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Latex Posters

OrganizationPopular
K-Dense-AI
latex-posters

Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.

Overview

PublisherK-Dense-AI
Repositoryclaude-scientific-writer
Skill namelatex-posters
Stars
2.4K
Forks
273
Bundled files
15
LicenseMIT
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.

  • 15 bundled files

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

  • Open source

    Published by K-Dense-AI on GitHub. Read the source before you install it.

Installation

Install the Latex Posters 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/K-Dense-AI/claude-scientific-writer.git /tmp/claude-scientific-writer
mkdir -p .claude/skills
cp -r /tmp/claude-scientific-writer/skills/latex-posters .claude/skills/latex-posters
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Latex Posters 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 Latex Posters 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 Latex Posters 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.

LaTeX Research Posters

Overview

Research posters are a critical medium for scientific communication at conferences, symposia, and academic events. This skill provides comprehensive guidance for creating professional, visually appealing research posters using LaTeX packages. Generate publication-quality posters with proper layout, typography, color schemes, and visual hierarchy.

When to Use This Skill

This skill should be used when:

  • Creating research posters for conferences, symposia, or poster sessions
  • Designing academic posters for university events or thesis defenses
  • Preparing visual summaries of research for public engagement
  • Converting scientific papers into poster format
  • Creating template posters for research groups or departments
  • Designing posters that comply with specific conference size requirements (A0, A1, 36×48", etc.)
  • Building posters with complex multi-column layouts
  • Integrating figures, tables, equations, and citations in poster format

AI-Powered Visual Element Generation

STANDARD WORKFLOW: Generate ALL major visual elements using AI before creating the LaTeX poster.

This is the recommended approach for creating visually compelling posters:

  1. Plan all visual elements needed (title, intro, methods, results, conclusions)
  2. Generate each element using scientific-schematics or Nano Banana Pro
  3. Assemble generated images in the LaTeX template
  4. Add text content around the visuals

Target: 60-70% of poster area should be AI-generated visuals, 30-40% text.


Hard limits (do not exceed)

These are limits, not guidelines. Violating them is the single most common cause of a failed poster. Full reasoning, per-graphic-type tables, and worked examples are in references/ai_graphics_for_posters.md.

ConstraintLimit
Elements per AI-generated graphic3-4 maximum (3 ideal)
Words per graphic10 maximum
White space per graphic50% minimum (60% better)
Key numbers / metrics120pt+
Labels80pt+
Body text on the poster24pt+
Content sections (A0)5-6 maximum
Total words on the poster300-800
Figure width0.85\linewidth, never 1.0

Every graphic prompt must include: POSTER FORMAT for A0, an explicit element or word count (ONLY 3 icons, 3 words total), a font size (GIANT (120pt+)), 60% white space, and a viewing distance (readable from 10-12 feet).

Two mandatory review gates. Skipping either is how unreadable posters happen:

  • Before generating — for each planned graphic, confirm it is 3-4 items, one message, under 10 words, and not a 5+ stage workflow. If not, split it into several graphics.
  • After generating, before assembly — open each figure at 25% zoom. All text readable, 4 or fewer elements, 50%+ white space, understandable in 2 seconds. Any failure means regenerate or split. Do not assemble a poster from figures that failed.

Patterns that always fail: 7-stage workflow, timeline with annual milestones, 3 case studies in one graphic, comparison of 5+ methods, architecture with all layers. Collapse each to 3 high-level items, or make several separate graphics.

Overflow is an error, not a warning. After compiling, run grep -i overfull poster.log and inspect all four edges at 100% zoom. See references/compilation_and_quality_control.md.

Scientific Schematics Integration

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

Key capabilities:

  • Nano Banana Pro automatically generates, reviews, and refines diagrams
  • Creates publication-quality images with proper formatting
  • Ensures accessibility (colorblind-friendly, high contrast)
  • Supports iterative refinement for complex diagrams

Core Capabilities

Three poster packages are supported — beamerposter (Beamer syntax, institutional themes), tikzposter (modern, colorful, flexible), and baposter (structured multi-column). Package comparison, layout and grid systems, design principles, standard sizes, per-package templates, figure and image integration, color schemes, typography, and QR codes are all documented in references/latex_poster_reference.md.

Reusable per-section content patterns, accessibility requirements, and presentation-day guidance are in references/poster_patterns_and_presentation.md.

Workflow for Poster Creation

Stage 1: Planning and Content Development

  1. Determine poster requirements:

    • Conference size specifications (A0, 36×48", etc.)
    • Orientation (portrait vs. landscape)
    • Submission deadlines and format requirements
  2. Develop content outline:

    • Identify 1-3 core messages
    • Select key figures (typically 3-6 main visuals)
    • Draft concise text for each section (bullet points preferred)
    • Aim for 300-800 words total
  3. Choose LaTeX package:

    • beamerposter: If familiar with Beamer, need institutional themes
    • tikzposter: For modern, colorful designs with flexibility
    • baposter: For structured, professional multi-column layouts

Stage 2: Generate Visual Elements (AI-Powered)

CRITICAL: Generate SIMPLE figures with MINIMAL content. Each graphic = ONE message.

Content limits:

  • Maximum 4-5 elements per graphic
  • Maximum 15 words total per graphic
  • 50% white space minimum
  • GIANT fonts (80pt+ for labels, 120pt+ for key numbers)
  1. Create figures directory:

    bash
    mkdir -p figures
  2. Generate SIMPLE visual elements:

    bash
    # Introduction - ONLY 3 icons/elements
    python scripts/generate_schematic.py "POSTER FORMAT for A0. SIMPLE visual with ONLY 3 elements: [icon1] [icon2] [icon3]. ONE word labels (80pt+). 50% white space. Readable from 8 feet." -o figures/intro.png
    
    # Methods - ONLY 4 steps maximum
    python scripts/generate_schematic.py "POSTER FORMAT for A0. SIMPLE flowchart with ONLY 4 boxes: STEP1 → STEP2 → STEP3 → STEP4. GIANT labels (100pt+). 50% white space. NO sub-steps." -o figures/methods.png
    
    # Results - ONLY 3 bars/comparisons
    python scripts/generate_schematic.py "POSTER FORMAT for A0. SIMPLE chart with ONLY 3 bars. GIANT percentages ON bars (120pt+). NO axis, NO legend. 50% white space." -o figures/results.png
    
    # Conclusions - EXACTLY 3 items with GIANT numbers
    python scripts/generate_schematic.py "POSTER FORMAT for A0. EXACTLY 3 key findings: '[NUMBER]' (150pt) '[LABEL]' (60pt) for each. 50% white space. NO other text." -o figures/conclusions.png
  3. Review generated figures - check for overflow:

    • View at 25% zoom: All text still readable?
    • Count elements: More than 5? → Regenerate simpler
    • Check white space: Less than 40%? → Add "60% white space" to prompt
    • Font too small?: Add "EVEN LARGER" or increase pt sizes
    • Still overflowing?: Reduce to 3 elements instead of 4-5

Stage 3: Design and Layout

  1. Select or create template:

    • Start with provided templates in assets/
    • Customize color scheme to match branding
    • Configure page size and orientation
  2. Design layout structure:

    • Plan column structure (2, 3, or 4 columns)
    • Map content flow (typically left-to-right, top-to-bottom)
    • Allocate space for title (10-15%), content (70-80%), footer (5-10%)
  3. Set typography:

    • Configure font sizes for different hierarchy levels
    • Ensure minimum 24pt body text
    • Test readability from 4-6 feet distance

Stage 4: Content Integration

  1. Create poster header:

    • Title (concise, descriptive, 10-15 words)
    • Authors and affiliations
    • Institution logos (high-resolution)
    • Conference logo if required
  2. Integrate AI-generated figures:

    • Add all figures from Stage 2 to appropriate sections
    • Use \includegraphics with proper sizing
    • Ensure figures dominate each section (visuals first, text second)
    • Center figures within blocks for visual impact
  3. Add minimal supporting text:

    • Keep text minimal and scannable (300-800 words total)
    • Use bullet points, not paragraphs
    • Write in active voice
    • Text should complement figures, not duplicate them
  4. Add supplementary elements:

    • QR codes for supplementary materials
    • References (cite key papers only, 5-10 typical)
    • Contact information and acknowledgments

Stage 5: Refinement and Testing

  1. Review and iterate:

    • Check for typos and errors
    • Verify all figures are high resolution
    • Ensure consistent formatting
    • Confirm color scheme works well together
  2. Test readability:

    • Print at 25% scale and read from 2-3 feet (simulates poster from 8-12 feet)
    • Check color on different monitors
    • Verify QR codes function correctly
    • Ask colleague to review
  3. Optimize for printing:

    • Embed all fonts in PDF
    • Verify image resolution
    • Check PDF size requirements
    • Include bleed area if required

Stage 6: Compilation and Delivery

  1. Compile final PDF:

    bash
    pdflatex poster.tex
    # Or for better font support:
    lualatex poster.tex
  2. Verify output quality:

    • Check all elements are visible and correctly positioned
    • Zoom to 100% and inspect figure quality
    • Verify colors match expectations
    • Confirm PDF opens correctly on different viewers
  3. Prepare for printing:

    • Export as PDF/X-1a if required
    • Save backup copies
    • Get test print on regular paper first
    • Order professional printing 2-3 days before deadline
  4. Create supplementary materials:

    • Save PNG/JPG version for social media
    • Create handout version (8.5×11" summary)
    • Prepare digital version for email sharing

Integration with Other Skills

This skill works effectively with:

  • Scientific Schematics: CRITICAL - Use for generating all poster diagrams and flowcharts
  • Generate Image / Nano Banana Pro: For stylized graphics, conceptual illustrations, and summary visuals
  • Scientific Writing: For developing poster content from papers
  • Literature Review: For contextualizing research
  • Data Analysis: For creating result figures and charts

Recommended workflow: Always use scientific-schematics and generate-image skills BEFORE creating the LaTeX poster to generate all visual elements.

Common Pitfalls to Avoid

AI-Generated Graphics Mistakes (MOST COMMON):

  • ❌ Too many elements in one graphic (10+ items) → Keep to 3-5 max
  • ❌ Text too small in AI graphics → Specify "GIANT (100pt+)" or "HUGE (150pt+)"
  • ❌ Too much detail in prompts → Use "SIMPLE" and "ONLY X elements"
  • ❌ No white space specification → Add "50% white space" to every prompt
  • ❌ Complex flowcharts with 8+ steps → Limit to 4-5 steps maximum
  • ❌ Comparison charts with 6+ items → Limit to 3 items maximum
  • ❌ Key findings with 5+ metrics → Show only top 3

Fixing Overflow in AI Graphics: If your AI-generated graphics are overflowing or have small text:

  1. Add "SIMPLER" or "ONLY 3 elements" to prompt
  2. Increase font sizes: "150pt+" instead of "80pt+"
  3. Add "60% white space" instead of "50%"
  4. Remove sub-details: "NO sub-steps", "NO axis labels", "NO legend"
  5. Regenerate with fewer elements

Design Mistakes:

  • ❌ Too much text (over 1000 words)
  • ❌ Font sizes too small (under 24pt body text)
  • ❌ Low-contrast color combinations
  • ❌ Cluttered layout with no white space
  • ❌ Inconsistent styling across sections
  • ❌ Poor quality or pixelated images

Content Mistakes:

  • ❌ No clear narrative or message
  • ❌ Too many research questions or objectives
  • ❌ Overuse of jargon without definitions
  • ❌ Results without context or interpretation
  • ❌ Missing author contact information

Technical Mistakes:

  • ❌ Wrong poster dimensions for conference requirements
  • ❌ RGB colors sent to CMYK printer (color shift)
  • ❌ Fonts not embedded in PDF
  • ❌ File size too large for submission portal
  • ❌ QR codes too small or not tested

Best Practices:

  • ✅ Generate SIMPLE AI graphics with 3-5 elements max
  • ✅ Use GIANT fonts (100pt+) for key numbers in graphics
  • ✅ Specify "50% white space" in every AI prompt
  • ✅ Follow conference size specifications exactly
  • ✅ Test print at reduced scale before final printing
  • ✅ Use high-contrast, accessible color schemes
  • ✅ Keep text minimal and highly scannable
  • ✅ Include clear contact information and QR codes
  • ✅ Proofread carefully (errors are magnified on posters!)

Package Installation

Ensure required LaTeX packages are installed:

bash
# For TeX Live (Linux/Mac)
tlmgr install beamerposter tikzposter baposter

# For MiKTeX (Windows)
# Packages typically auto-install on first use

# Additional recommended packages
tlmgr install qrcode graphics xcolor tcolorbox subcaption

Scripts and Automation

Helper scripts available in scripts/ directory:

  • review_poster.sh: Poster review and validation
  • generate_schematic.py: Generate scientific diagrams and schematics

References

Templates

Ready-to-use poster templates in assets/ directory:

  • beamerposter templates (classic, modern, colorful)
  • tikzposter templates (default, rays, wave, envelope)
  • baposter templates (portrait, landscape, minimal)
  • Example posters from various scientific disciplines
  • Color scheme definitions and institutional templates

Load these templates and customize for your specific research and conference requirements.

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 Latex Posters AI skill do?

Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.

Why use Latex Posters on TypingMind?

Because you install it once and use it with any model. Latex Posters 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 Latex Posters in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/K-Dense-AI/claude-scientific-writer/tree/main/skills/latex-posters. 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 Latex Posters?

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 Latex Posters?

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

Is the Latex Posters AI skill free?

Yes. It is published on GitHub by K-Dense-AI under the MIT license. 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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