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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.

referencesanalysis-framework.md

≈1.4k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Comic Content Analysis Framework

Deep analysis framework for transforming source content into effective visual storytelling.

Purpose

Before creating a comic, thoroughly analyze the source material to:

  • Identify the target audience and their needs
  • Determine what value the comic will deliver
  • Extract narrative potential for visual storytelling
  • Plan character arcs and key moments

Analysis Dimensions

1. Core Content (Understanding "What")

Central Message

  • What is the single most important idea readers should take away?
  • Can you express it in one sentence?

Key Concepts

  • What are the essential concepts readers must understand?
  • How should these concepts be visualized?
  • Which concepts need simplified explanations?

Content Structure

  • How is the source material organized?
  • What is the natural narrative arc?
  • Where are the climax and turning points?

Evidence & Examples

  • What concrete examples, data, or stories support the main ideas?
  • Which examples translate well to visual panels?
  • What can be shown rather than told?

2. Context & Background (Understanding "Why")

Source Origin

  • Who created this content? What is their perspective?
  • What was the original purpose?
  • Is there bias to be aware of?

Historical/Cultural Context

  • When and where does the story take place?
  • What background knowledge do readers need?
  • What period-specific visual elements are required?

Underlying Assumptions

  • What does the source assume readers already know?
  • What implicit beliefs or values are present?
  • Should the comic challenge or reinforce these?

3. Audience Analysis

Primary Audience

  • Who will read this comic?
  • What is their existing knowledge level?
  • What are their interests and motivations?

Secondary Audiences

  • Who else might benefit from this comic?
  • How might their needs differ?

Reader Questions

  • What questions will readers have?
  • What misconceptions might they bring?
  • What "aha moments" can we create?

4. Value Proposition

Knowledge Value

  • What will readers learn?
  • What new perspectives will they gain?
  • How will this change their understanding?

Emotional Value

  • What emotions should readers feel?
  • What connections will they make with characters?
  • What will make this memorable?

Practical Value

  • Can readers apply what they learn?
  • What actions might this inspire?
  • What conversations might it spark?

5. Narrative Potential

Story Arc Candidates

  • What natural narratives exist in the content?
  • Where is the conflict or tension?
  • What transformations occur?

Character Potential

  • Who are the key figures?
  • What are their motivations and obstacles?
  • How do they change throughout?

Visual Opportunities

  • What scenes have strong visual potential?
  • Where can abstract concepts become concrete images?
  • What metaphors can be visualized?

Dramatic Moments

  • What are the breakthrough/revelation moments?
  • Where are the emotional peaks?
  • What creates tension and release?

6. Adaptation Considerations

What to Keep

  • Essential facts and ideas
  • Key quotes or moments
  • Core emotional beats

What to Simplify

  • Complex explanations
  • Dense technical details
  • Lengthy descriptions

What to Expand

  • Brief mentions that deserve more attention
  • Implied emotions or relationships
  • Visual details not in source

What to Omit

  • Tangential information
  • Redundant examples
  • Content that doesn't serve the narrative

Output Format

Analysis results should be saved to analysis.md with:

  1. YAML Front Matter: Metadata (title, topic, time_span, source_language, user_language, aspect_ratio, recommended_page_count, recommended_art, recommended_tone, recommended_layout)
  2. Target Audience: Primary, secondary, tertiary audiences with their needs
  3. Value Proposition: What readers will gain (knowledge, emotional, practical)
  4. Core Themes: Table with theme, narrative potential, visual opportunity
  5. Key Figures & Story Arcs: Character profiles with arcs, visual identity, key moments
  6. Content Signals: Style and layout recommendations based on content type
  7. Recommended Approaches: Narrative approaches ranked by suitability

YAML Front Matter Example

---
title: "Alan Turing: The Father of Computing"
topic: alan-turing-biography
time_span: 1912-1954
source_language: en
user_language: zh  # From EXTEND.md or detected
aspect_ratio: "3:4"
recommended_page_count: 16
recommended_art: ligne-claire  # ligne-claire|manga|realistic|ink-brush|chalk
recommended_tone: neutral      # neutral|warm|dramatic|romantic|energetic|vintage|action
recommended_layout: mixed      # standard|cinematic|dense|splash|mixed|webtoon
---

Language Fields

Field Description
source_language Detected language of source content
user_language Output language for comic (from EXTEND.md > --lang > source_language)

Analysis Checklist

Before proceeding to storyboard:

  • Can I state the core message in one sentence?
  • Do I know exactly who will read this comic?
  • Have I identified at least 3 ways this comic provides value?
  • Are there clear protagonists with compelling arcs?
  • Have I found at least 5 visually powerful moments?
  • Do I understand what to keep, simplify, expand, and omit?
  • Have I identified the emotional peaks and valleys?

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

    No alerts

  • Snyk17d

    Risk: LOW · No issues

  • Runlayer6mo

    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.