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Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
SOC 職業分類に基づく
Deterministically query 78 public scientific, biomedical, materials science, regulatory, finance, and demographics databases through documented REST APIs. Use for reproducible lookups of compounds, genes, proteins, pathways, variants, clinical trials, patents, economic indicators, structures, astronomy objects, environmental records, or database-backed scientific facts when endpoints, filters, pagination, and provenance need to be explicit.
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML outside the Transformers library.
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
Complete mass spectrometry analysis platform. Use for proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free and isobaric quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.
Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so the results will actually be interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger this even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistica
| name | scientific-slides |
| description | Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer. |
| allowed-tools | Read Write Edit Bash |
| license | MIT license |
| required_environment_variables | [{"name":"OPENROUTER_API_KEY","prompt":"OpenRouter API key for the skill's LLM-powered steps.","required_for":"optional features"}] |
| metadata | {"version":"1.1","skill-author":"K-Dense Inc.","openclaw":{"primaryEnv":"OPENROUTER_API_KEY","envVars":[{"name":"OPENROUTER_API_KEY","required":false,"description":"OpenRouter API key for the skill's LLM-powered steps."}]}} |
Scientific presentations are a critical medium for communicating research, sharing findings, and engaging with academic and professional audiences. This skill provides comprehensive guidance for creating effective scientific presentations, from structure and content development to visual design and delivery preparation.
Key Focus: Oral presentations for conferences, seminars, defenses, and professional talks.
CRITICAL DESIGN PHILOSOPHY: Scientific presentations should be VISUALLY ENGAGING and RESEARCH-BACKED. Avoid dry, text-heavy slides at all costs. Great scientific presentations combine:
Remember: Boring presentations = forgotten science. Make your slides visually memorable while maintaining scientific rigor through proper citations.
This skill should be used when:
This skill uses Nano Banana Pro AI to generate stunning presentation slides automatically.
There are two workflows depending on output format:
Generate each slide as a complete image using Nano Banana Pro, then combine into a PDF. This produces the most visually stunning results.
How it works:
Step 1: Plan Each Slide
Before generating, create a detailed plan for your presentation:
# Presentation Plan: Introduction to Machine Learning
## Slide 1: Title Slide
- Title: "Machine Learning: From Theory to Practice"
- Subtitle: "AI Conference 2025"
- Speaker: Dr. Jane Smith, University of XYZ
- Visual: Modern abstract neural network background
## Slide 2: Introduction
- Title: "Why Machine Learning Matters"
- Key points: Industry adoption, breakthrough applications, future potential
- Visual: Icons showing different ML applications (healthcare, finance, robotics)
## Slide 3: Core Concepts
- Title: "The Three Types of Learning"
- Content: Supervised, Unsupervised, Reinforcement
- Visual: Three-part diagram showing each type with examples
... (continue for all slides)
Step 2: Generate Each Slide
Use the generate_slide_image.py script to create each slide.
CRITICAL: Formatting Consistency Protocol
To ensure unified formatting across all slides in a presentation:
Define a Formatting Goal at the start of your presentation and include it in EVERY prompt:
Always attach the previous slide when generating subsequent slides using --attach:
Default author is "K-Dense" unless another name is specified
Include citations directly in the prompt for slides that reference research:
Attach existing figures/data for results slides (CRITICAL for data-driven presentations):
figures/, results/, plots/, images/)--attach to include these figures so Nano Banana Pro can incorporate them:
--attach fig1.png --attach fig2.pngExample with formatting consistency, citations, and figure attachments:
# Title slide (first slide - establishes the style)
python scripts/generate_slide_image.py "Title slide for presentation: 'Machine Learning: From Theory to Practice'. Subtitle: 'AI Conference 2025'. Speaker: K-Dense. FORMATTING GOAL: Dark blue background (#1a237e), white text, gold accents (#ffc107), minimal design, sans-serif fonts, generous margins, no decorative elements." -o slides/01_title.png
