# Slide Automation > Generate presentation slides from research content (paper, thesis, markdown) using Python (python-pptx), LaTeX Beamer, Marp, or reveal.js. Use when converting written research into presentation decks, automating figure insertion, or creating reproducible slide templates. - Skill: `kinhluan/slide-automation` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add kinhluan/slide-automation` - Raw SKILL.md: https://api.skillmd.com/api/skills/kinhluan/slide-automation/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: kinhluan (https://skillmd.com/u/kinhluan) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/kinhluan/slide-automation --- # Slide Automation **From markdown to deck — reproducible, version-controlled presentations.** This skill automates the creation of research presentations from structured content. It eliminates manual copy-pasting, ensures consistency, and makes slides version-controllable alongside your research. > "Your slides should be as reproducible as your experiments." — Researcher's Maxim --- ## 1. When to Automate Slides ### Use Cases | Scenario | Tool | Output | |---|---|---| | **Paper → Conference talk** | python-pptx | .pptx with figures auto-inserted | | **Thesis → Defense slides** | LaTeX Beamer | .pdf with precise typography | | **Markdown → Quick deck** | Marp | .html or .pdf from markdown | | **Web-based presentation** | reveal.js | Interactive HTML slides | | **Recurring reports** | python-pptx | Template-based monthly updates | ### When NOT to Automate - **One-off, highly designed pitch deck** → Use Keynote/PowerPoint manually - **Creative storytelling presentation** → Manual design for emotional impact - **Rapid iteration with designer** → Figma/Sketch collaboration --- ## 2. Tool Comparison | Tool | Format | Best For | Learning Curve | Collaboration | |---|---|---|---|---| | **python-pptx** | .pptx | Data-heavy, figure-rich talks | Low | Git-friendly | | **LaTeX Beamer** | .pdf | Academic defense, math-heavy | Medium | Git-friendly | | **Marp** | .md → .pdf/.html | Quick markdown-based decks | Very low | Git-friendly | | **reveal.js** | .html | Interactive web presentations | Low | Git-friendly | | **Quarto** | .qmd → multiple | Reproducible research reports | Medium | Git-friendly | --- ## 3. python-pptx: PowerPoint from Python ### 3.1 Basic Structure ```python from pptx import Presentation from pptx.util import Inches, Pt from pptx.dml.color import RgbColor from pptx.enum.text import PP_ALIGN, MSO_ANCHOR # Create presentation prs = Presentation() prs.slide_width = Inches(13.333) # 16:9 prs.slide_height = Inches(7.5) # Add title slide blank_layout = prs.slide_layouts[6] # Blank layout slide = prs.slides.add_slide(blank_layout) # Add title title_box = slide.shapes.add_textbox(Inches(1), Inches(2.5), Inches(11.333), Inches(1.5)) tf = title_box.text_frame tf.text = "Federated Learning for Medical AI" p = tf.paragraphs[0] p.font.size = Pt(44) p.font.bold = True p.font.color.rgb = RgbColor(0x1a, 0x1a, 0x1a) p.alignment = PP_ALIGN.CENTER # Add subtitle sub_box = slide.shapes.add_textbox(Inches(1), Inches(4.2), Inches(11.333), Inches(1)) tf = sub_box.text_frame tf.text = "Privacy-Preserving Collaborative Training" p = tf.paragraphs[0] p.font.size = Pt(24) p.font.color.rgb = RgbColor(0x66, 0x66, 0x66) p.alignment = PP_ALIGN.CENTER # Save prs.save('presentation.pptx') ``` ### 3.2 Research Slide Template ```python from pptx import Presentation from pptx.util import Inches, Pt, Emu from pptx.enum.shapes import MSO_SHAPE from pptx.dml.color import RgbColor class ResearchSlideDeck: """Template for academic/research presentations.""" # Color scheme PRIMARY = RgbColor(0x1a, 0x5f, 0x9e) # Dark blue SECONDARY = RgbColor(0x2e, 0x8b, 0x57) # Green ACCENT = RgbColor(0xe6, 0x8a, 0x00) # Orange DARK = RgbColor(0x1a, 0x1a, 0x1a) # Near black LIGHT = RgbColor(0xf5, 0xf5, 0xf5) # Light gray def __init__(self, title: str, author: str, date: str): self.prs = Presentation() self.prs.slide_width = Inches(13.333) self.prs.slide_height = Inches(7.5) self.title = title self.author = author self.date = date self._add_title_slide() def _add_title_slide(self): """Add title slide with research branding.""" slide = self.prs.slides.add_slide(self.prs.slide_layouts[6]) # Background accent bar shape = slide.shapes.add_shape( MSO_SHAPE.RECTANGLE, Inches(0), Inches(0), Inches(0.3), Inches(7.5) ) shape.fill.solid() shape.fill.fore_color.rgb = self.PRIMARY shape.line.fill.background() # Title title_box = slide.shapes.add_textbox( Inches(1), Inches(2.5), Inches(11), Inches(1.5) ) tf = title_box.text_frame tf.text = self.title p = tf.paragraphs[0] p.font.size = Pt(40) p.font.bold = True p.font.color.rgb = self.DARK # Author and date info_box = slide.shapes.add_textbox( Inches(1), Inches(4.3), Inches(11), Inches(1) ) tf = info_box.text_frame tf.text = f"{self.author}\n{self.date}" p = tf.paragraphs[0] p.font.size = Pt(20) p.font.color.rgb = RgbColor(0x66, 0x66, 0x66) def add_content_slide(self, title: str, bullets: list[str], figure_path: str = None): """Add a content slide with bullets and optional figure.""" slide = self.prs.slides.add_slide(self.prs.slide_layouts[6]) # Title bar title_shape = slide.shapes.add_shape( MSO_SHAPE.RECTANGLE, Inches(0), Inches(0), Inches(13.333), Inches(1) ) title_shape.fill.solid() title_shape.fill.fore_color.rgb = self.PRIMARY title_shape.line.fill.background() # Title text title_box = slide.shapes.add_textbox( Inches(0.5), Inches(0.2), Inches(12), Inches(0.6) ) tf = title_box.text_frame tf.text = title p = tf.paragraphs[0] p.font.size = Pt(28) p.font.bold = True p.font.color.rgb = RgbColor(0xFF, 0xFF, 0xFF) # Content area if figure_path: # Two-column: bullets left, figure right # Bullets content_box = slide.shapes.add_textbox( Inches(0.5), Inches(1.3), Inches(6), Inches(5.5) ) tf = content_box.text_frame tf.word_wrap = True for i, bullet in enumerate(bullets): if i == 0: p = tf.paragraphs[0] else: p = tf.add_paragraph() p.text = f"• {bullet}" p.font.size = Pt(18) p.font.color.rgb = self.DARK p.space_after = Pt(12) # Figure slide.shapes.add_picture( figure_path, Inches(7), Inches(1.3), width=Inches(5.5) ) else: # Full-width bullets content_box = slide.shapes.add_textbox( Inches(0.5), Inches(1.3), Inches(12.333), Inches(5.5) ) tf = content_box.text_frame tf.word_wrap = True for i, bullet in enumerate(bullets): if i == 0: p = tf.paragraphs[0] else: p = tf.add_paragraph() p.text = f"• {bullet}" p.font.size = Pt(20) p.font.color.rgb = self.DARK p.space_after = Pt(14) return slide def add_figure_slide(self, title: str, figure_path: str, caption: str = None): """Add a full-slide figure with caption.""" slide = self.prs.slides.add_slide(self.prs.slide_layouts[6]) # Title title_box = slide.shapes.add_textbox( Inches(0.5), Inches(0.3), Inches(12), Inches(0.6) ) tf = title_box.text_frame tf.text = title p = tf.paragraphs[0] p.font.size = Pt(24) p.font.bold = True p.font.color.rgb = self.DARK # Figure (centered, large) slide.shapes.add_picture( figure_path, Inches(1.5), Inches(1.2), width=Inches(10.333) ) # Caption if caption: cap_box = slide.shapes.add_textbox( Inches(1), Inches(6.5), Inches(11.333), Inches(0.6) ) tf = cap_box.text_frame tf.text = caption p = tf.paragraphs[0] p.font.size = Pt(14) p.font.italic = True p.font.color.rgb = RgbColor(0x66, 0x66, 0x66) p.alignment = PP_ALIGN.CENTER return slide def save(self, filename: str): """Save the presentation.""" self.prs.save(filename) print(f"Saved: {filename}") # Usage example deck = ResearchSlideDeck( title="Federated Learning for Medical AI", author="Nguyen Van A", date="June 2026" ) deck.add_content_slide( title="Research Motivation", bullets=[ "Medical data is siloed across hospitals due to privacy regulations", "Centralized training requires data sharing — prohibited by HIPAA/GDPR", "Federated Learning enables collaborative training without data sharing", "Challenge: Statistical heterogeneity across medical institutions" ] ) deck.add_figure_slide( title="Proposed Architecture", figure_path="figures/fl_architecture.png", caption="Figure 1: Heterogeneous federated learning with personalized aggregation" ) deck.save("defense_presentation.pptx") ``` ### 3.3 Auto-Generate from Markdown ```python import re from pathlib import Path from pptx import Presentation from pptx.util import Inches, Pt def markdown_to_pptx(md_path: str, output_path: str): """Convert markdown research outline to PowerPoint.""" with open(md_path) as f: content = f.read() prs = Presentation() prs.slide_width = Inches(13.333) prs.slide_height = Inches(7.5) # Parse markdown sections sections = re.split(r'\n## ', content) for section in sections[1:]: # Skip title lines = section.strip().split('\n') title = lines[0].strip() # Extract bullets bullets = [] for line in lines[1:]: if