--- name: latex-posters description: "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." allowed-tools: Read Write Edit Bash ---

# 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.**

---

### CRITICAL: Preventing Content Overflow

**⚠️ POSTERS MUST NOT HAVE TEXT OR CONTENT CUT OFF AT EDGES.**

**Common Overflow Problems:** 1. **Title/footer text extending beyond page boundaries** 2. **Too many sections crammed into available space** 3. **Figures placed too close to edges** 4. **Text blocks exceeding column widths**

**Prevention Rules:**

**1. Limit Content Sections (MAXIMUM 5-6 sections for A0):** ``` ✅ GOOD - 5 sections with room to breathe: - Title/Header - Introduction/Problem - Methods - Results (1-2 key findings) - Conclusions

❌ BAD - 8+ sections crammed together: - Overview, Introduction, Background, Methods, - Results 1, Results 2, Discussion, Conclusions, Future Work ```

**2. Set Safe Margins in LaTeX:** ```latex % tikzposter - add generous margins \documentclass[25pt, a0paper, portrait, margin=25mm]{tikzposter}

% baposter - ensure content doesn't touch edges \begin{poster}{ columns=3, colspacing=2em, % Space between columns headerheight=0.1\textheight, % Smaller header % Leave space at bottom } ```

**3. Figure Sizing - Never 100% Width:** ```latex % Leave margins around figures \includegraphics[width=0.85\linewidth]{figure.png} % NOT 1.0\linewidth ```

**4. Check for Overflow Before Printing:** ```bash # Compile and check PDF at 100% zoom pdflatex poster.tex

# Look for: # - Text cut off at any edge # - Content touching page boundaries # - Overfull hbox warnings in .log file grep -i "overfull" poster.log ```

**5. Word Count Limits:** - **A0 poster**: 300-800 words MAXIMUM - **Per section**: 50-100 words maximum - **If you have more content**: Cut it or make a handout

---

### CRITICAL: Poster-Size Font Requirements

**⚠️ ALL text within AI-generated visualizations MUST be poster-readable.**

When generating graphics for posters, you MUST include font size specifications in EVERY prompt. Poster graphics are viewed from 4-6 feet away, so text must be LARGE.

**⚠️ COMMON PROBLEM: Content Overflow and Density**

The #1 issue with AI-generated poster graphics is **TOO MUCH CONTENT**. This causes: - Text overflow beyond boundaries - Unreadable small fonts - Cluttered, overwhelming visuals - Poor white space usage

