Transform academic papers and content into professional slide deck images with automatic figure extraction.

Usage

/paper-slide-deck path/to/paper.pdf
/paper-slide-deck path/to/paper.pdf --style academic-paper
/paper-slide-deck path/to/content.md --style sketch-notes
/paper-slide-deck path/to/content.md --audience executives
/paper-slide-deck path/to/content.md --lang zh
/paper-slide-deck path/to/content.md --slides 10
/paper-slide-deck path/to/content.md --outline-only
/paper-slide-deck  # Then paste content

Script Directory

Important: All scripts are located in the scripts/ subdirectory of this skill.

Agent Execution Instructions:

Determine this SKILL.md file's directory path as SKILL_DIR
Script path = ${SKILL_DIR}/scripts/<script-name>.ts
Replace all ${SKILL_DIR} in this document with the actual path

Script Reference:

| scripts/generate-slides.py | Generate AI slides via Gemini API (Python)

| scripts/merge-to-pptx.ts | Merge slides into PowerPoint

| scripts/merge-to-pdf.ts | Merge slides into PDF

| scripts/detect-figures.ts | Auto-detect figures/tables in PDF

| scripts/extract-figure.ts | Extract figure from PDF page (uses PyMuPDF fallback)

| scripts/apply-template.ts | Apply figure container template

Options

| --style <name> | Visual style (see Style Gallery)

| --audience <type> | Target audience: beginners, intermediate, experts, executives, general

| --lang <code> | Output language (en, zh, ja, etc.)

| --slides <number> | Target slide count

| --outline-only | Generate outline only, skip image generation

Style Gallery

| academic-paper | Clean professional, precise charts | Conference talks, thesis defense

| blueprint (Default) | Technical schematics, grid texture | Architecture, system design

| chalkboard | Black chalkboard, colorful chalk | Education, tutorials, classroom

| notion | SaaS dashboard, card-based layouts | Product demos, SaaS, B2B

| bold-editorial | Magazine cover, bold typography, dark | Product launches, keynotes

| corporate | Navy/gold, structured layouts | Investor decks, proposals

| dark-atmospheric | Cinematic dark mode, glowing accents | Entertainment, gaming

| editorial-infographic | Magazine explainers, flat illustrations | Tech explainers, research

| fantasy-animation | Ghibli/Disney style, hand-drawn | Educational, storytelling

| intuition-machine | Technical briefing, bilingual labels | Technical docs, academic

| minimal | Ultra-clean, maximum whitespace | Executive briefings, premium

| pixel-art | Retro 8-bit, chunky pixels | Gaming, developer talks

| scientific | Academic diagrams, precise labeling | Biology, chemistry, medical

| sketch-notes | Hand-drawn, warm & friendly | Educational, tutorials

| vector-illustration | Flat vector, retro & cute | Creative, children's content

| vintage | Aged-paper, historical styling | Historical, heritage, biography

| watercolor | Hand-painted textures, natural warmth | Lifestyle, wellness, travel

Auto Style Selection

| paper, thesis, defense, conference, ieee, acm, icml, neurips, cvpr, acl, aaai, iclr | academic-paper

| tutorial, learn, education, guide, intro, beginner | sketch-notes

| classroom, teaching, school, chalkboard, blackboard | chalkboard

| architecture, system, data, analysis, technical | blueprint

| creative, children, kids, cute, illustration | vector-illustration

| briefing, bilingual, infographic, concept | intuition-machine

| executive, minimal, clean, simple, elegant | minimal

| saas, product, dashboard, metrics, productivity | notion

| investor, quarterly, business, corporate, proposal | corporate

| launch, marketing, keynote, bold, impact, magazine | bold-editorial

| entertainment, music, gaming, creative, atmospheric | dark-atmospheric

| explainer, journalism, science communication | editorial-infographic

| story, fantasy, animation, magical, whimsical | fantasy-animation

| gaming, retro, pixel, developer, nostalgia | pixel-art

| biology, chemistry, medical, pathway, scientific | scientific

| history, heritage, vintage, expedition, historical | vintage

| lifestyle, wellness, travel, artistic, natural | watercolor

| Default | blueprint

Layout Gallery

Optional layout hints for individual slides. Specify in outline's // LAYOUT section.

