image

vercel-labs/json-render · updated Apr 8, 2026

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$npx skills add https://github.com/vercel-labs/json-render --skill image
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summary

Image renderer that converts JSON specs into SVG and PNG images using Satori.

skill.md

@json-render/image

Image renderer that converts JSON specs into SVG and PNG images using Satori.

Quick Start

import { renderToPng } from "@json-render/image/render";
import type { Spec } from "@json-render/core";

const spec: Spec = {
  root: "frame",
  elements: {
    frame: {
      type: "Frame",
      props: { width: 1200, height: 630, backgroundColor: "#1a1a2e" },
      children: ["heading"],
    },
    heading: {
      type: "Heading",
      props: { text: "Hello World", level: "h1", color: "#ffffff" },
      children: [],
    },
  },
};

const png = await renderToPng(spec, {
  fonts: [{ name: "Inter", data: fontData, weight: 400, style: "normal" }],
});

Using Standard Components

import { defineCatalog } from "@json-render/core";
import { schema, standardComponentDefinitions } from "@json-render/image";

export const imageCatalog = defineCatalog(schema, {
  components: standardComponentDefinitions,
});

Adding Custom Components

import { z } from "zod";

const catalog = defineCatalog(schema, {
  components: {
    ...standardComponentDefinitions,
    Badge: {
      props: z.object({ label: z.string(), color: z.string().nullable() }),
      slots: [],
      description: "A colored badge label",
    },
  },
});

Standard Components

Component Category Description
Frame Root Root container. Defines width, height, background. Must be root.
Box Layout Container with padding, margin, border, absolute positioning
Row Layout Horizontal flex layout
Column Layout Vertical flex layout
Heading Content h1-h4 heading text
Text Content Body text with full styling
Image Content Image from URL
Divider Decorative Horizontal line separator
Spacer Decorative Empty vertical space

Key Exports

Export Purpose
renderToSvg Render spec to SVG string
renderToPng Render spec to PNG buffer (requires @resvg/resvg-js)
schema Image element schema
standardComponents Pre-built component registry
standardComponentDefinitions Catalog definitions for AI prompts

Sub-path Exports

Export Description
@json-render/image Full package: schema, components, render functions
@json-render/image/server Schema and catalog definitions only (no React/Satori)
@json-render/image/catalog Standard component definitions and types
@json-render/image/render Render functions only
how to use image

How to use image 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 development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add image
2

Execute installation command

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

$npx skills add https://github.com/vercel-labs/json-render --skill image

The skills CLI fetches image from GitHub repository vercel-labs/json-render and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/image

Reload or restart Cursor to activate image. Access the skill through slash commands (e.g., /image) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.731 reviews
  • Yusuf Tandon· Dec 28, 2024

    image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Benjamin Perez· Dec 28, 2024

    image reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yusuf Li· Dec 24, 2024

    I recommend image for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Dhruvi Jain· Dec 8, 2024

    image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Oshnikdeep· Nov 27, 2024

    image is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Li Anderson· Nov 27, 2024

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

  • Mei Rahman· Nov 19, 2024

    image is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Arjun Park· Nov 15, 2024

    Solid pick for teams standardizing on skills: image is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Oct 18, 2024

    Keeps context tight: image is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Mei Zhang· Oct 10, 2024

    Keeps context tight: image is the kind of skill you can hand to a new teammate without a long onboarding doc.

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