**SOLUTION: Generate SIMPLE graphics with MINIMAL content.**

**MANDATORY prompt requirements for EVERY poster graphic:**

``` POSTER FORMAT REQUIREMENTS (STRICTLY ENFORCE): - ABSOLUTE MAXIMUM 3-4 elements per graphic (3 is ideal) - ABSOLUTE MAXIMUM 10 words total in the entire graphic - NO complex workflows with 5+ steps (split into 2-3 simple graphics instead) - NO multi-level nested diagrams (flatten to single level) - NO case studies with multiple sub-sections (one key point per case) - ALL text GIANT BOLD (80pt+ for labels, 120pt+ for key numbers) - High contrast ONLY (dark on white OR white on dark, NO gradients with text) - MANDATORY 50% white space minimum (half the graphic should be empty) - Thick lines only (5px+ minimum), large icons (200px+ minimum) - ONE SINGLE MESSAGE per graphic (not 3 related messages) ```

**⚠️ BEFORE GENERATING: Review your prompt and count elements** - If your description has 5+ items → STOP. Split into multiple graphics - If your workflow has 5+ stages → STOP. Show only 3-4 high-level steps - If your comparison has 4+ methods → STOP. Show only top 3 or Our vs Best Baseline

**Content limits per graphic type (STRICT):** | Graphic Type | Max Elements | Max Words | Reject If | Good Example | |--------------|--------------|-----------|-----------|--------------| | Flowchart | **3-4 boxes MAX** | **8 words** | 5+ stages, nested steps | "DISCOVER → VALIDATE → APPROVE" (3 words) | | Key findings | **3 items MAX** | **9 words** | 4+ metrics, paragraphs | "95% ACCURATE" "2X FASTER" "FDA READY" (6 words) | | Comparison chart | **3 bars MAX** | **6 words** | 4+ methods, legend text | "OURS: 95%" "BEST: 85%" (4 words) | | Case study | **1 case, 3 elements** | **6 words** | Multiple cases, substories | Logo + "18 MONTHS" + "to discovery" (2 words) | | Timeline | **3-4 points MAX** | **8 words** | Year-by-year detail | "2020 START" "2022 TRIAL" "2024 APPROVED" (6 words) |

**Example - WRONG (7-stage workflow - TOO COMPLEX):** ```bash # ❌ BAD - This creates tiny unreadable text like the drug discovery poster python scripts/generate_schematic.py "Drug discovery workflow showing: Stage 1 Target Identification, Stage 2 Molecular Synthesis, Stage 3 Virtual Screening, Stage 4 AI Lead Optimization, Stage 5 Clinical Trial Design, Stage 6 FDA Approval. Include success metrics, timelines, and validation steps for each stage." -o figures/workflow.png # Result: 7+ stages with tiny text, unreadable from 6 feet - POSTER FAILURE ```

**Example - CORRECT (simplified to 3 key stages):** ```bash # ✅ GOOD - Same content, split into ONE simple high-level graphic python scripts/generate_schematic.py "POSTER FORMAT for A0. ULTRA-SIMPLE 3-box workflow: 'DISCOVER' → 'VALIDATE' → 'APPROVE'. Each word in GIANT bold (120pt+). Thick arrows (10px). 60% white space. NO substeps, NO details. 3 words total. Readable from 10 feet." -o figures/workflow_overview.png # Result: Clean, impactful, readable - can add detail graphics separately if needed ```

**Example - WRONG (complex case studies with multiple sections):** ```bash # ❌ BAD - Creates cramped unreadable sections python scripts/generate_schematic.py "Case studies: Insilico Medicine (drug candidate, discovery time, clinical trials), Recursion Pharma (platform, methodology, results), Exscientia (drug candidates, FDA status, timeline). Include company logos, metrics, and outcomes." -o figures/cases.png # Result: 3 case studies with 4+ elements each = 12+ total elements, tiny text ```

**Example - CORRECT (one case study, one key metric):** ```bash # ✅ GOOD - Show ONE case with ONE key number python scripts/generate_schematic.py "POSTER FORMAT for A0. ONE case study card: Company logo (large), '18 MONTHS' in GIANT text (150pt), 'to discovery' below (60pt). 3 elements total: logo + number + caption. 50% white space. Readable from 10 feet." -o figures/case_single.png # Result: Clear, readable, impactful. Make 3 separate graphics if you need 3 cases. ```

**Example - WRONG (key findings too complex):** ```bash # BAD - too many items, too much detail python scripts/generate_schematic.py "Key findings showing 8 metrics: accuracy 95%, precision 92%, recall 94%, F1 0.93, AUC 0.97, training time 2.3 hours, inference 50ms, model size 145MB with comparison to 5 baseline methods" -o figures/findings.png # Result: Cramped graphic with tiny numbers ```

**Example - CORRECT (key findings simple):** ```bash # GOOD - only 3 key items, giant numbers python scripts/generate_schematic.py "POSTER FORMAT for A0. KEY FINDINGS with ONLY 3 large cards. Card 1: '95%' in GIANT text (120pt) with 'ACCURACY' below (48pt). Card 2: '2X' in GIANT text with 'FASTER' below. Card 3: checkmark icon with 'VALIDATED' in large text. 50% white space. High contrast colors. NO other text or details." -o figures/findings.png # Result: Bold, readable impact statement ```

**Font size reference for poster prompts:** | Element | Minimum Size | Prompt Keywords | |---------|--------------|-----------------| | Main numbers/metrics | 72pt+ | "huge", "very large", "giant", "poster-size" | | Section titles | 60pt+ | "large bold", "prominent" | | Labels/captions | 36pt+ | "readable from 6 feet", "clear labels" | | Body text | 24pt+ | "poster-readable", "large text" |

**Always include in prompts:** - "POSTER FORMAT" or "for A0 poster" or "readable from 6 feet" - "VERY LARGE TEXT" or "huge bold fonts" - Specific text that should appear (so it's baked into the image) - "minimal text, maximum impact" - "high contrast" for readability - "generous margins" and "no text near edges"

---

### CRITICAL: AI-Generated Graphic Sizing

**⚠️ Each AI-generated graphic should focus on ONE concept with MINIMAL content.**

**Problem**: Generating complex diagrams with many elements leads to small text.

**Solution**: Generate SIMPLE graphics with FEW elements and LARGE text.

**Example - WRONG (too complex, text will be small):** ```bash # BAD - too many elements in one graphic python scripts/generate_schematic.py "Complete ML pipeline showing data collection, preprocessing with 5 steps, feature engineering with 8 techniques, model training with hyperparameter tuning, validation with cross-validation, and deployment with monitoring. Include all labels and descriptions." -o figures/pipeline.png ```

**Example - CORRECT (simple, focused, large text):** ```bash # GOOD - split into multiple simple graphics with large text

# Graphic 1: High-level overview (3-4 elements max) python scripts/generate_schematic.py "POSTER FORMAT for A0: Simple 4-step pipeline. Four large boxes: DATA → PROCESS → MODEL → RESULTS. GIANT labels (80pt+), thick arrows, lots of white space. Only 4 words total. Readable from 8 feet." -o figures/overview.png

# Graphic 2: Key result (1 metric highlighted) python scripts/generate_schematic.py "POSTER FORMAT for A0: Single key metric display. Giant '95%' text (150pt+) with 'ACCURACY' below (60pt+). Checkmark icon. Minimal design, high contrast. Readable from 10 feet." -o figures/accuracy.png ```

**Rules for AI-generated poster graphics:** | Rule | Limit | Reason | |------|-------|--------| | **Elements per graphic** | 3-5 maximum | More elements = smaller text | | **Words per graphic** | 10-15 maximum | Minimal text = larger fonts | | **Flowchart steps** | 4-5 maximum | Keeps labels readable | | **Chart categories** | 3-4 maximum | Prevents crowding | | **Nested levels** | 1-2 maximum | Avoids complexity |

**Split complex content into multiple simple graphics:** ``` Instead of 1 complex diagram with 12 elements: → Create 3 simple diagrams with 4 elements each → Each graphic can have LARGER text → Arrange in poster with clear visual flow ```

---

### Step 0: MANDATORY Pre-Generation Review (DO THIS FIRST)

**⚠️ BEFORE generating ANY graphics, review your content plan:**

**For EACH planned gra

--- name: latex-posters description: "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." allowed-tools: Read Write Edit Bash ---

# 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.**

---

### CRITICAL: Preventing Content Overflow

**⚠️ POSTERS MUST NOT HAVE TEXT OR CONTENT CUT OFF AT EDGES.**

**Common Overflow Problems:** 1. **Title/footer text extending beyond page boundaries** 2. **Too many sections crammed into available space** 3. **Figures placed too close to edges** 4. **Text blocks exceeding column widths**

**Prevention Rules:**

**1. Limit Content Sections (MAXIMUM 5-6 sections for A0):** ``` ✅ GOOD - 5 sections with room to breathe: - Title/Header - Introduction/Problem - Methods - Results (1-2 key findings) - Conclusions

❌ BAD - 8+ sections crammed together: - Overview, Introduction, Background, Methods, - Results 1, Results 2, Discussion, Conclusions, Future Work ```

**2. Set Safe Margins in LaTeX:** ```latex % tikzposter - add generous margins \documentclass[25pt, a0paper, portrait, margin=25mm]{tikzposter}

% baposter - ensure content doesn't touch edges \begin{poster}{ columns=3, colspacing=2em, % Space between columns headerheight=0.1\textheight, % Smaller header % Leave space at bottom } ```

**3. Figure Sizing - Never 100% Width:** ```latex % Leave margins around figures \includegraphics[width=0.85\linewidth]{figure.png} % NOT 1.0\linewidth ```

**4. Check for Overflow Before Printing:** ```bash # Compile and check PDF at 100% zoom pdflatex poster.tex

# Look for: # - Text cut off at any edge # - Content touching page boundaries # - Overfull hbox warnings in .log file grep -i "overfull" poster.log ```

**5. Word Count Limits:** - **A0 poster**: 300-800 words MAXIMUM - **Per section**: 50-100 words maximum - **If you have more content**: Cut it or make a handout

---

### CRITICAL: Poster-Size Font Requirements

**⚠️ ALL text within AI-generated visualizations MUST be poster-readable.**

When generating graphics for posters, you MUST include font size specifications in EVERY prompt. Poster graphics are viewed from 4-6 feet away, so text must be LARGE.

**⚠️ COMMON PROBLEM: Content Overflow and Density**

The #1 issue with AI-generated poster graphics is **TOO MUCH CONTENT**. This causes: - Text overflow beyond boundaries - Unreadable small fonts - Cluttered, overwhelming visuals - Poor white space usage

**SOLUTION: Generate SIMPLE graphics with MINIMAL content.**

**MANDATORY prompt requirements for EVERY poster graphic:**