Slide-Specific Layouts

| title-hero | Large centered title + subtitle | Cover slides, section breaks

| quote-callout | Featured quote with attribution | Testimonials, key insights

| key-stat | Single large number as focal point | Impact statistics, metrics

| split-screen | Half image, half text | Feature highlights, comparisons

| icon-grid | Grid of icons with labels | Features, capabilities, benefits

| two-columns | Content in balanced columns | Paired information, dual points

| three-columns | Content in three columns | Triple comparisons, categories

| image-caption | Full-bleed image + text overlay | Visual storytelling, emotional

| agenda | Numbered list with highlights | Session overview, roadmap

| bullet-list | Structured bullet points | Simple content, lists

Infographic-Derived Layouts

| linear-progression | Sequential flow left-to-right | Timelines, step-by-step

| binary-comparison | Side-by-side A vs B | Before/after, pros-cons

| comparison-matrix | Multi-factor grid | Feature comparisons

| hierarchical-layers | Pyramid or stacked levels | Priority, importance

| hub-spoke | Central node with radiating items | Concept maps, ecosystems

| bento-grid | Varied-size tiles | Overview, summary

| funnel | Narrowing stages | Conversion, filtering

| dashboard | Metrics with charts/numbers | KPIs, data display

| venn-diagram | Overlapping circles | Relationships, intersections

| circular-flow | Continuous cycle | Recurring processes

| winding-roadmap | Curved path with milestones | Journey, timeline

| tree-branching | Parent-child hierarchy | Org charts, taxonomies

| iceberg | Visible vs hidden layers | Surface vs depth

| bridge | Gap with connection | Problem-solution

Academic-Specific Layouts

| paper-title | Title, authors, affiliations, venue | Conference paper cover

| outline-agenda | Numbered section list with highlights | Talk structure overview

| methods-diagram | Central architecture/pipeline diagram | Methods, system design

| results-chart | Chart area + data annotations | Quantitative results

| equation-focus | Centered equation + variable definitions | Mathematical derivations

| qualitative-grid | 2x2 or 3x2 image comparison grid | Visual results, ablations

| references-list | Numbered citation list | Key references slide

| contributions | Numbered contribution points | Contributions summary

Usage: Add Layout: <name> in slide's // LAYOUT section to guide visual composition.

Design Philosophy

This deck is designed for reading and sharing, not live presentation:

Each slide must be self-explanatory without verbal commentary
Structure content for logical flow when scrolling
Include all necessary context within each slide
Optimize for social media sharing and offline reading

File Management

Output Directory

Each session creates an independent directory named by content slug:

slide-deck/{topic-slug}/
├── source-{slug}.{ext}    # Source files (text, images, etc.)
├── outline.md
├── outline-{style}.md     # Style variant outlines
├── prompts/
│   └── 01-slide-cover.md, 02-slide-{slug}.md, ...
├── 01-slide-cover.png, 02-slide-{slug}.png, ...
├── {topic-slug}.pptx
└── {topic-slug}.pdf

Slug Generation:

Extract main topic from content (2-4 words, kebab-case)
Example: "Introduction to Machine Learning" → intro-machine-learning

Conflict Resolution

If slide-deck/{topic-slug}/ already exists:

Append timestamp: {topic-slug}-YYYYMMDD-HHMMSS
Example: intro-ml exists → intro-ml-20260118-143052

Source Files

Copy all sources with naming source-{slug}.{ext}:

source-article.md (main text content)
source-diagram.png (image from conversation)
source-data.xlsx (additional file)

Multiple sources supported: text, images, files from conversation.

Workflow

Step 1: Analyze Content

Save source content (if pasted, save as source.md)
Follow references/analysis-framework.md for deep content analysis
Determine style (use --style or auto-select from signals)
Detect languages (source vs. user preference)
Plan slide count (--slides or dynamic)
For academic papers (PDF with figures): Run automatic figure detection:

npx -y bun ${SKILL_DIR}/scripts/detect-figures.ts --pdf source-paper.pdf --output figures.json

This outputs a JSON file with all detected figures/tables, their page numbers, and captions.