# Content slide with citations (attach previous slide for consistency)
python scripts/generate_slide_image.py "Presentation slide titled 'Why Machine Learning Matters'. Three key points with simple icons: 1) Industry adoption, 2) Breakthrough applications, 3) Future potential. CITATIONS: Include at bottom in small text: (LeCun et al., 2015; Goodfellow et al., 2016). FORMATTING GOAL: Match attached slide style - dark blue background, white text, gold accents, minimal professional design, no visual clutter." -o slides/02_intro.png --attach slides/01_title.png
# Background slide with multiple citations
python scripts/generate_slide_image.py "Presentation slide titled 'Deep Learning Revolution'. Key milestones: ImageNet breakthrough (2012), transformer architecture (2017), GPT models (2018-present). CITATIONS: Show references at bottom: (Krizhevsky et al., 2012; Vaswani et al., 2017; Brown et al., 2020). FORMATTING GOAL: Match attached slide style exactly - same colors, fonts, minimal design." -o slides/03_background.png --attach slides/02_intro.png
# RESULTS SLIDE - Attach actual data figure from working directory
# First, check what figures exist: ls figures/ or ls results/
python scripts/generate_slide_image.py "Presentation slide titled 'Model Performance Results'. Create a slide presenting the attached accuracy chart. Key findings to highlight: 1) 95% accuracy achieved, 2) Outperforms baseline by 12%, 3) Consistent across test sets. CITATIONS: Include at bottom: (Our results, 2025). FORMATTING GOAL: Match attached slide style exactly." -o slides/04_results.png --attach slides/03_background.png --attach figures/accuracy_chart.png
# RESULTS SLIDE - Multiple figures comparison
python scripts/generate_slide_image.py "Presentation slide titled 'Before vs After Comparison'. Build a side-by-side comparison slide using the two attached figures. Left: baseline results, Right: our improved results. Add brief labels explaining the improvement. FORMATTING GOAL: Match attached slide style exactly." -o slides/05_comparison.png --attach slides/04_results.png --attach figures/baseline.png --attach figures/improved.png
# METHODOLOGY SLIDE - Attach existing diagram
python scripts/generate_slide_image.py "Presentation slide titled 'System Architecture'. Present the attached architecture diagram with brief explanatory bullet points: 1) Input processing, 2) Model inference, 3) Output generation. FORMATTING GOAL: Match attached slide style exactly." -o slides/06_architecture.png --attach slides/05_comparison.png --attach diagrams/system_architecture.png
IMPORTANT: Before creating results slides, always:
ls -la figures/ or ls -la results/Prompt Template:
Include these elements in every prompt (customize as needed):
[Slide content description]
CITATIONS: Include at bottom: (Author1 et al., Year; Author2 et al., Year)
FORMATTING GOAL: [Background color], [text color], [accent color], minimal professional design, no decorative elements, consistent with attached slide style.
Step 3: Combine to PDF
# Combine all slides into a PDF presentation
python scripts/slides_to_pdf.py slides/*.png -o presentation.pdf
When creating PowerPoint presentations, use Nano Banana Pro to generate images and figures for each slide, then add text separately using the PPTX skill.
How it works:
--visual-only flag to create images for slidesStep 1: Generate Visuals for Each Slide
# Generate a figure for the introduction slide
python scripts/generate_slide_image.py "Professional illustration showing machine learning applications: healthcare diagnosis, financial analysis, autonomous vehicles, and robotics. Modern flat design, colorful icons on white background." -o figures/ml_applications.png --visual-only
# Generate a diagram for the methods slide
python scripts/generate_slide_image.py "Neural network architecture diagram showing input layer, three hidden layers, and output layer. Clean, technical style with node connections. Blue and gray color scheme." -o figures/neural_network.png --visual-only
# Generate a conceptual graphic for results
python scripts/generate_slide_image.py "Before and after comparison showing improvement: left side shows cluttered data, right side shows organized insights. Arrow connecting them. Professional business style." -o figures/results_visual.png --visual-only
Step 2: Build PowerPoint with PPTX Skill
Use the PPTX skill's html2pptx workflow to create slides that include:
See skills/pptx/SKILL.md for complete PPTX creation documentation.
Generate presentation slides or visuals using Nano Banana Pro AI.
