Paper Slide Deck Generator

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

scripts/

1. Determine this SKILL.md file's directory path as

   SKILL_DIR

2. Script path =

   ${SKILL_DIR}/scripts/<script-name>.ts

3. Replace all

   ${SKILL_DIR}

   in this document with the actual path

scripts/generate-slides.py

scripts/merge-to-pptx.ts

scripts/merge-to-pdf.ts

scripts/detect-figures.ts

scripts/extract-figure.ts

scripts/apply-template.ts

Options

--style <name>

--audience <type>

--lang <code>

--slides <number>

--outline-only

Style Gallery

academic-paper

blueprint

chalkboard

notion

bold-editorial

corporate

dark-atmospheric

editorial-infographic

fantasy-animation

intuition-machine

minimal

pixel-art

scientific

sketch-notes

vector-illustration

vintage

watercolor

Auto Style Selection

academic-paper

sketch-notes

chalkboard

blueprint

vector-illustration

intuition-machine

minimal

notion

corporate

bold-editorial

dark-atmospheric

editorial-infographic

fantasy-animation

pixel-art

scientific

vintage

watercolor

blueprint

Layout Gallery

// LAYOUT

Slide-Specific Layouts

title-hero

quote-callout

key-stat

split-screen

icon-grid

two-columns

three-columns

image-caption

agenda

bullet-list

Infographic-Derived Layouts

linear-progression

binary-comparison

comparison-matrix

hierarchical-layers

hub-spoke

bento-grid

funnel

dashboard

venn-diagram

circular-flow

winding-roadmap

tree-branching

iceberg

bridge

Academic-Specific Layouts

paper-title

outline-agenda

methods-diagram

results-chart

equation-focus

qualitative-grid

references-list

contributions

Layout: <name>

// LAYOUT

Design Philosophy

• 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

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

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

   intro-machine-learning

Conflict Resolution

slide-deck/{topic-slug}/

• Append timestamp:

  {topic-slug}-YYYYMMDD-HHMMSS

• Example:

  intro-ml

  exists →

  intro-ml-20260118-143052

Source Files

source-{slug}.{ext}

• source-article.md

  (main text content)

• source-diagram.png

  (image from conversation)

• source-data.xlsx

  (additional file)

Workflow

Step 1: Analyze Content

1. Save source content (if pasted, save as

   source.md

   )
2. Follow

   references/analysis-framework.md

   for deep content analysis
3. Determine style (use

   --style

   or auto-select from signals)
4. Detect languages (source vs. user preference)
5. Plan slide count (

   --slides

   or dynamic)
6. For academic papers (PDF with figures): Run automatic figure detection:
   bash

   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

1. Generate 3 style variant outlines based on content analysis
2. Follow

   references/outline-template.md

   for structure
3. 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)
4. Save as

   outline-{style}.md

   for each variant

Step 3: User Confirmation

• Copy selected

  outline-{style}.md

  to

  outline.md

• Regenerate in different language if requested
• User may edit

  outline.md

  for fine-tuning

--outline-only

Step 4: Generate Prompts

1. Read

   references/base-prompt.md

2. Combine with style instructions from outline
3. Add slide-specific content
4. 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"
5. Save to

   prompts/

   directory

Step 5: Image Generation Method Selection

Option 1: Gemini API (Python)

1. Verify API key: Check

   GOOGLE_API_KEY

   or

   GEMINI_API_KEY

   environment variable
2. Run generation script:
   bash

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

• 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

• 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

1. 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

2. 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.

3. For each slide, run:
   bash

   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.
4. Proxy support: If user is in restricted network, prepend:
   bash

   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)

1. Parse outline to identify slides with

   Source: extract

2. Create figures directory:

   mkdir -p figures

3. For each extract slide, automatically:
   • Read the Figure number, Page, and Caption from metadata
   • Run figure extraction script:
     bash

     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:
     bash

     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"
4. For slides with

   Source: generate

   (or no IMAGE_SOURCE):
   • Proceed to Step 6 for AI generation

source-paper.pdf

• 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)

extract-figure.ts

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")

apply-template.ts

Step 6: Generate Images

1. Use selected method from Step 5
2. Skip slides already processed in Step 5.5 (those with

   Source: extract

   )
3. Generate session ID:

   slides-{topic-slug}-{timestamp}

4. Generate each remaining slide with same session ID
5. Report progress: "Generated X/N"
6. 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

references/modification-guide.md

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

Image Generation Dependencies

Gemini API (Option 1 - Recommended)

• GOOGLE_API_KEY

  or

  GEMINI_API_KEY

  environment variable
• Python 3.8+ with pip

• google-genai

  package (auto-installed by script)

gemini-3-pro-image-preview

Gemini Web Skill (Option 2)

• 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

• 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

references/outline-template.md

references/modification-guide.md

references/content-rules.md

references/base-prompt.md

references/figure-container-template.md

references/styles/<style>.md

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

1. .paper-skills/paper-slide-deck/EXTEND.md

   (project)

2. ~/.paper-skills/paper-slide-deck/EXTEND.md

   (user)