``` POSTER FORMAT REQUIREMENTS (STRICTLY ENFORCE): - ABSOLUTE MAXIMUM 3-4 elements per graphic (3 is ideal) - ABSOLUTE MAXIMUM 10 words total in the entire graphic - NO complex workflows with 5+ steps (split into 2-3 simple graphics instead) - NO multi-level nested diagrams (flatten to single level) - NO case studies with multiple sub-sections (one key point per case) - ALL text GIANT BOLD (80pt+ for labels, 120pt+ for key numbers) - High contrast ONLY (dark on white OR white on dark, NO gradients with text) - MANDATORY 50% white space minimum (half the graphic should be empty) - Thick lines only (5px+ minimum), large icons (200px+ minimum) - ONE SINGLE MESSAGE per graphic (not 3 related messages) ```

**⚠️ BEFORE GENERATING: Review your prompt and count elements** - If your description has 5+ items → STOP. Split into multiple graphics - If your workflow has 5+ stages → STOP. Show only 3-4 high-level steps - If your comparison has 4+ methods → STOP. Show only top 3 or Our vs Best Baseline

**Content limits per graphic type (STRICT):** | Graphic Type | Max Elements | Max Words | Reject If | Good Example | |--------------|--------------|-----------|-----------|--------------| | Flowchart | **3-4 boxes MAX** | **8 words** | 5+ stages, nested steps | "DISCOVER → VALIDATE → APPROVE" (3 words) | | Key findings | **3 items MAX** | **9 words** | 4+ metrics, paragraphs | "95% ACCURATE" "2X FASTER" "FDA READY" (6 words) | | Comparison chart | **3 bars MAX** | **6 words** | 4+ methods, legend text | "OURS: 95%" "BEST: 85%" (4 words) | | Case study | **1 case, 3 elements** | **6 words** | Multiple cases, substories | Logo + "18 MONTHS" + "to discovery" (2 words) | | Timeline | **3-4 points MAX** | **8 words** | Year-by-year detail | "2020 START" "2022 TRIAL" "2024 APPROVED" (6 words) |

**Example - WRONG (7-stage workflow - TOO COMPLEX):** ```bash # ❌ BAD - This creates tiny unreadable text like the drug discovery poster python scripts/generate_schematic.py "Drug discovery workflow showing: Stage 1 Target Identification, Stage 2 Molecular Synthesis, Stage 3 Virtual Screening, Stage 4 AI Lead Optimization, Stage 5 Clinical Trial Design, Stage 6 FDA Approval. Include success metrics, timelines, and validation steps for each stage." -o figures/workflow.png # Result: 7+ stages with tiny text, unreadable from 6 feet - POSTER FAILURE ```

**Example - CORRECT (simplified to 3 key stages):** ```bash # ✅ GOOD - Same content, split into ONE simple high-level graphic python scripts/generate_schematic.py "POSTER FORMAT for A0. ULTRA-SIMPLE 3-box workflow: 'DISCOVER' → 'VALIDATE' → 'APPROVE'. Each word in GIANT bold (120pt+). Thick arrows (10px). 60% white space. NO substeps, NO details. 3 words total. Readable from 10 feet." -o figures/workflow_overview.png # Result: Clean, impactful, readable - can add detail graphics separately if needed ```

**Example - WRONG (complex case studies with multiple sections):** ```bash # ❌ BAD - Creates cramped unreadable sections python scripts/generate_schematic.py "Case studies: Insilico Medicine (drug candidate, discovery time, clinical trials), Recursion Pharma (platform, methodology, results), Exscientia (drug candidates, FDA status, timeline). Include company logos, metrics, and outcomes." -o figures/cases.png # Result: 3 case studies with 4+ elements each = 12+ total elements, tiny text ```

**Example - CORRECT (one case study, one key metric):** ```bash # ✅ GOOD - Show ONE case with ONE key number python scripts/generate_schematic.py "POSTER FORMAT for A0. ONE case study card: Company logo (large), '18 MONTHS' in GIANT text (150pt), 'to discovery' below (60pt). 3 elements total: logo + number + caption. 50% white space. Readable from 10 feet." -o figures/case_single.png # Result: Clear, readable, impactful. Make 3 separate graphics if you need 3 cases. ```

**Example - WRONG (key findings too complex):** ```bash # BAD - too many items, too much detail python scripts/generate_schematic.py "Key findings showing 8 metrics: accuracy 95%, precision 92%, recall 94%, F1 0.93, AUC 0.97, training time 2.3 hours, inference 50ms, model size 145MB with comparison to 5 baseline methods" -o figures/findings.png # Result: Cramped graphic with tiny numbers ```

**Example - CORRECT (key findings simple):** ```bash # GOOD - only 3 key items, giant numbers python scripts/generate_schematic.py "POSTER FORMAT for A0. KEY FINDINGS with ONLY 3 large cards. Card 1: '95%' in GIANT text (120pt) with 'ACCURACY' below (48pt). Card 2: '2X' in GIANT text with 'FASTER' below. Card 3: checkmark icon with 'VALIDATED' in large text. 50% white space. High contrast colors. NO other text or details." -o figures/findings.png # Result: Bold, readable impact statement ```

**Font size reference for poster prompts:** | Element | Minimum Size | Prompt Keywords | |---------|--------------|-----------------| | Main numbers/metrics | 72pt+ | "huge", "very large", "giant", "poster-size" | | Section titles | 60pt+ | "large bold", "prominent" | | Labels/captions | 36pt+ | "readable from 6 feet", "clear labels" | | Body text | 24pt+ | "poster-readable", "large text" |

**Always include in prompts:** - "POSTER FORMAT" or "for A0 poster" or "readable from 6 feet" - "VERY LARGE TEXT" or "huge bold fonts" - Specific text that should appear (so it's baked into the image) - "minimal text, maximum impact" - "high contrast" for readability - "generous margins" and "no text near edges"

---

### CRITICAL: AI-Generated Graphic Sizing

**⚠️ Each AI-generated graphic should focus on ONE concept with MINIMAL content.**

**Problem**: Generating complex diagrams with many elements leads to small text.

**Solution**: Generate SIMPLE graphics with FEW elements and LARGE text.

**Example - WRONG (too complex, text will be small):** ```bash # BAD - too many elements in one graphic python scripts/generate_schematic.py "Complete ML pipeline showing data collection, preprocessing with 5 steps, feature engineering with 8 techniques, model training with hyperparameter tuning, validation with cross-validation, and deployment with monitoring. Include all labels and descriptions." -o figures/pipeline.png ```

**Example - CORRECT (simple, focused, large text):** ```bash # GOOD - split into multiple simple graphics with large text

# Graphic 1: High-level overview (3-4 elements max) python scripts/generate_schematic.py "POSTER FORMAT for A0: Simple 4-step pipeline. Four large boxes: DATA → PROCESS → MODEL → RESULTS. GIANT labels (80pt+), thick arrows, lots of white space. Only 4 words total. Readable from 8 feet." -o figures/overview.png

# Graphic 2: Key result (1 metric highlighted) python scripts/generate_schematic.py "POSTER FORMAT for A0: Single key metric display. Giant '95%' text (150pt+) with 'ACCURACY' below (60pt+). Checkmark icon. Minimal design, high contrast. Readable from 10 feet." -o figures/accuracy.png ```

**Rules for AI-generated poster graphics:** | Rule | Limit | Reason | |------|-------|--------| | **Elements per graphic** | 3-5 maximum | More elements = smaller text | | **Words per graphic** | 10-15 maximum | Minimal text = larger fonts | | **Flowchart steps** | 4-5 maximum | Keeps labels readable | | **Chart categories** | 3-4 maximum | Prevents crowding | | **Nested levels** | 1-2 maximum | Avoids complexity |

**Split complex content into multiple simple graphics:** ``` Instead of 1 complex diagram with 12 elements: → Create 3 simple diagrams with 4 elements each → Each graphic can have LARGER text → Arrange in poster with clear visual flow ```

---

### Step 0: MANDATORY Pre-Generation Review (DO THIS FIRST)

**⚠️ BEFORE generating ANY graphics, review your content plan:**

**For EACH planned gra

--- name: latex-posters description: "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." allowed-tools: Read Write Edit Bash ---

# 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.**

---

### CRITICAL: Preventing Content Overflow

**⚠️ POSTERS MUST NOT HAVE TEXT OR CONTENT CUT OFF AT EDGES.**

**Common Overflow Problems:** 1. **Title/footer text extending beyond page boundaries** 2. **Too many sections crammed into available space** 3. **Figures placed too close to edges** 4. **Text blocks exceeding column widths**

**Prevention Rules:**

**1. Limit Content Sections (MAXIMUM 5-6 sections for A0):** ``` ✅ GOOD - 5 sections with room to breathe: - Title/Header - Introduction/Problem - Methods - Results (1-2 key findings) - Conclusions

❌ BAD - 8+ sections crammed together: - Overview, Introduction, Background, Methods, - Results 1, Results 2, Discussion, Conclusions, Future Work ```

**2. Set Safe Margins in LaTeX:** ```latex % tikzposter - add generous margins \documentclass[25pt, a0paper, portrait, margin=25mm]{tikzposter}

% baposter - ensure content doesn't touch edges \begin{poster}{ columns=3, colspacing=2em, % Space between columns headerheight=0.1\textheight, % Smaller header % Leave space at bottom } ```

**3. Figure Sizing - Never 100% Width:** ```latex % Leave margins around figures \includegraphics[width=0.85\linewidth]{figure.png} % NOT 1.0\linewidth ```

**4. Check for Overflow Before Printing:** ```bash # Compile and check PDF at 100% zoom pdflatex poster.tex

# Look for: # - Text cut off at any edge # - Content touching page boundaries # - Overfull hbox warnings in .log file grep -i "overfull" poster.log ```

**5. Word Count Limits:** - **A0 poster**: 300-800 words MAXIMUM - **Per section**: 50-100 words maximum - **If you have more content**: Cut it or make a handout

---

### CRITICAL: Poster-Size Font Requirements

**⚠️ ALL text within AI-generated visualizations MUST be poster-readable.**

When generating graphics for posters, you MUST include font size specifications in EVERY prompt. Poster graphics are viewed from 4-6 feet away, so text must be LARGE.

**⚠️ COMMON PROBLEM: Content Overflow and Density**

The #1 issue with AI-generated poster graphics is **TOO MUCH CONTENT**. This causes: - Text overflow beyond boundaries - Unreadable small fonts - Cluttered, overwhelming visuals - Poor white space usage

**SOLUTION: Generate SIMPLE graphics with MINIMAL content.**

**MANDATORY prompt requirements for EVERY poster graphic:**

``` POSTER FORMAT REQUIREMENTS (STRICTLY ENFORCE): - ABSOLUTE MAXIMUM 3-4 elements per graphic (3 is ideal) - ABSOLUTE MAXIMUM 10 words total in the entire graphic - NO complex workflows with 5+ steps (split into 2-3 simple graphics instead) - NO multi-level nested diagrams (flatten to single level) - NO case studies with multiple sub-sections (one key point per case) - ALL text GIANT BOLD (80pt+ for labels, 120pt+ for key numbers) - High contrast ONLY (dark on white OR white on dark, NO gradients with text) - MANDATORY 50% white space minimum (half the graphic should be empty) - Thick lines only (5px+ minimum), large icons (200px+ minimum) - ONE SINGLE MESSAGE per graphic (not 3 related messages) ```

**⚠️ BEFORE GENERATING: Review your prompt and count elements** - If your description has 5+ items → STOP. Split into multiple graphics - If your workflow has 5+ stages → STOP. Show only 3-4 high-level steps - If your comparison has 4+ methods → STOP. Show only top 3 or Our vs Best Baseline

**Content limits per graphic type (STRICT):** | Graphic Type | Max Elements | Max Words | Reject If | Good Example | |--------------|--------------|-----------|-----------|--------------| | Flowchart | **3-4 boxes MAX** | **8 words** | 5+ stages, nested steps | "DISCOVER → VALIDATE → APPROVE" (3 words) | | Key findings | **3 items MAX** | **9 words** | 4+ metrics, paragraphs | "95% ACCURATE" "2X FASTER" "FDA READY" (6 words) | | Comparison chart | **3 bars MAX** | **6 words** | 4+ methods, legend text | "OURS: 95%" "BEST: 85%" (4 words) | | Case study | **1 case, 3 elements** | **6 words** | Multiple cases, substories | Logo + "18 MONTHS" + "to discovery" (2 words) | | Timeline | **3-4 points MAX** | **8 words** | Year-by-year detail | "2020 START" "2022 TRIAL" "2024 APPROVED" (6 words) |

**Example - WRONG (7-stage workflow - TOO COMPLEX):** ```bash # ❌ BAD - This creates tiny unreadable text like the drug discovery poster python scripts/generate_schematic.py "Drug discovery workflow showing: Stage 1 Target Identification, Stage 2 Molecular Synthesis, Stage 3 Virtual Screening, Stage 4 AI Lead Optimization, Stage 5 Clinical Trial Design, Stage 6 FDA Approval. Include success metrics, timelines, and validation steps for each stage." -o figures/workflow.png # Result: 7+ stages with tiny text, unreadable from 6 feet - POSTER FAILURE ```

**Example - CORRECT (simplified to 3 key stages):** ```bash # ✅ GOOD - Same content, split into ONE simple high-level graphic python scripts/generate_schematic.py "POSTER FORMAT for A0. ULTRA-SIMPLE 3-box workflow: 'DISCOVER' → 'VALIDATE' → 'APPROVE'. Each word in GIANT bold (120pt+). Thick arrows (10px). 60% white space. NO substeps, NO details. 3 words total. Readable from 10 feet." -o figures/workflow_overview.png # Result: Clean, impactful, readable - can add detail graphics separately if needed ```

**Example - WRONG (complex case studies with multiple sections):** ```bash # ❌ BAD - Creates cramped unreadable sections python scripts/generate_schematic.py "Case studies: Insilico Medicine (drug candidate, discovery time, clinical trials), Recursion Pharma (platform, methodology, results), Exscientia (drug candidates, FDA status, timeline). Include company logos, metrics, and outcomes." -o figures/cases.png # Result: 3 case studies with 4+ elements each = 12+ total elements, tiny text ```

**Example - CORRECT (one case study, one key metric):** ```bash # ✅ GOOD - Show ONE case with ONE key number python scripts/generate_schematic.py "POSTER FORMAT for A0. ONE case study card: Company logo (large), '18 MONTHS' in GIANT text (150pt), 'to discovery' below (60pt). 3 elements total: logo + number + caption. 50% white space. Readable from 10 feet." -o figures/case_single.png # Result: Clear, readable, impactful. Make 3 separate graphics if you need 3 cases. ```

**Example - WRONG (key findings too complex):** ```bash # BAD - too many items, too much detail python scripts/generate_schematic.py "Key findings showing 8 metrics: accuracy 95%, precision 92%, recall 94%, F1 0.93, AUC 0.97, training time 2.3 hours, inference 50ms, model size 145MB with comparison to 5 baseline methods" -o figures/findings.png # Result: Cramped graphic with tiny numbers ```

**Example - CORRECT (key findings simple):** ```bash # GOOD - only 3 key items, giant numbers python scripts/generate_schematic.py "POSTER FORMAT for A0. KEY FINDINGS with ONLY 3 large cards. Card 1: '95%' in GIANT text (120pt) with 'ACCURACY' below (48pt). Card 2: '2X' in GIANT text with 'FASTER' below. Card 3: checkmark icon with 'VALIDATED' in large text. 50% white space. High contrast colors. NO other text or details." -o figures/findings.png # Result: Bold, readable impact statement ```

**Font size reference for poster prompts:** | Element | Minimum Size | Prompt Keywords | |---------|--------------|-----------------| | Main numbers/metrics | 72pt+ | "huge", "very large", "giant", "poster-size" | | Section titles | 60pt+ | "large bold", "prominent" | | Labels/captions | 36pt+ | "readable from 6 feet", "clear labels" | | Body text | 24pt+ | "poster-readable", "large text" |

**Always include in prompts:** - "POSTER FORMAT" or "for A0 poster" or "readable from 6 feet" - "VERY LARGE TEXT" or "huge bold fonts" - Specific text that should appear (so it's baked into the image) - "minimal text, maximum impact" - "high contrast" for readability - "generous margins" and "no text near edges"

---

### CRITICAL: AI-Generated Graphic Sizing

**⚠️ Each AI-generated graphic should focus on ONE concept with MINIMAL content.**

**Problem**: Generating complex diagrams with many elements leads to small text.

**Solution**: Generate SIMPLE graphics with FEW elements and LARGE text.

**Example - WRONG (too complex, text will be small):** ```bash # BAD - too many elements in one graphic python scripts/generate_schematic.py "Complete ML pipeline showing data collection, preprocessing with 5 steps, feature engineering with 8 techniques, model training with hyperparameter tuning, validation with cross-validation, and deployment with monitoring. Include all labels and descriptions." -o figures/pipeline.png ```

**Example - CORRECT (simple, focused, large text):** ```bash # GOOD - split into multiple simple graphics with large text

# Graphic 1: High-level overview (3-4 elements max) python scripts/generate_schematic.py "POSTER FORMAT for A0: Simple 4-step pipeline. Four large boxes: DATA → PROCESS → MODEL → RESULTS. GIANT labels (80pt+), thick arrows, lots of white space. Only 4 words total. Readable from 8 feet." -o figures/overview.png

# Graphic 2: Key result (1 metric highlighted) python scripts/generate_schematic.py "POSTER FORMAT for A0: Single key metric display. Giant '95%' text (150pt+) with 'ACCURACY' below (60pt+). Checkmark icon. Minimal design, high contrast. Readable from 10 feet." -o figures/accuracy.png ```

**Rules for AI-generated poster graphics:** | Rule | Limit | Reason | |------|-------|--------| | **Elements per graphic** | 3-5 maximum | More elements = smaller text | | **Words per graphic** | 10-15 maximum | Minimal text = larger fonts | | **Flowchart steps** | 4-5 maximum | Keeps labels readable | | **Chart categories** | 3-4 maximum | Prevents crowding | | **Nested levels** | 1-2 maximum | Avoids complexity |

**Split complex content into multiple simple graphics:** ``` Instead of 1 complex diagram with 12 elements: → Create 3 simple diagrams with 4 elements each → Each graphic can have LARGER text → Arrange in poster with clear visual flow ```

---

### Step 0: MANDATORY Pre-Generation Review (DO THIS FIRST)

**⚠️ BEFORE generating ANY graphics, review your content plan:**

**For EACH planned gra

--- name: latex-posters description: "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." allowed-tools: Read Write Edit Bash ---

# 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.**

---

### CRITICAL: Preventing Content Overflow

**⚠️ POSTERS MUST NOT HAVE TEXT OR CONTENT CUT OFF AT EDGES.**

**Common Overflow Problems:** 1. **Title/footer text extending beyond page boundaries** 2. **Too many sections crammed into available space** 3. **Figures placed too close to edges** 4. **Text blocks exceeding column widths**

**Prevention Rules:**

**1. Limit Content Sections (MAXIMUM 5-6 sections for A0):** ``` ✅ GOOD - 5 sections with room to breathe: - Title/Header - Introduction/Problem - Methods - Results (1-2 key findings) - Conclusions

❌ BAD - 8+ sections crammed together: - Overview, Introduction, Background, Methods, - Results 1, Results 2, Discussion, Conclusions, Future Work ```

**2. Set Safe Margins in LaTeX:** ```latex % tikzposter - add generous margins \documentclass[25pt, a0paper, portrait, margin=25mm]{tikzposter}

% baposter - ensure content doesn't touch edges \begin{poster}{ columns=3, colspacing=2em, % Space between columns headerheight=0.1\textheight, % Smaller header % Leave space at bottom } ```

**3. Figure Sizing - Never 100% Width:** ```latex % Leave margins around figures \includegraphics[width=0.85\linewidth]{figure.png} % NOT 1.0\linewidth ```

**4. Check for Overflow Before Printing:** ```bash # Compile and check PDF at 100% zoom pdflatex poster.tex

# Look for: # - Text cut off at any edge # - Content touching page boundaries # - Overfull hbox warnings in .log file grep -i "overfull" poster.log ```

**5. Word Count Limits:** - **A0 poster**: 300-800 words MAXIMUM - **Per section**: 50-100 words maximum - **If you have more content**: Cut it or make a handout

---

### CRITICAL: Poster-Size Font Requirements

**⚠️ ALL text within AI-generated visualizations MUST be poster-readable.**

When generating graphics for posters, you MUST include font size specifications in EVERY prompt. Poster graphics are viewed from 4-6 feet away, so text must be LARGE.

**⚠️ COMMON PROBLEM: Content Overflow and Density**

The #1 issue with AI-generated poster graphics is **TOO MUCH CONTENT**. This causes: - Text overflow beyond boundaries - Unreadable small fonts - Cluttered, overwhelming visuals - Poor white space usage

**SOLUTION: Generate SIMPLE graphics with MINIMAL content.**

**MANDATORY prompt requirements for EVERY poster graphic:**

``` POSTER FORMAT REQUIREMENTS (STRICTLY ENFORCE): - ABSOLUTE MAXIMUM 3-4 elements per graphic (3 is ideal) - ABSOLUTE MAXIMUM 10 words total in the entire graphic - NO complex workflows with 5+ steps (split into 2-3 simple graphics instead) - NO multi-level nested diagrams (flatten to single level) - NO case studies with multiple sub-sections (one key point per case) - ALL text GIANT BOLD (80pt+ for labels, 120pt+ for key numbers) - High contrast ONLY (dark on white OR white on dark, NO gradients with text) - MANDATORY 50% white space minimum (half the graphic should be empty) - Thick lines only (5px+ minimum), large icons (200px+ minimum) - ONE SINGLE MESSAGE per graphic (not 3 related messages) ```

**⚠️ BEFORE GENERATING: Review your prompt and count elements** - If your description has 5+ items → STOP. Split into multiple graphics - If your workflow has 5+ stages → STOP. Show only 3-4 high-level steps - If your comparison has 4+ methods → STOP. Show only top 3 or Our vs Best Baseline

**Content limits per graphic type (STRICT):** | Graphic Type | Max Elements | Max Words | Reject If | Good Example | |--------------|--------------|-----------|-----------|--------------| | Flowchart | **3-4 boxes MAX** | **8 words** | 5+ stages, nested steps | "DISCOVER → VALIDATE → APPROVE" (3 words) | | Key findings | **3 items MAX** | **9 words** | 4+ metrics, paragraphs | "95% ACCURATE" "2X FASTER" "FDA READY" (6 words) | | Comparison chart | **3 bars MAX** | **6 words** | 4+ methods, legend text | "OURS: 95%" "BEST: 85%" (4 words) | | Case study | **1 case, 3 elements** | **6 words** | Multiple cases, substories | Logo + "18 MONTHS" + "to discovery" (2 words) | | Timeline | **3-4 points MAX** | **8 words** | Year-by-year detail | "2020 START" "2022 TRIAL" "2024 APPROVED" (6 words) |

**Example - WRONG (7-stage workflow - TOO COMPLEX):** ```bash # ❌ BAD - This creates tiny unreadable text like the drug discovery poster python scripts/generate_schematic.py "Drug discovery workflow showing: Stage 1 Target Identification, Stage 2 Molecular Synthesis, Stage 3 Virtual Screening, Stage 4 AI Lead Optimization, Stage 5 Clinical Trial Design, Stage 6 FDA Approval. Include success metrics, timelines, and validation steps for each stage." -o figures/workflow.png # Result: 7+ stages with tiny text, unreadable from 6 feet - POSTER FAILURE ```

**Example - CORRECT (simplified to 3 key stages):** ```bash # ✅ GOOD - Same content, split into ONE simple high-level graphic python scripts/generate_schematic.py "POSTER FORMAT for A0. ULTRA-SIMPLE 3-box workflow: 'DISCOVER' → 'VALIDATE' → 'APPROVE'. Each word in GIANT bold (120pt+). Thick arrows (10px). 60% white space. NO substeps, NO details. 3 words total. Readable from 10 feet." -o figures/workflow_overview.png # Result: Clean, impactful, readable - can add detail graphics separately if needed ```

**Example - WRONG (complex case studies with multiple sections):** ```bash # ❌ BAD - Creates cramped unreadable sections python scripts/generate_schematic.py "Case studies: Insilico Medicine (drug candidate, discovery time, clinical trials), Recursion Pharma (platform, methodology, results), Exscientia (drug candidates, FDA status, timeline). Include company logos, metrics, and outcomes." -o figures/cases.png # Result: 3 case studies with 4+ elements each = 12+ total elements, tiny text ```

**Example - CORRECT (one case study, one key metric):** ```bash # ✅ GOOD - Show ONE case with ONE key number python scripts/generate_schematic.py "POSTER FORMAT for A0. ONE case study card: Company logo (large), '18 MONTHS' in GIANT text (150pt), 'to discovery' below (60pt). 3 elements total: logo + number + caption. 50% white space. Readable from 10 feet." -o figures/case_single.png # Result: Clear, readable, impactful. Make 3 separate graphics if you need 3 cases. ```

**Example - WRONG (key findings too complex):** ```bash # BAD - too many items, too much detail python scripts/generate_schematic.py "Key findings showing 8 metrics: accuracy 95%, precision 92%, recall 94%, F1 0.93, AUC 0.97, training time 2.3 hours, inference 50ms, model size 145MB with comparison to 5 baseline methods" -o figures/findings.png # Result: Cramped graphic with tiny numbers ```

**Example - CORRECT (key findings simple):** ```bash # GOOD - only 3 key items, giant numbers python scripts/generate_schematic.py "POSTER FORMAT for A0. KEY FINDINGS with ONLY 3 large cards. Card 1: '95%' in GIANT text (120pt) with 'ACCURACY' below (48pt). Card 2: '2X' in GIANT text with 'FASTER' below. Card 3: checkmark icon with 'VALIDATED' in large text. 50% white space. High contrast colors. NO other text or details." -o figures/findings.png # Result: Bold, readable impact statement ```

**Font size reference for poster prompts:** | Element | Minimum Size | Prompt Keywords | |---------|--------------|-----------------| | Main numbers/metrics | 72pt+ | "huge", "very large", "giant", "poster-size" | | Section titles | 60pt+ | "large bold", "prominent" | | Labels/captions | 36pt+ | "readable from 6 feet", "clear labels" | | Body text | 24pt+ | "poster-readable", "large text" |

**Always include in prompts:** - "POSTER FORMAT" or "for A0 poster" or "readable from 6 feet" - "VERY LARGE TEXT" or "huge bold fonts" - Specific text that should appear (so it's baked into the image) - "minimal text, maximum impact" - "high contrast" for readability - "generous margins" and "no text near edges"

---

### CRITICAL: AI-Generated Graphic Sizing

**⚠️ Each AI-generated graphic should focus on ONE concept with MINIMAL content.**

**Problem**: Generating complex diagrams with many elements leads to small text.

**Solution**: Generate SIMPLE graphics with FEW elements and LARGE text.

**Example - WRONG (too complex, text will be small):** ```bash # BAD - too many elements in one graphic python scripts/generate_schematic.py "Complete ML pipeline showing data collection, preprocessing with 5 steps, feature engineering with 8 techniques, model training with hyperparameter tuning, validation with cross-validation, and deployment with monitoring. Include all labels and descriptions." -o figures/pipeline.png ```

**Example - CORRECT (simple, focused, large text):** ```bash # GOOD - split into multiple simple graphics with large text

# Graphic 1: High-level overview (3-4 elements max) python scripts/generate_schematic.py "POSTER FORMAT for A0: Simple 4-step pipeline. Four large boxes: DATA → PROCESS → MODEL → RESULTS. GIANT labels (80pt+), thick arrows, lots of white space. Only 4 words total. Readable from 8 feet." -o figures/overview.png

# Graphic 2: Key result (1 metric highlighted) python scripts/generate_schematic.py "POSTER FORMAT for A0: Single key metric display. Giant '95%' text (150pt+) with 'ACCURACY' below (60pt+). Checkmark icon. Minimal design, high contrast. Readable from 10 feet." -o figures/accuracy.png ```

**Rules for AI-generated poster graphics:** | Rule | Limit | Reason | |------|-------|--------| | **Elements per graphic** | 3-5 maximum | More elements = smaller text | | **Words per graphic** | 10-15 maximum | Minimal text = larger fonts | | **Flowchart steps** | 4-5 maximum | Keeps labels readable | | **Chart categories** | 3-4 maximum | Prevents crowding | | **Nested levels** | 1-2 maximum | Avoids complexity |

**Split complex content into multiple simple graphics:** ``` Instead of 1 complex diagram with 12 elements: → Create 3 simple diagrams with 4 elements each → Each graphic can have LARGER text → Arrange in poster with clear visual flow ```

---

### Step 0: MANDATORY Pre-Generation Review (DO THIS FIRST)

**⚠️ BEFORE generating ANY graphics, review your content plan:**

**For EACH planned gra