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/baoyu-comic

@b0ac523 official
by Jim Liu 宝玉jimliu/baoyu-skills26k stars
2,896

Knowledge comic creator supporting multiple art styles and tones. Creates original educational comics with detailed panel layouts and batch-capable image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".

Use this Skill: https://skilld.dev/gh/jimliu/baoyu-skills/baoyu-comic

This session only. Nothing lands on disk.

referencesohmsha-guide.md

≈734 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Ohmsha Manga Guide Style

Guidelines for --style ohmsha educational manga comics.

Character Setup

Role Default Traits
Student (Role A) 大雄 Confused, asks basic but crucial questions, represents reader
Mentor (Role B) 哆啦A梦 Knowledgeable, patient, uses gadgets as technical metaphors
Antagonist (Role C, optional) 胖虎 Represents misunderstanding, or "noise" in the data

Custom characters: --characters "Student:小明,Mentor:教授,Antagonist:Bug怪"

Character Reference Sheet Style

For Ohmsha style, use manga/anime style with:

  • Exaggerated expressions for educational clarity
  • Simple, distinctive silhouettes
  • Bright, saturated color palettes
  • Chibi/SD (super-deformed) variants for comedic reactions

Outline Spec Block

Every ohmsha outline must start with:

【漫画规格单】
- Language: [Same as input content]
- Style: Ohmsha (Manga Guide), Full Color
- Layout: Vertical Scrolling Comic (竖版条漫)
- Characters: [List character names and roles]
- Character Reference: characters/characters.png
- Page Limit: ≤20 pages

Visual Metaphor Rules (Critical)

NEVER create "talking heads" panels. Every technical concept must become:

  1. A tangible gadget/prop - Something characters can hold, use, demonstrate
  2. An action scene - Characters doing something that illustrates the concept
  3. A visual environment - Stepping into a metaphorical space

Examples

Concept Bad (Talking Heads) Good (Visual Metaphor)
Word embeddings Characters discussing vectors 哆啦A梦拿出"词向量压缩机",把书本压缩成彩色小球
Gradient descent Explaining math formula 大雄在山谷地形上滚球,寻找最低点
Neural network Diagram on whiteboard 角色走进由发光节点组成的网络迷宫

Page Title Convention

Avoid AI-style "Title: Subtitle" format. Use narrative descriptions:

  • ❌ "Page 3: Introduction to Neural Networks"
  • ✓ "Page 3: 大雄被海量单词淹没,哆啦A梦拿出'词向量压缩机'"

Ending Requirements

  • NO generic endings ("What will you choose?", "Thanks for reading")
  • End with: Technical summary moment OR character achieving a small goal
  • Final panel: Sense of accomplishment, not open-ended question

Good Endings

  • Student successfully applies learned concept
  • Visual callback to opening problem, now solved
  • Mentor gives summary while student demonstrates understanding

Bad Endings

  • "What do you think?" open questions
  • "Thanks for reading this tutorial"
  • Cliffhanger without resolution

Layout Preference

Ohmsha style typically uses:

  • webtoon (vertical scrolling) - Primary choice
  • dense - For information-heavy sections
  • mixed - For varied pacing

Avoid cinematic and splash for educational content.

Source: SKILL.md on GitHub

1 warning17d5 checks · Risk MEDIUM
  • Gen Agent Trust Hub17d

    This skill is a complex comic creation tool that uses dynamic script execution for PDF merging and environment-aware image generation. It includes logic to discover and run local wrapper scripts by searching directory paths at runtime. While these behaviors are documented as part of its cross-platform support (Codex, Cursor, etc.), the use of dynamic execution from computed paths and the processing of untrusted user content for prompt generation represent notable security surfaces.

  • Socket17d

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  • Snyk17d

    Risk: LOW · No issues

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    2/34 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at b0ac523. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 days ago.

Activeupdated 4 months ago
version
1.117.4
Other metadata
metadata
{
  "openclaw": {
    "homepage": "https://github.com/JimLiu/baoyu-skills#baoyu-comic",
    "requires": {
      "anyBins": [
        "bun",
        "npx"
      ]
    }
  }
}
  • TypeScript
  • comic
  • education
  • knowledge
  • image-generation
  • batch-capable
  • panel-layout
  • art-styles
  • storytelling
  • bun

README badge

README badge for jimliu/baoyu-skills/baoyu-comic

Creates original educational comics with flexible art style and tone combinations, supporting batch image generation and detailed panel layouts. Use when asked to generate knowledge comics, biography comics, tutorial comics, or similar educational visual narratives in styles like ligne-claire, manga, or ink-brush.

Generated from the current SKILL.md.

What art styles and tones does this skill support?
Six art styles (ligne-claire, manga, realistic, ink-brush, chalk, minimalist) and seven tones (neutral, warm, dramatic, romantic, energetic, vintage, action) can be combined. Five named presets (ohmsha, wuxia, shoujo, concept-story, four-panel) bundle specific art+tone combinations with special visual rules.
Can I use my own reference images to guide the comic style?
Yes. Pass reference images via `--ref <files...>` and specify usage mode (direct, style, or palette). Direct mode passes the image to the backend; style and palette modes extract traits and embed them in prompts.
What image backends does this skill work with?
It auto-detects and prioritizes Codex `imagegen`, Cursor `GenerateImage`, or other runtime-native tools. If none are available, it falls back to `baoyu-image-gen` or asks you to choose from installed backends.
Can I regenerate just a few pages instead of the whole comic?
Yes. Use `--regenerate N` to regenerate specific pages (e.g., `--regenerate 3` or `--regenerate 2,5,8`), or `--images-only` to generate images from existing prompts without rebuilding the storyboard.
Does this skill require bun or npm?
It requires either `bun` or `npx` installed. The skill will use `bun` if available; otherwise it falls back to `npx -y bun`.

Generated from the current SKILL.md. These answers refresh after source changes.