Step 2: Generate Outline Variants

Generate 3 style variant outlines based on content analysis
Follow references/outline-template.md for structure
Auto-populate IMAGE_SOURCE for academic papers:

Read figures.json from Step 1

Map figures to slides using rules in references/analysis-framework.md Section 8
Automatically add // IMAGE_SOURCE blocks to appropriate slides:

Architecture/pipeline figures → Methods slides (Source: extract)

Results tables → Quantitative results slides (Source: extract)
Comparison images → Qualitative results slides (Source: extract)
Conceptual/simple diagrams → Leave for AI generation (Source: generate or omit)
Save as outline-{style}.md for each variant

Step 3: User Confirmation

Single AskUserQuestion with all applicable options:

| Style variant | Always (3 options + custom)

| Language | Only if source ≠ user language

After selection:

Copy selected outline-{style}.md to outline.md
Regenerate in different language if requested
User may edit outline.md for fine-tuning

If --outline-only, stop here.

Step 4: Generate Prompts

Read references/base-prompt.md
Combine with style instructions from outline
Add slide-specific content
If Layout: specified in outline, include layout guidance in prompt:

Reference layout characteristics for image composition

Example: Layout: hub-spoke → "Central concept in middle with related items radiating outward"
Save to prompts/ directory

Step 5: Image Generation Method Selection

Before generating images, ask user to choose generation method:

Use AskUserQuestion with options:

| 1 | Gemini API (Recommended) | Official Google API via Python. Requires GOOGLE_API_KEY env var.

| 2 | Gemini Web (Browser-based) | ⚠️ Uses reverse-engineered web API. No API key needed but may break.

Based on selection:

Option 1: Gemini API (Python)

Verify API key: Check GOOGLE_API_KEY or GEMINI_API_KEY environment variable
Run generation script:

python ${SKILL_DIR}/scripts/generate-slides.py <slide-deck-dir> --model gemini-3-pro-image-preview

Script Features:

Auto-installs google-genai package if missing
Retry logic with exponential backoff (3 retries)
Skips already-generated slides (> 10KB)
Supports custom model via --model flag
Outputs to slides/ subdirectory

Troubleshooting:

If server disconnection errors occur, script auto-retries
For persistent failures, re-run the script (it skips completed slides)
Check API quota if many failures occur

Option 2: Gemini Web Skill

Consent Check: Read consent file at:

Windows: $APPDATA/baoyu-skills/gemini-web/consent.json

macOS: ~/Library/Application Support/baoyu-skills/gemini-web/consent.json
Linux: ~/.local/share/baoyu-skills/gemini-web/consent.json
If no consent or version mismatch, display disclaimer and ask:

⚠️ DISCLAIMER: This uses a reverse-engineered Gemini Web API (NOT official).
Risks: May break anytime, no support, possible account risk.

For each slide, run:

npx -y bun ${GEMINI_WEB_SKILL_DIR}/scripts/main.ts \
  --promptfiles prompts/01-slide-cover.md \
  --image 01-slide-cover.png \
  --sessionId slides-{topic-slug}-{timestamp}

Where GEMINI_WEB_SKILL_DIR = path to baoyu-danger-gemini-web skill directory.

Proxy support: If user is in restricted network, prepend:

HTTP_PROXY=http://127.0.0.1:7890 HTTPS_PROXY=http://127.0.0.1:7890

Step 5.5: Process IMAGE_SOURCE (Automatic Figure Extraction)

For academic presentations, IMAGE_SOURCE metadata was auto-populated in Step 2 based on figure detection from Step 1.

Automatic Execution:

Parse outline to identify slides with Source: extract
Create figures directory: mkdir -p figures
For each extract slide, automatically:

Read the Figure number, Page, and Caption from metadata

Run figure extraction script:

npx -y bun ${SKILL_DIR}/scripts/extract-figure.ts \
  --pdf source-paper.pdf \
  --page <page-number> \
  --output figures/figure-<N>.png

Run template application script:

npx -y bun ${SKILL_DIR}/scripts/apply-template.ts \
  --figure figures/figure-<N>.png \
  --title "<slide-headline>" \
  --caption "Figure <N>: <caption-text>" \
  --output <NN>-slide-<slug>.png

Report: "Extracted: Figure N → slide NN"
For slides with Source: generate (or no IMAGE_SOURCE):

Proceed to Step 6 for AI generation

Note: Source PDF must be saved as source-paper.pdf in output directory.

Troubleshooting:

If figure detection missed a figure: manually add // IMAGE_SOURCE block to outline
If wrong figure mapped: edit the Figure: and Page: values in outline
If extraction fails: check PDF page number (1-indexed)

PyMuPDF Fallback for Page Extraction: If extract-figure.ts fails with "Image or Canvas expected" error (common with complex PDFs), use PyMuPDF:

import fitz
doc = fitz.open("source-paper.pdf")
page = doc[page_num - 1]  # 0-indexed
mat = fitz.Matrix(3, 3)  # 3x scale for high resolution
pix = page.get_pixmap(matrix=mat)
pix.save(f"extracted/page-{page_num}.png")

Then apply template using apply-template.ts.

Step 6: Generate Images

Use selected method from Step 5
Skip slides already processed in Step 5.5 (those with Source: extract)
Generate session ID: slides-{topic-slug}-{timestamp}
Generate each remaining slide with same session ID
Report progress: "Generated X/N"
Auto-retry once on generation failure

Step 7: Merge to PPTX and PDF

npx -y bun ${SKILL_DIR}/scripts/merge-to-pptx.ts <slide-deck-dir>
npx -y bun ${SKILL_DIR}/scripts/merge-to-pdf.ts <slide-deck-dir>

Step 8: Output Summary

Slide Deck Complete!

Topic: [topic]
Style: [style name]
Location: [directory path]
Slides: N total

- 01-slide-cover.png ✓ Cover
- 02-slide-intro.png ✓ Content
- ...
- {NN}-slide-back-cover.png ✓ Back Cover

Outline: outline.md
PPTX: {topic-slug}.pptx
PDF: {topic-slug}.pdf

Slide Modification

See references/modification-guide.md for:

Edit single slide workflow
Add new slide (with renumbering)
Delete slide (with renumbering)
File naming conventions

Image Generation Dependencies

Gemini API (Option 1 - Recommended)

Requires:

GOOGLE_API_KEY or GEMINI_API_KEY environment variable
Python 3.8+ with pip
google-genai package (auto-installed by script)

Model: gemini-3-pro-image-preview (default)

Gemini Web Skill (Option 2)

Requires:

baoyu-danger-gemini-web skill installed at .claude/skills/baoyu-danger-gemini-web
Google Chrome browser with logged-in Google account
User consent for reverse-engineered API disclaimer

PDF Figure Extraction

Requires:

Primary: pdfjs-dist npm package (use legacy build for Node.js)
Fallback: pymupdf Python package (more reliable for complex PDFs)
canvas npm package for apply-template.ts

References

| references/analysis-framework.md | Deep content analysis for presentations

| references/outline-template.md | Outline structure and STYLE_INSTRUCTIONS format

| references/modification-guide.md | Edit, add, delete slide workflows

| references/content-rules.md | Content and style guidelines

| references/base-prompt.md | Base prompt for image generation

| references/figure-container-template.md | Visual specs for extracted figure containers

| references/styles/<style>.md | Full style specifications

Notes

Image Generation

Nano Banana Pro API: Recommended. Stable, reliable, requires API key
Gemini Web: No API key needed, but uses reverse-engineered API with account risk
Generation time: 10-30 seconds per slide
Auto-retry once on generation failure
Maintain style consistency via session ID

Content Guidelines

Use stylized alternatives for sensitive public figures
Both methods use the same underlying Gemini model for image generation

Extension Support

Custom styles and configurations via EXTEND.md.

Check paths (priority order):

.paper-skills/paper-slide-deck/EXTEND.md (project)
~/.paper-skills/paper-slide-deck/EXTEND.md (user)

If found, load before Step 1. Extension content overrides defaults.

安装

Usage

Script Directory

Options

Style Gallery

Auto Style Selection

Layout Gallery

Slide-Specific Layouts

Infographic-Derived Layouts

Academic-Specific Layouts

Design Philosophy

File Management

Output Directory

Conflict Resolution

Source Files

Workflow

Step 1: Analyze Content

Step 2: Generate Outline Variants

Step 3: User Confirmation

Step 4: Generate Prompts

Step 5: Image Generation Method Selection

Option 1: Gemini API (Python)

Option 2: Gemini Web Skill

Step 5.5: Process IMAGE_SOURCE (Automatic Figure Extraction)

Step 6: Generate Images

Step 7: Merge to PPTX and PDF

Step 8: Output Summary

Slide Modification

Image Generation Dependencies

Gemini API (Option 1 - Recommended)

Gemini Web Skill (Option 2)

PDF Figure Extraction

References

Notes

Image Generation

Content Guidelines

Extension Support