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Juju Content Illustrations

Community
dososo
juju-content-illustrations

Use this skill when the user wants to turn an article, lesson, product note, retrospective, method, or abstract idea into JUJU-style hand-drawn visual method images. It analyzes the content, asks for the output ratio, decides whether to create one image or a series, writes image-generation prompts, and calls the available image-generation tool when possible.

Overview

Publisherdososo
Repositoryjuju-content-illustrations
Skill namejuju-content-illustrations
Stars
93
Forks
6
Bundled files
20
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 20 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by dososo on GitHub. Read the source before you install it.

Installation

Install the Juju Content Illustrations AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dososo/juju-content-illustrations/tree/main/juju-content-illustrations
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dososo/juju-content-illustrations.git /tmp/juju-content-illustrations
mkdir -p .claude/skills
cp -r /tmp/juju-content-illustrations/juju-content-illustrations .claude/skills/juju-content-illustrations
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Juju Content Illustrations in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Juju Content Illustrations on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Juju Content Illustrations is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Juju Organizing Lab: Content Illustration Skill

JUJU turns content into hand-drawn visual method images featuring Juju, a white bichon organizer.

The output should feel like a small paper world where a problem becomes easier to enter. Do not make generic cute dog art, pet portraits, slide templates, dashboards, or copied example layouts.

First Interaction

When the user only says something like:

text
调用卷卷整理研究所 Skill 帮我生图
帮我把内容生成卷卷内容插画
生成 卷卷整理研究所风格图
Use the juju-content-illustrations skill to make images
Turn this into a Juju-style image

Ask:

text
这次需要做什么?请把你的文章或内容复制给我。

After the user provides content, ask:

text
请选择图片比例 / 平台:

1. 16:9,1600 x 900:X 正文图、公众号头图、公众号正文图、技术复盘图
2. 5:2,1600 x 640:X 封面图、X 长文入口图
3. 3:4,1200 x 1600:小红书正文方法卡、收藏卡、课程型套图
4. 1:1,1200 x 1200:社媒方图
5. 4:5,1440 x 1800:社媒竖图、封面
6. 9:16,1080 x 1920:竖屏封面、故事图

Do not ask the user how many images to generate unless the user explicitly wants manual control. Decide the count from the content.

Core Workflow

  1. Read the content.
  2. Identify the core claim and reader problem.
  3. Decide output type:
    • one image;
    • short series;
    • cover + body cards.
  4. Use no more than 10 images per run.
  5. Choose the parallel world, color mood, image structure, and variation strategy.
  6. Write one prompt per image.
  7. Call the available image-generation tool.
  8. If no image-generation tool is available, output copy-ready prompts and tell the user what tool is missing.
  9. Review the outputs against the QA checklist.

Count Rules

  • Simple opinion or concept: 1 image.
  • Dense article with several linked ideas: 3-6 images.
  • Course or tutorial content: 1 cover + up to 9 body cards.
  • Never create extra images only to fill a quota.
  • Every image in a series must carry a different cognitive action.

Visual Identity

Juju must read as a white bichon dog:

  • black eyes;
  • black nose;
  • clear eye-nose triangle;
  • drooping ears;
  • short legs;
  • small dog proportions;
  • optional orange scarf with small Juju lettering, or a plain orange scarf when text is too small or unstable.

Avoid:

  • sheep-like wool ball;
  • generic fluffy mascot;
  • pet portrait;
  • overly cute healing illustration;
  • character standing idle while the diagram does the work.
  • Chinese, gibberish, or random symbols on Juju's scarf.

Style DNA

Default visual language:

  • white or near-white paper background;
  • light black hand-drawn linework;
  • low-saturation accent colors;
  • visible paper-world props;
  • Chinese labels integrated as handwritten objects;
  • one cognitive action per image;
  • generous whitespace;
  • no slide-template layout.

