paper-slide-deck

Generate professional slide deck images from academic papers and content. Creates comprehensive outlines with style instructions, auto-detects figures from PDFs, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", or "slide deck" for papers.

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Install skill "paper-slide-deck" with this command: npx skills add luwill/research-skills/luwill-research-skills-paper-slide-deck

Paper Slide Deck Generator

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:

  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

Script Reference:

ScriptPurpose
scripts/generate-slides.pyGenerate AI slides via Gemini API (Python)
scripts/merge-to-pptx.tsMerge slides into PowerPoint
scripts/merge-to-pdf.tsMerge slides into PDF
scripts/detect-figures.tsAuto-detect figures/tables in PDF
scripts/extract-figure.tsExtract figure from PDF page (uses PyMuPDF fallback)
scripts/apply-template.tsApply figure container template

Options

OptionDescription
--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-onlyGenerate outline only, skip image generation

Style Gallery

StyleDescriptionBest For
academic-paperClean professional, precise chartsConference talks, thesis defense
blueprint (Default)Technical schematics, grid textureArchitecture, system design
chalkboardBlack chalkboard, colorful chalkEducation, tutorials, classroom
notionSaaS dashboard, card-based layoutsProduct demos, SaaS, B2B
bold-editorialMagazine cover, bold typography, darkProduct launches, keynotes
corporateNavy/gold, structured layoutsInvestor decks, proposals
dark-atmosphericCinematic dark mode, glowing accentsEntertainment, gaming
editorial-infographicMagazine explainers, flat illustrationsTech explainers, research
fantasy-animationGhibli/Disney style, hand-drawnEducational, storytelling
intuition-machineTechnical briefing, bilingual labelsTechnical docs, academic
minimalUltra-clean, maximum whitespaceExecutive briefings, premium
pixel-artRetro 8-bit, chunky pixelsGaming, developer talks
scientificAcademic diagrams, precise labelingBiology, chemistry, medical
sketch-notesHand-drawn, warm & friendlyEducational, tutorials
vector-illustrationFlat vector, retro & cuteCreative, children's content
vintageAged-paper, historical stylingHistorical, heritage, biography
watercolorHand-painted textures, natural warmthLifestyle, wellness, travel

Auto Style Selection

Content SignalsSelected Style
paper, thesis, defense, conference, ieee, acm, icml, neurips, cvpr, acl, aaai, iclracademic-paper
tutorial, learn, education, guide, intro, beginnersketch-notes
classroom, teaching, school, chalkboard, blackboardchalkboard
architecture, system, data, analysis, technicalblueprint
creative, children, kids, cute, illustrationvector-illustration
briefing, bilingual, infographic, conceptintuition-machine
executive, minimal, clean, simple, elegantminimal
saas, product, dashboard, metrics, productivitynotion
investor, quarterly, business, corporate, proposalcorporate
launch, marketing, keynote, bold, impact, magazinebold-editorial
entertainment, music, gaming, creative, atmosphericdark-atmospheric
explainer, journalism, science communicationeditorial-infographic
story, fantasy, animation, magical, whimsicalfantasy-animation
gaming, retro, pixel, developer, nostalgiapixel-art
biology, chemistry, medical, pathway, scientificscientific
history, heritage, vintage, expedition, historicalvintage
lifestyle, wellness, travel, artistic, naturalwatercolor
Defaultblueprint

Layout Gallery

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

Slide-Specific Layouts

LayoutDescriptionBest For
title-heroLarge centered title + subtitleCover slides, section breaks
quote-calloutFeatured quote with attributionTestimonials, key insights
key-statSingle large number as focal pointImpact statistics, metrics
split-screenHalf image, half textFeature highlights, comparisons
icon-gridGrid of icons with labelsFeatures, capabilities, benefits
two-columnsContent in balanced columnsPaired information, dual points
three-columnsContent in three columnsTriple comparisons, categories
image-captionFull-bleed image + text overlayVisual storytelling, emotional
agendaNumbered list with highlightsSession overview, roadmap
bullet-listStructured bullet pointsSimple content, lists

Infographic-Derived Layouts

LayoutDescriptionBest For
linear-progressionSequential flow left-to-rightTimelines, step-by-step
binary-comparisonSide-by-side A vs BBefore/after, pros-cons
comparison-matrixMulti-factor gridFeature comparisons
hierarchical-layersPyramid or stacked levelsPriority, importance
hub-spokeCentral node with radiating itemsConcept maps, ecosystems
bento-gridVaried-size tilesOverview, summary
funnelNarrowing stagesConversion, filtering
dashboardMetrics with charts/numbersKPIs, data display
venn-diagramOverlapping circlesRelationships, intersections
circular-flowContinuous cycleRecurring processes
winding-roadmapCurved path with milestonesJourney, timeline
tree-branchingParent-child hierarchyOrg charts, taxonomies
icebergVisible vs hidden layersSurface vs depth
bridgeGap with connectionProblem-solution

Academic-Specific Layouts

LayoutDescriptionBest For
paper-titleTitle, authors, affiliations, venueConference paper cover
outline-agendaNumbered section list with highlightsTalk structure overview
methods-diagramCentral architecture/pipeline diagramMethods, system design
results-chartChart area + data annotationsQuantitative results
equation-focusCentered equation + variable definitionsMathematical derivations
qualitative-grid2x2 or 3x2 image comparison gridVisual results, ablations
references-listNumbered citation listKey references slide
contributionsNumbered contribution pointsContributions 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:

  1. Extract main topic from content (2-4 words, kebab-case)
  2. 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

  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:
    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

Single AskUserQuestion with all applicable options:

QuestionWhen to Ask
Style variantAlways (3 options + custom)
LanguageOnly 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

  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

Before generating images, ask user to choose generation method:

Use AskUserQuestion with options:

OptionLabelDescription
1Gemini API (Recommended)Official Google API via Python. Requires GOOGLE_API_KEY env var.
2Gemini Web (Browser-based)⚠️ Uses reverse-engineered web API. No API key needed but may break.

Based on selection:

Option 1: Gemini API (Python)

  1. Verify API key: Check GOOGLE_API_KEY or GEMINI_API_KEY environment variable
  2. 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

  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:

    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:

    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:

  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:
      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"
  4. 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

  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

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

FileContent
references/analysis-framework.mdDeep content analysis for presentations
references/outline-template.mdOutline structure and STYLE_INSTRUCTIONS format
references/modification-guide.mdEdit, add, delete slide workflows
references/content-rules.mdContent and style guidelines
references/base-prompt.mdBase prompt for image generation
references/figure-container-template.mdVisual specs for extracted figure containers
references/styles/<style>.mdFull 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):

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

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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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