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Paper Slide Deck

CommunityPopular
brycewang-stanford
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.

Overview

Publisherbrycewang-stanford
RepositoryAuto-Empirical-Research-Skills
Skill namepaper-slide-deck
Stars
3.8K
Forks
479
Bundled files
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Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by brycewang-stanford on GitHub. Read the source before you install it.

Installation

Install the Paper Slide Deck AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git /tmp/Auto-Empirical-Research-Skills
mkdir -p .claude/skills
cp -r /tmp/Auto-Empirical-Research-Skills/skills/02-luwill-research-skills/paper-slide-deck .claude/skills/paper-slide-deck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Slide Deck in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Paper Slide Deck on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Paper Slide Deck is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Paper Slide Deck Generator

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

Usage

bash
/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:
    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

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:
    bash
    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:

    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)

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:
      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

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:

python
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

bash
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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Paper Slide Deck AI skill do?

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.

Why use Paper Slide Deck on TypingMind?

Because you install it once and use it with any model. Paper Slide Deck is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Paper Slide Deck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/02-luwill-research-skills/paper-slide-deck. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Paper Slide Deck?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Paper Slide Deck?

As many as you like. As long as a model supports skills, you can use Paper Slide Deck with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Paper Slide Deck AI skill free?

It is published on GitHub by brycewang-stanford. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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