baoyu-article-illustrator

name	baoyu-article-illustrator
description	Analyzes article structure, identifies positions requiring visual aids, generates illustrations with Type × Style two-dimension approach. Use when user asks to "illustrate article", "add images", "generate images for article", or "为文章配图".

Article Illustrator

Analyze articles, identify illustration positions, generate images with Type × Style consistency.

Two Dimensions

Dimension	Controls	Examples
Type	Information structure	infographic, scene, flowchart, comparison, framework, timeline
Style	Visual aesthetics	notion, warm, minimal, blueprint, watercolor, elegant

Combine freely: --type infographic --style blueprint

Types

Type	Best For
infographic	Data, metrics, technical
scene	Narratives, emotional
flowchart	Processes, workflows
comparison	Side-by-side, options
framework	Models, architecture
timeline	History, evolution

Styles

See references/styles.md for Core Styles, full gallery, and Type × Style compatibility.

Workflow

- [ ] Step 1: Pre-check (EXTEND.md, references, config)
- [ ] Step 2: Analyze content
- [ ] Step 3: Confirm settings (AskUserQuestion)
- [ ] Step 4: Generate outline
- [ ] Step 5: Generate images
- [ ] Step 6: Finalize

Step 1: Pre-check

1.5 Load Preferences (EXTEND.md) ⛔ BLOCKING

test -f .baoyu-skills/baoyu-article-illustrator/EXTEND.md && echo "project"
test -f "$HOME/.baoyu-skills/baoyu-article-illustrator/EXTEND.md" && echo "user"

Result	Action
Found	Read, parse, display summary
Not found	⛔ Run first-time-setup

Full procedures: references/workflow.md

Step 2: Analyze

Analysis	Output
Content type	Technical / Tutorial / Methodology / Narrative
Purpose	information / visualization / imagination
Core arguments	2-5 main points
Positions	Where illustrations add value

CRITICAL: Metaphors → visualize underlying concept, NOT literal image.

Full procedures: references/workflow.md

Step 3: Confirm Settings ⚠️

ONE AskUserQuestion, max 4 Qs. Q1-Q3 REQUIRED.

Q	Options
Q1: Type	[Recommended], infographic, scene, flowchart, comparison, framework, timeline, mixed
Q2: Density	minimal (1-2), balanced (3-5), per-section (Recommended), rich (6+)
Q3: Style	[Recommended], minimal-flat, sci-fi, hand-drawn, editorial, scene, Other
Q4: Language	When article language ≠ EXTEND.md setting

Full procedures: references/workflow.md

Step 4: Generate Outline

Save outline.md with frontmatter (type, density, style, image_count) and entries:

## Illustration 1
**Position**: [section/paragraph]
**Purpose**: [why]
**Visual Content**: [what]
**Filename**: 01-infographic-concept-name.png

Full template: references/workflow.md

Step 5: Generate Images

1. Create prompts per references/prompt-construction.md
2. Select generation skill from available skills
3. Process references (direct/style/palette)
4. Apply watermark if EXTEND.md enabled
5. Generate sequentially, retry once on failure

Full procedures: references/workflow.md

Step 6: Finalize

Insert ![description](path/NN-{type}-{slug}.png) after paragraphs.

Article Illustration Complete!
Article: [path] | Type: [type] | Density: [level] | Style: [style]
Images: X/N generated

Output Directory

illustrations/{topic-slug}/
├── source-{slug}.{ext}
├── references/           # if provided
├── outline.md
├── prompts/
└── NN-{type}-{slug}.png

Slug: 2-4 words, kebab-case. Conflict: append -YYYYMMDD-HHMMSS.

Modification

Action	Steps
Edit	Update prompt → Regenerate → Update reference
Add	Position → Prompt → Generate → Update outline → Insert
Delete	Delete files → Remove reference → Update outline

References

File	Content
references/workflow.md	Detailed procedures
references/usage.md	Command syntax
references/styles.md	Style gallery
references/prompt-construction.md	Prompt templates
references/config/first-time-setup.md	First-time setup

🔒 Mandatory Post-Processing (EXIF strip)

After every image generated by this skill — regardless of file extension claimed (.png/.jpg/.webp), regardless of provider (Gemini/OpenAI/DashScope), regardless of whether the user is going to share it — Claude MUST run the post-processing pipeline defined in:

~/.baoyu-skills/image-post-processing.md

Why this is mandatory and unconditional:

• AI providers routinely embed metadata: provider tags, timestamps, color profiles, copyright fingerprints, watermark indicators, C2PA chunks
• Provider-claimed file format (e.g. .png) often disagrees with actual format (e.g. JPEG with PNG extension) — verify and rename
• Local-only files frequently get uploaded later (CDN, R2, screenshots into shared docs, git history) — strip on creation, not before sharing

Required steps for each generated image (in order):

1. Detect actual format with PIL.Image.open(f).format (not the extension)
2. Re-save via PIL with no metadata (this is the EXIF-strip step):

   from PIL import Image
   img = Image.open(path)
   data = list(img.getdata())
   clean = Image.new(img.mode, img.size)
   clean.putdata(data)
   clean.save(target_path, img.format, quality=95, optimize=True)
   

3. If actual format ≠ claimed extension, rename to the correct one and remove the original
4. Verify: re-open the saved file and assert img.getexif() is empty AND img.info has no metadata keys (other than benign jfif/dpi)
5. Only after verification passes may you report the image as done

⚠️ Skipping this step or trusting "the provider doesn't add metadata" is a contract violation. Verify, do not assume.