The recent stable style direction is:

text
paper practice field + small working props + clear Juju action + low-saturation color shifts

The photography composition example in assets/examples/composition-3x4/ is the current public calibration set.

v0.2 adds a variation layer:

  • lighter linework by default;
  • semantic color annotations;
  • more diverse parallel worlds;
  • off-canvas props or gestures only when useful;
  • more varied text placement;
  • stronger anti-repetition rules.
  • more explicit Juju pose and scarf rules.

Parallel Worlds

Choose a parallel world from the content. Examples:

  • paper photography practice field;
  • method desk;
  • route map;
  • small archive room;
  • toolbox and workbench;
  • emotional weather room;
  • retrospective repair shop.
  • broken bridge and gap;
  • island crossing;
  • signal tower;
  • folded-paper city;
  • small experiment field.

Do not reuse an old world as a template. Each new article should invent its own metaphor.

Color Rules

Use restrained color. Color should clarify the action, not decorate the canvas.

  • White or near-white remains dominant.
  • Black linework anchors the image.
  • Low-saturation colors may shift by card.
  • Orange can mark the main path or Juju's scarf; scarf text should be Juju or omitted.
  • Blue can mark loops, water, evidence, or secondary path.
  • Red is only for small correction marks or warnings.
  • Green can mark reusable ideas, saved methods, or growth.
  • Purple-gray can mark ambiguity or unnamed states.

For a series:

  • Use a shared family mood when the article is narrative or reflective.
  • Use controlled color variation when each card teaches a different action.
  • Do not let the color system overpower the paper-line identity.

Prompt Requirements

Each image prompt must include:

  • target ratio and size;
  • title and allowed text;
  • Juju action;
  • Juju pose and scarf rule;
  • cognitive action;
  • metaphor props;
  • color mood;
  • parallel world;
  • variation strategy;
  • line language;
  • semantic annotation colors;
  • text placement;
  • negative constraints.

Every prompt must explicitly say:

text
Juju must look like a white bichon dog, not a sheep or wool ball.
If Juju has scarf text, it must read `Juju`; otherwise keep the scarf plain orange. Do not put Chinese, gibberish, or random marks on the scarf.

Image Tool Handling

Use the image-generation capability available in the current Agent.

If no image tool is available, output copy-ready prompts and say that image generation cannot be executed in the current environment.

Do not pretend an image was generated. If generation fails, say what failed and provide the prompts.

QA Before Delivery

Before delivery, check:

  • Does Juju look like a bichon?
  • Does Juju's scarf read Juju or stay plain, without Chinese or gibberish?
  • Is there one clear cognitive action?
  • Is the text readable?
  • Is the text integrated into the scene?
  • Does the cover differ from body cards?
  • Does each card in a series have a different action?
  • Does the image change enough from old examples in world, props, composition, line language, color, or text placement?
  • Are off-canvas props or gestures used only when they help the content?
  • Is the color restrained?
  • Does the image avoid copying old examples?

If a generated image fails, label the problem and either regenerate or provide a repair prompt.

Useful References

  • references/style-dna.md
  • references/output-formats.md
  • references/workflow.md
  • references/prompt-template.md
  • references/qa-checklist.md
  • references/variation-system.md
  • examples/composition-3x4-suite.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Juju Content Illustrations AI skill do?

Use this skill when the user wants to turn an article, lesson, product note, retrospective, method, or abstract idea into JUJU-style hand-drawn visual method images. It analyzes the content, asks for the output ratio, decides whether to create one image or a series, writes image-generation prompts, and calls the available image-generation tool when possible.

Why use Juju Content Illustrations on TypingMind?

Because you install it once and use it with any model. Juju Content Illustrations is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Juju Content Illustrations in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dososo/juju-content-illustrations/tree/main/juju-content-illustrations. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Juju Content Illustrations?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Juju Content Illustrations?

As many as you like. As long as a model supports skills, you can use Juju Content Illustrations with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Juju Content Illustrations AI skill free?

Yes. It is published on GitHub by dososo under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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