json-render-generative-ui

Skill by ara.so — Daily 2026 Skills collection.

aradotso/trending-skillsUpdated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/aradotso/trending-skills --skill json-render-generative-ui

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Installation Guide

How to use json-render-generative-ui on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add json-render-generative-ui
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aradotso/trending-skills --skill json-render-generative-ui

Fetches json-render-generative-ui from aradotso/trending-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/json-render-generative-ui

Restart Cursor to activate json-render-generative-ui. Access via /json-render-generative-ui in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

json-render Generative UI Framework

Skill by ara.so — Daily 2026 Skills collection.

json-render is a Generative UI framework that lets AI generate dynamic interfaces from natural language prompts, constrained to a predefined component catalog. AI outputs JSON; json-render renders it safely and predictably across any platform.

Installation

# React (core)
npm install @json-render/core @json-render/react

# React + shadcn/ui (36 pre-built components)
npm install @json-render/shadcn

# React Native
npm install @json-render/core @json-render/react-native

# Vue
npm install @json-render/core @json-render/vue

# Svelte
npm install @json-render/core @json-render/svelte

# SolidJS
npm install @json-render/core @json-render/solid

# Video (Remotion)
npm install @json-render/core @json-render/remotion

# PDF
npm install @json-render/core @json-render/react-pdf

# Email
npm install @json-render/core @json-render/react-email @react-email/components @react-email/render

# 3D (React Three Fiber)
npm install @json-render/core @json-render/react-three-fiber @react-three/fiber @react-three/drei three

# OG Images / SVG / PNG
npm install @json-render/core @json-render/image

# State management adapters
npm install @json-render/zustand   # or redux, jotai, xstate

# MCP integration (Claude, ChatGPT, Cursor)
npm install @json-render/mcp

# YAML wire format
npm install @json-render/yaml

Core Concepts

Concept Description
Catalog Defines allowed components and actions (the guardrails for AI)
Spec AI-generated JSON describing which components to render and with what props
Registry Maps catalog component names to actual render implementations
Renderer Platform-specific component that takes a spec + registry and renders UI
Actions Named events AI can trigger (e.g. export_report, refresh_data)

Spec Format

The flat spec format uses a root key + elements map:

const spec = {
  root: "card-1",
  elements: {
    "card-1": {
      type: "Card",
      props: { title: "Dashboard" },
      children: ["metric-1", "metric-2", "button-1"],
    },
    "metric-1": {
      type: "Metric",
      props: { label: "Revenue", value: "124000", format: "currency" },
      children: [],
    },
    "metric-2": {
      type: "Metric",
      props: { label: "Growth", value: "0.18", format: "percent" },
      children: [],
    },
    "button-1": {
      type: "Button",
      props: { label: "Export Report", action: "export_report" },
      children: [],
    },
  },
};

Step 1: Define a Catalog

import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/react/schema";
import { z } from "zod";

const catalog = defineCatalog(schema, {
  components: {
    Card: {
      props: z.object({ title: z.string() }),
      description: "A card container with a title",
    },
    Metric: {
      props: z.object({
        label: z.string(),
        value: z.string(),
        format: z.enum(["currency", "percent", "number"]).nullable(),
      }),
      description: "Displays a single metric value with optional formatting",
    },
    Button: {
      props: z.object({
        label: z.string(),
        action: z.string(),
      }),
      description: "Clickable button that triggers an action",
    },
    Stack: {
      props: z.object({
        direction: z.enum(["row", "column"]).default("column"),
        gap: z.number().optional(),
      }),
      description: "Layout container that stacks children",
    },
  },
  actions: {
    export_report: { description: "Export the current dashboard to PDF" },
    refresh_data: { description: "Refresh all metric data" },
    navigate: {
      description: "Navigate to a page",
      payload: z.object({ path: z.string() }),
    },
  },
});

Step 2: Define a Registry (React)

import { defineRegistry, Renderer } from "@json-render/react";

function format(value: string, fmt: string | null): string {
  if (fmt === "currency") return `$${Number(value).toLocaleString()}`;
  if (fmt === "percent") return `${(Number(value) * 100).toFixed(1)}

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.836 reviews
  • K
    Kaira PatelDec 28, 2024

    json-render-generative-ui reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • V
    Valentina ThompsonDec 24, 2024

    json-render-generative-ui has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • C
    Chaitanya PatilDec 16, 2024

    json-render-generative-ui reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • E
    Emma LiuNov 19, 2024

    I recommend json-render-generative-ui for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • H
    Harper BhatiaNov 15, 2024

    json-render-generative-ui fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • P
    Piyush GNov 7, 2024

    I recommend json-render-generative-ui for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • S
    Shikha MishraOct 26, 2024

    Useful defaults in json-render-generative-ui — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • F
    Fatima NasserOct 10, 2024

    Useful defaults in json-render-generative-ui — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • F
    Fatima JacksonOct 6, 2024

    We added json-render-generative-ui from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • L
    Liam RamirezSep 13, 2024

    json-render-generative-ui fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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