],"input_types":["Component description with responsive requirements","Target breakpoints or device sizes","Mobile-first or desktop-first preference","Styling approach (Tailwind or CSS)"],"output_types":["Responsive component code with media queries","Tailwind responsive utility classes","Mobile-optimized layouts and interactions","Breakpoint-specific styling"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_11","uri":"capability://code.generation.editing.semantic.html.and.accessibility.aware.code.generation","name":"semantic html and accessibility-aware code generation","description":"Generates components with semantic HTML elements (e.g., `<button>` instead of `<div>` with click handlers) and includes accessibility attributes (ARIA labels, roles, keyboard navigation) by default. The system follows WCAG guidelines and best practices for accessible component design, though accessibility compliance is not guaranteed and may require manual refinement.","intents":["I want to generate a component that's accessible to screen reader users","I need a form component with proper labels and ARIA attributes","I want to generate a modal dialog with keyboard navigation support","I need a component that meets WCAG 2.1 AA accessibility standards"],"best_for":["Teams building accessible web applications","Projects with accessibility compliance requirements","Developers prioritizing inclusive design","Public-facing applications requiring WCAG compliance"],"limitations":["Accessibility compliance is not guaranteed — generated code may require manual refinement","ARIA attributes are generated but may not be semantically correct for all use cases","Keyboard navigation is not automatically tested — requires manual testing","Color contrast and visual accessibility are not validated — requires manual review","Complex interactive components may not have complete accessibility support","No built-in accessibility testing or validation tools"],"requires":["VSCode 1.80+ with Superflex extension","OpenAI API key or Anthropic API key","Internet connection for code generation","Manual accessibility testing and refinement"],"input_types":["Component description with accessibility requirements","Target accessibility standards (WCAG 2.1 AA, etc.)","Interactive behavior and keyboard navigation needs"],"output_types":["Semantic HTML markup","ARIA labels and roles","Keyboard navigation code","Accessibility-focused component structure"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_2","uri":"capability://memory.knowledge.codebase.aware.chat.with.file.context.injection","name":"codebase-aware chat with file context injection","description":"Provides a chat interface within VSCode that understands the current project's code structure, allowing developers to ask questions about their codebase and receive context-aware answers. Developers can select code snippets via keyboard shortcut (⌘M) to add them to chat messages, search for specific files using a file picker, and reference project context without manually copying code. The chat maintains conversation history and can answer questions about component usage, architecture patterns, and code relationships.","intents":["I want to ask the AI about how a specific component is used across my project","I need to understand the architecture of an unfamiliar codebase quickly","I want to ask questions about my code without manually copying snippets","I need to find where a function is defined and understand its dependencies"],"best_for":["Developers onboarding to new projects","Teams maintaining large codebases","Solo developers working across multiple projects","Code review and refactoring workflows"],"limitations":["Context window limited by LLM token limits — very large files or many files may be truncated","No automatic codebase indexing — requires manual file selection for context","Cannot access files outside the VSCode workspace or project directory","No semantic code analysis beyond what the LLM can infer from text — may miss implicit dependencies","Conversation history is stored locally but not synced across devices","No built-in code navigation or jump-to-definition integration with VSCode's native features"],"requires":["VSCode 1.80+ with Superflex extension","Project files accessible within VSCode workspace","OpenAI API key or Anthropic API key","Internet connection for chat processing"],"input_types":["Natural language questions","Code snippets (via ⌘M selection)","File references (via file search picker)","Project context (implicit from workspace)"],"output_types":["Natural language explanations","Code examples and suggestions","Architecture diagrams (text-based)","Refactoring recommendations"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_3","uri":"capability://code.generation.editing.smart.component.refactoring.with.style.preservation","name":"smart component refactoring with style preservation","description":"Analyzes existing React, Vue, Next.js, or Angular components and refactors them while maintaining the original coding style, design patterns, and visual appearance. The system detects the component's current style (e.g., CSS-in-JS, Tailwind, CSS Modules), naming conventions, and architectural patterns, then applies refactoring suggestions (e.g., extracting sub-components, improving type safety, optimizing performance) while preserving these conventions. Changes are generated as code suggestions that can be reviewed and applied incrementally.","intents":["I want to refactor a large component into smaller, reusable sub-components without changing its visual appearance","I need to improve TypeScript typing in an existing component while keeping the same style","I want to optimize a component's performance without rewriting it from scratch","I need to modernize an older component to match current project standards"],"best_for":["Teams maintaining legacy component libraries","Developers improving code quality incrementally","Projects with strict style guides and conventions","Refactoring workflows where visual regression is a concern"],"limitations":["Style detection mechanism is undocumented — unclear how accurately it identifies CSS-in-JS vs Tailwind vs CSS Modules","Cannot guarantee zero visual regression — generated code may have subtle layout or spacing differences","Refactoring suggestions are AI-generated and may not align with project-specific patterns or best practices","No automated testing integration — refactored code must be manually tested","Cannot refactor components with complex state management or side effects reliably","Limited to single-file components — multi-file component structures may not be handled correctly"],"requires":["VSCode 1.80+ with Superflex extension","Existing component code in React, Vue, Next.js, or Angular","OpenAI API key or Anthropic API key","Internet connection for refactoring processing"],"input_types":["Component source code (selected via ⌘M or file picker)","Refactoring goals (natural language description)","Style preferences (inferred from existing code)","Framework and tooling context"],"output_types":["Refactored component code","Sub-component suggestions","Type definitions and interfaces","Performance optimization recommendations"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_4","uri":"capability://code.generation.editing.multi.framework.component.generation.from.natural.language","name":"multi-framework component generation from natural language","description":"Generates complete, production-ready components in React, Vue, Next.js, or Angular from natural language descriptions. Developers describe the component's functionality, layout, and behavior in the chat, and the system generates fully typed, styled code with proper error handling and accessibility considerations. The generator supports both simple UI components and complex stateful components with hooks, lifecycle methods, or reactive properties depending on the framework.","intents":["I want to generate a form component with validation without writing boilerplate code","I need a data table component with sorting and filtering for React","I want to create a modal dialog component that works across multiple frameworks","I need a carousel component with keyboard navigation and accessibility features"],"best_for":["Rapid component library development","Teams building design systems","Developers prototyping UI features quickly","Projects requiring consistent components across multiple frameworks"],"limitations":["Generated components may require customization for specific design systems or brand guidelines","Complex state management (Redux, Vuex, NgRx) is not automatically integrated — requires manual setup","Accessibility compliance is not guaranteed — generated code may need ARIA attribute refinement","No built-in testing code generation — developers must write tests manually","Framework-specific best practices may not be followed consistently across all frameworks","Generated code may not match project-specific linting or formatting rules"],"requires":["VSCode 1.80+ with Superflex extension","OpenAI API key or Anthropic API key","Target framework (React, Vue, Next.js, or Angular) installed in project","Internet connection for code generation"],"input_types":["Natural language component description","Component requirements and features","Design specifications (colors, spacing, typography)","Framework preference","Styling approach preference (optional)"],"output_types":["TypeScript/JavaScript component code","CSS, Tailwind, or CSS-in-JS styling","Type definitions and interfaces","Props documentation and examples"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_5","uri":"capability://code.generation.editing.real.time.streaming.code.generation.with.cancellation","name":"real-time streaming code generation with cancellation","description":"Generates code with real-time streaming output, displaying generated code character-by-character as it's produced by the AI model. Developers can cancel generation mid-stream if the output is not meeting expectations, and the partially generated code is retained for editing. This streaming approach reduces perceived latency and allows developers to start reviewing code before generation completes, with support for message editing and regeneration of specific responses.","intents":["I want to see code generation progress in real-time instead of waiting for completion","I need to cancel code generation if it's going in the wrong direction","I want to edit a previous message and regenerate code with different parameters","I need to iterate quickly on code suggestions without waiting for full responses"],"best_for":["Developers with slow internet connections","Iterative development workflows requiring rapid feedback","Teams using expensive API calls where cancellation saves costs","Users who prefer to see generation progress"],"limitations":["Streaming adds network overhead — may not be faster than buffered responses on fast connections","Partial code generation may be syntactically incomplete — requires manual completion or regeneration","Cancellation is not atomic — some tokens may be processed after cancellation request","Message editing and regeneration require re-sending full context, increasing API costs","Streaming performance depends on network latency and LLM response time","No built-in syntax validation during streaming — incomplete code may have errors"],"requires":["VSCode 1.80+ with Superflex v1.0.0+ (streaming added in v1.0.0)","Stable internet connection for streaming","OpenAI API key or Anthropic API key with streaming support","Modern browser/VSCode version supporting WebSocket or streaming HTTP"],"input_types":["Code generation prompts","Context files and snippets","Framework and styling preferences"],"output_types":["Streamed code text (character-by-character)","Partial or complete code blocks","Editable code suggestions"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_6","uri":"capability://memory.knowledge.conversation.history.persistence.and.multi.turn.context.management","name":"conversation history persistence and multi-turn context management","description":"Automatically saves chat conversations within the VSCode extension, allowing developers to resume previous design-to-code or refactoring sessions without losing context. The system maintains conversation state across VSCode sessions, preserving file references, code snippets, and previous generation results. Developers can reference earlier messages in the conversation, and the AI maintains context across multiple turns without requiring manual context re-injection.","intents":["I want to resume a design-to-code session from yesterday without re-uploading the Figma file","I need to reference a component I generated earlier in the conversation","I want to iterate on a refactoring suggestion across multiple turns","I need to maintain context when switching between different components in the same session"],"best_for":["Long-running design-to-code projects","Iterative component development workflows","Teams collaborating on the same codebase","Developers working across multiple VSCode sessions"],"limitations":["Conversation history is stored locally in VSCode — not synced across devices or machines","No built-in conversation export or sharing — history is private to the local VSCode instance","Context window limitations mean very long conversations may lose earlier context","No automatic cleanup or archival — old conversations accumulate in local storage","Conversation history is not encrypted — stored in plaintext in VSCode extension storage","No collaborative conversation support — each developer has separate conversation history"],"requires":["VSCode 1.80+ with Superflex v1.0.0+ (conversation history added in v1.0.0)","Local storage available in VSCode extension directory","OpenAI API key or Anthropic API key"],"input_types":["Chat messages and prompts","Code snippets and file references","Previous generation results"],"output_types":["Persisted conversation history","Context-aware responses referencing previous messages","Conversation metadata (timestamps, file references)"],"categories":["memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_7","uri":"capability://code.generation.editing.design.system.and.coding.style.inference.and.preservation","name":"design system and coding style inference and preservation","description":"Analyzes existing project code to infer design system conventions, coding style, naming patterns, and architectural preferences, then applies these inferred patterns to all generated code. The system detects CSS-in-JS libraries, Tailwind configuration, component naming conventions, TypeScript strictness levels, and code formatting preferences from the project, ensuring generated code matches the project's existing standards without explicit configuration.","intents":["I want generated components to automatically match my project's design system and coding style","I need generated code to follow my team's naming conventions and patterns","I want to ensure TypeScript strictness and type safety match my project settings","I need generated styling to use my project's Tailwind config or CSS-in-JS setup"],"best_for":["Teams with strict coding standards and design systems","Projects with established architectural patterns","Design system maintainers ensuring consistency","Large teams requiring uniform code quality"],"limitations":["Inference mechanism is undocumented — unclear how accurately it detects design systems and style preferences","Cannot infer implicit or undocumented conventions — requires explicit project patterns","Design token extraction from Figma is not documented — unclear if custom tokens are supported","No built-in design system validation — generated code may not perfectly match design tokens","Inference is one-time at generation — does not update if project conventions change","Complex or non-standard project structures may not be inferred correctly"],"requires":["VSCode 1.80+ with Superflex extension","Project with established coding style and design system","Accessible project files for style inference","OpenAI API key or Anthropic API key"],"input_types":["Project source code (for style inference)","Design system files (optional)","Tailwind config or CSS-in-JS setup","TypeScript configuration"],"output_types":["Generated code matching project style","Components using project's design tokens","Code following project's naming conventions","TypeScript types matching project strictness"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_8","uri":"capability://tool.use.integration.keyboard.driven.code.selection.and.context.injection","name":"keyboard-driven code selection and context injection","description":"Provides keyboard shortcuts (⌘M on macOS, equivalent on Windows) to quickly select code snippets from the editor and inject them into chat messages without manual copy-paste. The selected code is automatically formatted and added to the chat context, allowing developers to reference specific code sections in their questions or generation requests. This integrates VSCode's native selection mechanism with the chat interface for seamless context injection.","intents":["I want to ask about a specific code snippet without manually copying it to chat","I need to refactor a selected component without leaving the editor","I want to generate a similar component based on an existing one","I need to ask the AI about a specific function or class definition"],"best_for":["Developers who prefer keyboard-driven workflows","Rapid iteration on code generation and refactoring","Teams using VSCode as primary