line.strip().startswith('- ') or line.strip().startswith('* '): bullets.append(line.strip()[2:]) # Create slide slide = prs.slides.add_slide(prs.slide_layouts[6]) # Add title title_box = slide.shapes.add_textbox( Inches(0.5), Inches(0.5), Inches(12), Inches(0.8) ) tf = title_box.text_frame tf.text = title p = tf.paragraphs[0] p.font.size = Pt(32) p.font.bold = True # Add bullets if bullets: content_box = slide.shapes.add_textbox( Inches(0.5), Inches(1.5), Inches(12), Inches(5) ) tf = content_box.text_frame tf.word_wrap = True for i, bullet in enumerate(bullets[:6]): # Max 6 bullets if i == 0: p = tf.paragraphs[0] else: p = tf.add_paragraph() p.text = f"• {bullet}" p.font.size = Pt(20) p.space_after = Pt(10) prs.save(output_path) print(f"Generated {output_path} with {len(sections)-1} slides") # Usage markdown_to_pptx("research_outline.md", "auto_presentation.pptx") ``` --- ## 4. LaTeX Beamer: Academic Defense ### 4.1 Basic Template ```latex \documentclass[aspectratio=169]{beamer} % Theme \usetheme{Madrid} \usecolortheme{seahorse} \setbeamertemplate{navigation symbols}{} % Colors \definecolor{primary}{RGB}{26, 95, 158} \definecolor{accent}{RGB}{230, 138, 0} \setbeamercolor{title}{fg=primary} \setbeamercolor{frametitle}{fg=primary,bg=white} \setbeamercolor{structure}{fg=primary} % Information \title[Federated Learning]{Federated Learning for Medical AI} \subtitle{Privacy-Preserving Collaborative Training} \author{Nguyen Van A} \institute{Hanoi University of Science and Technology} \date{June 2026} \begin{document} % Title slide \begin{frame} \titlepage \end{frame} % Outline \begin{frame}{Outline} \tableofcontents \end{frame} % Content \section{Introduction} \begin{frame}{Research Motivation} \begin{itemize} \item Medical data is siloed across hospitals \item Privacy regulations prohibit data sharing \item Federated Learning enables collaborative training \item Challenge: Statistical heterogeneity \end{itemize} \end{frame} \section{Methodology} \begin{frame}{Proposed Approach} \begin{columns} \column{0.5\textwidth} \begin{itemize} \item Personalized aggregation \item Adaptive learning rates \item Differential privacy guarantees \end{itemize} \column{0.5\textwidth} \includegraphics[width=\linewidth]{figures/architecture.pdf} \end{columns} \end{frame} \section{Results} \begin{frame}{Experimental Results} \begin{table} \centering \begin{tabular}{lccc} \toprule Method & Accuracy & Rounds & Privacy \\ \midrule FedAvg & 92.1\% & 134 & $\epsilon=8$ \\ FedProx & 93.0\% & 118 & $\epsilon=8$ \\ \textbf{Ours} & \textbf{94.3\%} & \textbf{87} & $\epsilon=4$ \\ \bottomrule \end{tabular} \end{table} \end{frame} \section{Conclusion} \begin{frame}{Conclusion} \begin{block}{Key Contributions} \begin{enumerate} \item Novel aggregation mechanism for heterogeneous data \item Improved convergence with fewer communication rounds \item Stronger privacy guarantees \end{enumerate} \end{block} \end{frame} \begin{frame} \centering \Huge Thank You \vspace{1cm} \normalsize Questions? \end{frame} \end{document} ``` ### 4.2 Compile ```bash # Compile Beamer to PDF pdflatex defense.tex pdflatex defense.tex # Run twice for TOC # Or use latexmk latexmk -pdf defense.tex ``` --- ## 5. Marp: Markdown to Slides ### 5.1 Basic Usage ```markdown --- marp: true theme: default paginate: true backgroundColor: #fff --- # Federated Learning for Medical AI ## Privacy-Preserving Collaborative Training **Nguyen Van A** Hanoi University of Science and Technology June 2026 --- ## Research Motivation - Medical data is siloed across hospitals - Privacy regulations prohibit data sharing - Federated Learning enables collaborative training - **Challenge**: Statistical heterogeneity --- ## Proposed Architecture ![width:800px](figures/architecture.png) *Figure 1: Heterogeneous federated learning system* --- ## Results | Method | Accuracy | Rounds | |--------|----------|--------| | FedAvg | 92.1% | 134 | | FedProx | 93.0% | 118 | | **Ours** | **94.3%** | **87** | --- ## Conclusion 1. Novel aggregation mechanism 2. Improved convergence 3. Stronger privacy guarantees --- # Thank You Questions? ``` ### 5.2 Compile ```bash # Install Marp CLI npm install -g @marp-team/marp-cli # Convert to PDF marp slides.md -o presentation.pdf # Convert to HTML marp slides.md -o presentation.html # Watch mode (auto-rebuild) marp slides.md --watch ``` --- ## 6. reveal.js: Web Presentations ### 6.1 Basic Structure ```html

Federated Learning for Medical AI

Privacy-Preserving Collaborative Training

Nguyen Van A | HUST | June 2026

Research Motivation

  • Medical data is siloed across hospitals
  • Privacy regulations prohibit data sharing
  • Federated Learning enables collaborative training

Results

MethodAccuracyRounds
FedAvg92.1%134
Ours94.3%87

Thank You

Questions?

``` --- ## 7. Integration with AI Figure Generation ``` Research Content (markdown/paper) ↓ [1] Extract figures and concepts ↓ [2] ai-figure-generation → Create conceptual visuals │ • Architecture diagrams │ • Process flows │ • Abstract illustrations ↓ [3] slide-automation → Build slide structure │ • Insert AI-generated figures │ • Add data plots (matplotlib) │ • Format text and layout ↓ [4] Export final deck │ • .pptx for conference │ • .pdf for defense │ • .html for web ↓ Final Presentation ``` ### Combined Workflow Example ```python from ai_figure_generation import generate_diagram_prompt from slide_automation import ResearchSlideDeck import matplotlib.pyplot as plt import numpy as np # Step 1: Generate AI figure prompt = generate_diagram_prompt( concept="federated learning architecture", style="clean vector diagram", components=["5 hospitals", "aggregator", "encrypted gradients"] ) # → Send to DALL-E/Midjourney → Save as 'fl_architecture.png' # Step 2: Create data plot fig, ax = plt.subplots(figsize=(8, 5)) rounds = np.arange(1, 101) ax.plot(rounds, 1 - np.exp(-rounds/30), label='FedAvg', color='gray') ax.plot(rounds, 1 - np.exp(-rounds/20), label='Ours', color='#1a5f9e') ax.set_xlabel('Communication Rounds') ax.set_ylabel('Accuracy') ax.legend() ax.set_title('Convergence Comparison') plt.savefig('convergence_plot.png', dpi=150, bbox_inches='tight') # Step 3: Build presentation deck = ResearchSlideDeck("Federated Learning", "Nguyen Van A", "2026") deck.add_figure_slide("Architecture", "fl_architecture.png") deck.add_figure_slide("Results", "convergence_plot.png", "Faster convergence with proposed method") deck.save("presentation.pptx") ``` --- ## 8. Best Practices ### 8.1 Slide Design Rules | Rule | Why | Implementation | |---|---|---| | **1 idea per slide** | Cognitive load | One title = one takeaway | | **6×6 rule** | Readability | Max 6 bullets, max 6 words each | | **Figure > Table > Text** | Visual processing | Convert tables to charts when possible | | **Consistent branding** | Professionalism | Same colors, fonts, layout throughout | | **Backup slides** | Q&A preparation | 5-10 extra slides after "Thank You" | ### 8.2 Version Control ```bash # Store slides alongside research git add slides/ git commit -m "slides: update results with experiment 042" # Tag versions git tag v1.0-defense git tag v1.1-conference ``` ### 8.3 Reusable Templates ```python # Save template for future use import json template = { "colors": { "primary": "#1a5f9e", "secondary": "#2e8b57", "accent": "#e68a00" }, "fonts": { "title": "Arial Bold", "body": "Arial" }, "layout": { "title_height": 0.8, "content_top": 1.5, "margin": 0.5 } } with open("slide_template.json", "w") as f: json.dump(template, f, indent=2) ``` --- ## Integration with Other Skills | This skill provides | Related skill | For deeper dive | |---|---|---| | Slide structure | `defense-prep` | Defense-specific slide organization | | Figure insertion | `ai-figure-generation` | AI-generated conceptual visuals | | Data plots | `experiment-tracking` | Publication-ready result figures | | Academic tone | `technical-english-cs` | Slide text refinement | | Presentation delivery | `defense-prep` | Q&A preparation, timing | --- ## References - [python-pptx](https://python-pptx.readthedocs.io/) — Python library for PowerPoint - [LaTeX Beamer](https://ctan.org/pkg/beamer) — LaTeX presentation class - [Marp](https://marp.app/) — Markdown presentation ecosystem - [reveal.js](https://revealjs.com/) — HTML presentation framework - [Quarto](https://quarto.org/) — Reproducible research publishing - [ai-figure-generation](./ai-figure-generation/SKILL.md) — AI-generated figures