# Full slide (default) - generates complete slide as image
python scripts/generate_slide_image.py "slide description" -o output.png
# Visual only - generates just the image/figure for embedding in PPT
python scripts/generate_slide_image.py "visual description" -o output.png --visual-only
# With reference images attached (Nano Banana Pro will see these)
python scripts/generate_slide_image.py "Create a slide explaining this chart" -o slide.png --attach chart.png
python scripts/generate_slide_image.py "Combine these into a comparison slide" -o compare.png --attach before.png --attach after.png
Options:
-o, --output: Output file path (required)--attach IMAGE: Attach image file(s) as context for generation (can use multiple times)--visual-only: Generate just the visual/figure, not a complete slide--iterations: Max refinement iterations (default: 2)--api-key: OpenRouter API key (or set OPENROUTER_API_KEY env var)-v, --verbose: Verbose outputAttaching Reference Images:
Use --attach when you want Nano Banana Pro to see existing images as context:
Environment Setup:
export OPENROUTER_API_KEY='your_api_key_here'
# Get key at: https://openrouter.ai/keys
Combine multiple slide images into a single PDF.
# Combine PNG files
python scripts/slides_to_pdf.py slides/*.png -o presentation.pdf
# Combine specific files in order
python scripts/slides_to_pdf.py title.png intro.png methods.png -o talk.pdf
# From directory (sorted by filename)
python scripts/slides_to_pdf.py slides/ -o presentation.pdf
Options:
-o, --output: Output PDF path (required)--dpi: PDF resolution (default: 150)-v, --verbose: Verbose outputTip: Name slides with numbers for correct ordering: 01_title.png, 02_intro.png, etc.
For complete slides, include:
Example prompts:
Title slide:
"Title slide for a medical research presentation. Title: 'Advances in Cancer Immunotherapy'. Subtitle: 'Clinical Trial Results 2024'. Professional medical theme with subtle DNA helix in background. Navy blue and white color scheme."
Content slide:
"Presentation slide titled 'Key Findings'. Three bullet points: 1) 40% improvement in response rate, 2) Reduced side effects, 3) Extended survival outcomes. Include relevant medical icons. Clean, professional design with green and white colors."
Diagram slide:
"Presentation slide showing the research methodology. Title: 'Study Design'. Flowchart showing: Patient Screening → Randomization → Treatment Groups (A, B, Control) → Follow-up → Analysis. CONSORT-style flow diagram. Professional academic style."
For images to embed in PowerPoint, focus on the visual element only:
"Flowchart showing machine learning pipeline: Data Collection → Preprocessing → Model Training → Validation → Deployment. Clean technical style, blue and gray colors."
"Conceptual illustration of cloud computing with servers, data flow, and connected devices. Modern flat design, suitable for business presentation."
"Scientific diagram of cell division process showing mitosis phases. Educational style with labels, colorblind-friendly colors."
In addition to slide generation, use the scientific-schematics skill for technical diagrams:
When to use scientific-schematics instead:
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
Build presentations with clear narrative flow and appropriate structure for different contexts. For detailed guidance, refer to references/presentation_structure.md.
Universal Story Arc:
Talk-Specific Structures:
Create professional, readable, and accessible slides that enhance understanding. For complete design guidelines, refer to references/slide_design_principles.md.
ANTI-PATTERN: Avoid Dry, Text-Heavy Presentations
❌ What Makes Presentations Dry and Forgettable:
✅ What Makes Presentations Engaging and Memorable:
Core Design Principles:
Visual-First Approach (CRITICAL):
Simplicity with Impact:
Typography for Engagement:
Color for Impact:
Layout for Visual Interest:
Adapt scientific figures for presentation context. For detailed guidance, refer to references/data_visualization_slides.md.
Key Differences from Journal Figures:
Visualization Best Practices:
Common Mistakes to Avoid:
Different presentation contexts require different approaches. For comprehensive guidance on each type, refer to references/talk_types_guide.md.
Conference Talks (10-20 minutes):
Academic Seminars (45-60 minutes):
Thesis Defenses (45-60 minutes):
Grant Pitches (10-20 minutes):
Journal Clubs (20-45 minutes):
Best for: Visually stunning slides, fast creation, non-technical audiences
This is the default and recommended approach. Generate each slide as a complete image using AI.
Workflow:
generate_slide_image.pyslides_to_pdf.py# Generate slides
python scripts/generate_slide_image.py "Title: Introduction..." -o slides/01.png
python scripts/generate_slide_image.py "Title: Methods..." -o slides/02.png
# Combine to PDF
python scripts/slides_to_pdf.py slides/*.png -o presentation.pdf
Advantages:
Best for:
Best for: Editable slides, custom designs, template-based workflows
Reference: See skills/pptx/SKILL.md for complete documentation
Use Nano Banana Pro with --visual-only to generate images, then build PPTX with text.