IDE","Workflows requiring frequent context switching between editor and chat"],"limitations":["Keyboard shortcut (⌘M) may conflict with other VSCode extensions or custom keybindings","Windows keybinding equivalent is not documented — users must configure manually","Selection is limited to visible editor content — cannot select across multiple files","Large selections may exceed LLM context window limits","No syntax highlighting or formatting preview before injection","Selected code is injected as plain text — no semantic understanding of selection"],"requires":["VSCode 1.80+ with Superflex extension","Keyboard shortcut ⌘M (macOS) or configured equivalent (Windows/Linux)","Code selection in VSCode editor","OpenAI API key or Anthropic API key"],"input_types":["Code selection from VSCode editor","Natural language questions or prompts","Additional context or parameters"],"output_types":["Chat message with injected code context","Code suggestions or refactoring recommendations","Generated code based on selected snippet"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-aquilalabs-superflex__cap_9","uri":"capability://search.retrieval.file.search.and.multi.file.context.selection","name":"file search and multi-file context selection","description":"Provides a file picker interface within the chat to search for and select specific project files as context for code generation or refactoring. Developers can search by filename, path, or content, then add selected files to the chat context. This allows referencing multiple files in a single generation request without manually copying code, enabling context-aware generation that understands file relationships and dependencies.","intents":["I want to generate a component that integrates with multiple existing files","I need to understand how a component is used across different files in the project","I want to refactor a component while considering its dependencies in other files","I need to generate code that matches patterns used in similar files"],"best_for":["Large projects with complex file structures","Developers working with interdependent components","Teams maintaining shared component libraries","Refactoring workflows requiring multi-file context"],"limitations":["File search mechanism is undocumented — unclear if it supports regex, fuzzy matching, or content search","Multi-file context may exceed LLM token limits — very large files or many files may be truncated","No automatic dependency resolution — developers must manually select all relevant files","File picker UI is not documented — unclear how to navigate large file trees","No built-in file preview — developers cannot see file contents before adding to context","Context ordering and prioritization is not documented — unclear how multiple files are presented to the LLM"],"requires":["VSCode 1.80+ with Superflex extension","Project files accessible within VSCode workspace","OpenAI API key or Anthropic API key","Internet connection for file processing"],"input_types":["File search query (filename, path, or content)","Selected files from file picker","Natural language prompts or generation requests"],"output_types":["Chat context with selected file contents","Code generation considering multi-file context","Refactoring suggestions based on file relationships"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":46,"verified":false,"data_access_risk":"high","permissions":["VSCode 1.80+ (minimum version not documented, inferred from extension standards)","Figma design file accessible and uploadable to chat","OpenAI API key or Anthropic API key (authentication mechanism unknown — may use Superflex backend)","Internet connection for design upload and code generation","VSCode 1.80+ with Superflex extension installed","Image file (PNG, JPG, WebP) or screenshot capability","OpenAI API key or Anthropic API key","Internet connection for image upload and processing","VSCode 1.80+ with Superflex extension","Tailwind CSS or CSS media query support in project"],"failure_modes":["Design system adherence mechanism is undocumented — unclear how design tokens or custom design rules are enforced in generated code","No support for complex Figma interactions, animations, or prototyping logic — only static layout conversion","Limited to React, Vue, Next.js, and Angular; no support for Svelte, Solid, or other frameworks","Styling approach (CSS-in-JS vs Tailwind vs CSS Modules) is not configurable — defaults unknown","No documented support for Figma components with overrides or complex nested structures","Figma file complexity limits unknown — may fail on very large or deeply nested designs","Image quality and resolution directly impact code accuracy — low-quality screenshots may produce incorrect layouts","No support for extracting actual design tokens or colors from images — uses visual approximation only","Cannot infer interactive behavior or state management from static images","Hand-drawn sketches require reasonable clarity and structure — abstract or illegible sketches will fail","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.48,"quality":0.49,"ecosystem":0.45,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.118Z","last_scraped_at":"2026-05-03T15:20:40.998Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude","compare_url":"https://unfragile.ai/compare?artifact=superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude"}},"signature":"S/ycB4t3XEXJBoBkf5nc8NZYlo2kM6DPWYhQp9FeyujZvrDhsnCCAfy277uV5GXIXMFor+IUY1KzAkJmjKclBw==","signedAt":"2026-06-20T14:08:25.424Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude","artifact":"https://unfragile.ai/superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude","verify":"https://unfragile.ai/api/v1/verify?slug=superflex-ai-frontend-assistant-figma-to-reactvuenextjsangular-powered-by-gpt-claude","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}