MCPInstall

lovstudio-image-creator

Generate images via multiple mechanisms. Supports: (1) End-to-end AI generation via Gemini/ZenMux — given a prompt, directly output an image. (2) Code-based rendering — generate HTML/React single-file, render to PNG via Playwright. (3) Prompt engineering — generate optimized prompts for external models (nano-banana-pro, etc.). Trigger words: image, generate image, 生图, render, poster, 海报, banner, card, 卡片

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/lovstudio/skills --skill lovstudio-image-creator
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads lovstudio-image-creator automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Image Creator — Multi-Mechanism Framework

Mechanism Selection

Choose the mechanism based on user intent:

MechanismWhen to UseOutput
end-to-endUser wants AI-generated artwork, photos, illustrationsPNG image
codeUser wants designed layouts (posters, cards, banners) with editable contentHTML file + PNG
promptUser wants a prompt for external model (Midjourney, nano-banana-pro, etc.)Text prompt

If the user doesn't specify, infer from context:

  • "生成一张猫的图片" → end-to-end
  • "做一张活动海报" → code
  • "帮我写一个 Midjourney prompt" → prompt

Mechanism 1: End-to-End (Gemini)

python3 gen_image.py "PROMPT" [-o output.png] [-q low|medium|high] [--ascii]
  • Generates image directly via Gemini 3 Pro (through ZenMux)
  • Requires ZENMUX_API_KEY environment variable
  • First run auto-installs google-genai and Pillow via pip --user (no manual setup)
  • Display result with Read tool after generation

Mechanism 2: Code-Based Rendering

Step 1: Generate HTML

Write a single self-contained HTML file that includes all styles inline. Use:

  • React 19 via CDN (https://cdn.jsdelivr.net/npm/react@19/umd/react.production.min.js)
  • ReactDOM 19 via CDN
  • Tailwind CSS via CDN (https://cdn.tailwindcss.com)
  • Google Fonts via <link> for CJK: Noto Sans SC, Noto Serif SC

Template structure:

<!DOCTYPE html>
<html>
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <script src="https://cdn.jsdelivr.net/npm/react@19/umd/react.production.min.js"></script>
  <script src="https://cdn.jsdelivr.net/npm/react-dom@19/umd/react-dom.production.min.js"></script>
  <script src="https://cdn.tailwindcss.com"></script>
  <link href="https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@300;400;500;700;900&family=Noto+Serif+SC:wght@400;700&display=swap" rel="stylesheet">
  <script>
    tailwind.config = {
      theme: { extend: { /* custom theme */ } }
    }
  </script>
  <style>
    /* Reset & base styles */
    * { margin: 0; padding: 0; box-sizing: border-box; }
    body { width: {{WIDTH}}px; height: {{HEIGHT}}px; overflow: hidden; }
  </style>
</head>
<body>
  <div id="root"></div>
  <script type="text/babel" data-type="module">
    // React component here
    function Poster() {
      return (/* JSX */);
    }
    ReactDOM.createRoot(document.getElementById('root')).render(<Poster />);
  </script>
  <script src="https://cdn.jsdelivr.net/npm/@babel/standalone/babel.min.js"></script>
</body>
</html>

IMPORTANT: Babel standalone script MUST come AFTER the text/babel script block.

Step 2: Render to PNG

python3 scripts/render_to_png.py \
  /path/to/poster.html \
  -o output.png \
  -W 1200 -H 630 \
  --scale 2

Common aspect ratios:

RatioDimensionsUse Case
16:91200×675Social media banner
4:31200×900Presentation
1:11080×1080Instagram post
9:161080×1920Story / mobile poster
3:4900×1200Portrait poster
A4794×1123Print poster (210mm×297mm @96dpi)

Step 3: Display & Iterate

  • Use Read to display the PNG
  • Open with open output.png on macOS
  • User can request edits → modify the HTML → re-render

Mechanism 3: Prompt Engineering

Generate optimized prompts for external models. Include:

  • Positive prompt: subject, style, lighting, quality tags
  • Negative prompt: common defects to avoid

Format output as copyable code block.

Reference Image Support

When user provides a reference image:

  • End-to-end: describe the style/composition in the prompt
  • Code: analyze the layout, colors, typography → replicate in HTML/CSS
  • Prompt: extract style keywords for the external model

Aspect Ratio

Always ask or infer the desired aspect ratio. Map to pixel dimensions using the table above.

FAQ

What does the lovstudio-image-creator skill do?

Generate images via multiple mechanisms. Supports: (1) End-to-end AI generation via Gemini/ZenMux — given a prompt, directly output an image. (2) Code-based rendering — generate HTML/React single-file, render to PNG via Playwright. (3) Prompt engineering — generate optimized prompts for external models (nano-banana-pro, etc.). Trigger words: image, generate image, 生图, render, poster, 海报, banner, card, 卡片

How do I install lovstudio-image-creator?

Run npx skills add https://github.com/lovstudio/skills --skill lovstudio-image-creator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/lovstudio-image-creator/ (personal) or .claude/skills/lovstudio-image-creator/ (project).

Which AI agents can use lovstudio-image-creator?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is lovstudio-image-creator safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains lovstudio-image-creator?

It is published by lovstudio in lovstudio/skills. It has 85 recorded installs.

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