Key Resources:
assets/powerpoint_design_guide.md: Complete PowerPoint design guidehtml2pptx.md: Programmatic creation workflowrearrange.py, inventory.py, replace.py, thumbnail.pyWorkflow:
generate_slide_image.py --visual-onlyAdvantages:
Best for: Mathematical content, consistent formatting, version control
Reference: See references/beamer_guide.md for complete documentation
Templates Available:
assets/beamer_template_conference.tex: 15-minute conference talkassets/beamer_template_seminar.tex: 45-minute academic seminarassets/beamer_template_defense.tex: Dissertation defenseWorkflow:
Advantages:
Implement iterative improvement through visual inspection. For complete workflow, refer to references/visual_review_workflow.md.
Visual Validation Workflow:
Step 1: Generate PDF (if not already PDF)
Step 2: Convert to Images
# Using the pdf_to_images script
python scripts/pdf_to_images.py presentation.pdf review/slide --dpi 150
# Or use pptx skill's thumbnail tool
python skills/pptx/scripts/thumbnail.py presentation.pptx review/thumb
Step 3: Systematic Inspection
Check each slide for:
Step 4: Document Issues
Create issue log:
Slide # | Issue Type | Description | Priority
--------|-----------|-------------|----------
3 | Text overflow | Bullet 4 extends beyond box | High
7 | Overlap | Figure overlaps with caption | High
12 | Font size | Axis labels too small | Medium
Step 5: Apply Fixes
Make corrections to source files:
Step 6: Re-Validate
Repeat Steps 1-5 until no critical issues remain.
Stopping Criteria:
Ensure presentations fit allocated time. For comprehensive timing guidance, refer to assets/timing_guidelines.md.
The One-Slide-Per-Minute Rule:
Time Allocation:
Practice Requirements:
Timing Checkpoints:
For 15-minute talk:
Emergency Strategies:
Automated Validation:
# Validate slide count, timing, file size
python scripts/validate_presentation.py presentation.pdf --duration 15
# Generates report on:
# - Slide count vs. recommended range
# - File size warnings
# - Slide dimensions
# - Font size issues (PowerPoint)
# - Compilation success (Beamer)
Manual Validation Checklist:
Define Context:
Research and Literature Review (Use research-lookup skill):
Develop Content Outline:
Example Outline for 15-Minute Talk:
1. Title (30 sec)
2. Hook: Compelling problem (60 sec) [Cite 1-2 papers via research-lookup]
3. Background (90 sec) [Cite 3-4 key papers establishing context]
4. Research question (45 sec) [Cite papers showing gap]
5. Methods overview (2 min)
6-8. Main result 1 (3 min, 3 slides)
9-10. Main result 2 (2 min, 2 slides)
11-12. Result 3 or validation (2 min, 2 slides)
13-14. Discussion and implications (2 min) [Compare to 2-3 prior studies]
15. Conclusions (45 sec)
16. Acknowledgments (15 sec)
NOTE: Use research-lookup to find papers for background (slides 2-4)
and discussion (slides 13-14) BEFORE creating slides.
Choose Implementation Method:
Option A: PowerPoint (via PPTX skill)
assets/powerpoint_design_guide.mdskills/pptx/SKILL.mdOption B: LaTeX Beamer
references/beamer_guide.mdassets/Design Considerations (Make It Visually Appealing):
Populate Slides (Visual-First Strategy):
VISUAL CONTENT REQUIREMENTS (Make Slides Engaging):
Scientific Content (Research-Backed):
Text Guidelines (Less is More):
Generate Images:
# Convert PDF to images
python scripts/pdf_to_images.py presentation.pdf review/slides
# Or create thumbnail grid
python skills/pptx/scripts/thumbnail.py presentation.pptx review/grid
Systematic Review:
Common Issues to Fix:
Iteration:
Practice Schedule:
What to Practice:
Refinement Based on Practice:
Technical Checks:
Content Final:
Delivery Prep:
Research Lookup (Critical for Scientific Presentations):
Scientific Writing:
PPTX Skill:
Data Visualization:
Dry, Boring Presentations (CRITICAL TO AVOID):
Too Much Content:
Too Much Text:
Missing Research Context:
Poor Narrative:
Rushing Through Results:
Generic, Default Appearance:
Text-Heavy, Visual-Poor:
Small Fonts:
Low Contrast:
Cluttered Slides:
Inconsistent Formatting:
Missing Visual Hierarchy:
Not Practicing:
No Time Checkpoints:
Going Over Time:
Skipping Conclusions:
generate_slide_image.py - Generate slides or visuals with AI:
# Full slide (for PDF workflow)
python scripts/generate_slide_image.py "Title: Introduction\nContent: Key points" -o slide.png
# Visual only (for PPT workflow)
python scripts/generate_slide_image.py "Diagram description" -o figure.png --visual-only
# Options:
# -o, --output Output file path (required)
# --visual-only Generate just the visual, not complete slide
# --iterations N Max refinement iterations (default: 2)
# -v, --verbose Verbose output
slides_to_pdf.py - Combine slide images into PDF:
# From glob pattern
python scripts/slides_to_pdf.py slides/*.png -o presentation.pdf
# From directory (sorted by filename)
python scripts/slides_to_pdf.py slides/ -o presentation.pdf
# Options:
# -o, --output Output PDF path (required)
# --dpi N PDF resolution (default: 150)
# -v, --verbose Verbose output
validate_presentation.py:
python scripts/validate_presentation.py presentation.pdf --duration 15
# Checks:
# - Slide count vs. recommended range
# - File size warnings
# - Slide dimensions
# - Font sizes (PowerPoint)
# - Compilation (Beamer)
pdf_to_images.py:
python scripts/pdf_to_images.py presentation.pdf output/slide --dpi 150
# Converts PDF to images for visual inspection
# Supports: JPG, PNG
# Adjustable DPI
# Page range selection
From skills/pptx/scripts/:
thumbnail.py: Create thumbnail gridsrearrange.py: Duplicate and reorder slidesinventory.py: Extract text contentreplace.py: Update text programmaticallyRecommended:
Comprehensive guides for specific aspects:
references/presentation_structure.md: Detailed structure for all talk types, timing allocation, opening/closing strategies, transition techniquesreferences/slide_design_principles.md: Typography, color theory, layout, accessibility, visual hierarchy, design workflowreferences/data_visualization_slides.md: Simplifying figures, chart types, progressive disclosure, common mistakes, recreation workflowreferences/talk_types_guide.md: Specific guidance for conferences, seminars, defenses, grants, journal clubs, with examplesreferences/beamer_guide.md: Complete LaTeX Beamer documentation, themes, customization, advanced features, compilationreferences/visual_review_workflow.md: PDF to images conversion, systematic inspection, issue documentation, iterative improvementassets/beamer_template_conference.tex: 15-minute conference talk templateassets/beamer_template_seminar.tex: 45-minute academic seminar templateassets/beamer_template_defense.tex: Dissertation defense templateassets/powerpoint_design_guide.md: Complete PowerPoint design and implementation guideassets/timing_guidelines.md: Comprehensive timing, pacing, and practice strategiesResearch & Plan (45 minutes):
Generate Slides with Nano Banana Pro (1-2 hours):
Important: Use consistent formatting, attach previous slides, and include citations!
# Title slide (establishes style - default author: K-Dense)
python scripts/generate_slide_image.py "Title slide: 'Your Research Title'. Conference name, K-Dense. FORMATTING GOAL: [your color scheme], minimal professional design, no decorative elements, clean and corporate." -o slides/01_title.png
# Introduction slide with citations (attach previous for consistency)
python scripts/generate_slide_image.py "Slide titled 'Why This Matters'. Three key points with simple icons. CITATIONS: Include at bottom: (Smith et al., 2023; Jones et al., 2024). FORMATTING GOAL: Match attached slide style exactly." -o slides/02_intro.png --attach slides/01_title.png
# Continue for each slide (always attach previous, include citations where relevant)
python scripts/generate_slide_image.py "Slide titled 'Methods'. Key methodology points. CITATIONS: (Based on Chen et al., 2022). FORMATTING GOAL: Match attached slide style exactly." -o slides/03_methods.png --attach slides/02_intro.png
# Combine to PDF
python scripts/slides_to_pdf.py slides/*.png -o presentation.pdf
Review & Iterate (30 minutes):
Practice (2-3 hours):
Finalize (30 minutes):
Total time: ~5-6 hours for quality AI-generated presentation
If you need editable slides (e.g., for company templates):
--visual-only flag:
python scripts/generate_slide_image.py "diagram description" -o figures/fig1.png --visual-only
See skills/pptx/SKILL.md for complete PowerPoint workflow.
Remember: