XzhLoongSkills/skills/research-skills/paper-slide-deck/references/analysis-framework.md

Presentation Analysis Framework

Deep content analysis for effective slide deck creation.

1. Message Hierarchy

Identify the core message structure before designing slides.

Core Message (One Sentence)

• What is the single most important takeaway?
• If the audience remembers only one thing, what should it be?
• Can you state it in ≤15 words?

Supporting Points (3-5 Maximum)

• What evidence supports the core message?
• What sub-topics must be covered?
• Prioritize by audience relevance, not source order

Call-to-Action

• What should the audience DO after viewing?
• Is it clear, specific, and achievable?
• Where does it appear (slide position)?

2. Audience Decision Matrix

Question	Analysis
Who is the primary audience?	[Role, expertise level, relationship to topic]
What do they currently believe?	[Existing knowledge, assumptions, biases]
What decision do we want them to make?	[Specific action or conclusion]
What barriers exist?	[Objections, concerns, missing information]
What evidence will convince them?	[Data types, credibility sources, emotional hooks]

Audience Adaptation

Audience Type	Content Focus	Visual Treatment
Executives	Outcomes, ROI, strategic impact	High-level, clean, data highlights
Technical	Architecture, implementation, specs	Detailed diagrams, code, schematics
General	Benefits, stories, relatability	Visual metaphors, simple charts
Investors	Market size, traction, team	Growth charts, milestones, comparisons
Learners	Step-by-step, examples, practice	Progressive reveals, exercises

3. Visual Opportunity Map

Identify which content benefits from visualization.

Content-to-Visual Mapping

Content Type	Visual Treatment	Example
Comparisons	Side-by-side, before/after	Feature comparison table
Processes	Flow diagrams, numbered steps	Workflow illustration
Hierarchies	Org charts, pyramids, trees	Organizational structure
Timelines	Horizontal/vertical timelines	Project milestones
Statistics	Charts, highlighted numbers	Key metrics with context
Concepts	Icons, metaphors, illustrations	Abstract idea visualization
Relationships	Venn diagrams, networks	Ecosystem or dependencies
Lists	Structured grids, icon rows	Feature bullets with icons

Visual Priority

Rate each piece of content:

• Must Visualize: Complex data, key differentiators, memorable moments
• Should Visualize: Supporting evidence, secondary points
• Text Only: Simple statements, transitions, minor details

4. Presentation Flow

Structure for impact and retention.

Opening (First 2-3 Slides)

Element	Purpose
Hook	Capture attention (surprising stat, question, story)
Context	Why this matters now
Preview	What audience will learn/gain

Middle (Content Slides)

Pattern	When to Use
Problem → Solution	Introducing new products/ideas
Situation → Complication → Resolution	Complex business cases
What → Why → How	Educational content
Past → Present → Future	Transformation stories
Claim → Evidence → Implication	Data-driven arguments

Closing (Final 2-3 Slides)

Element	Purpose
Synthesis	Tie back to core message
Call-to-Action	Clear next steps
Memorable Close	Resonant quote, image, or statement

Transitions

• Each slide should answer: "What comes next?"
• Use narrative connectors between sections
• Build logical progression, not topic jumps

5. Content Adaptation

Decide what to keep, transform, or omit.

Keep (High Value)

• Core arguments and evidence
• Unique insights or data
• Audience-relevant examples
• Memorable quotes or statistics

Simplify (Medium Value)

• Technical details → Visual summaries
• Long explanations → Bullet hierarchies
• Multiple examples → Best 1-2 examples
• Background context → Brief framing

Visualize (Transform)

• Data tables → Charts or highlighted numbers
• Process descriptions → Flow diagrams
• Comparisons in text → Side-by-side visuals
• Abstract concepts → Concrete metaphors

Omit (Low Value)

• Tangential information
• Redundant examples
• Excessive caveats
• Background the audience already knows

6. Analysis Checklist

Before outline creation, confirm:

Message Clarity

• Core message stated in one sentence
• 3-5 supporting points identified
• Call-to-action defined

Audience Fit

• Primary audience identified
• Existing beliefs mapped
• Desired decision clear
• Evidence matches audience needs

Visual Planning

• Key visualizations identified
• Chart/diagram types selected
• Visual priority assigned

Flow Design

• Opening hook defined
• Middle pattern selected
• Closing approach planned
• Transitions considered

Content Decisions

• Keep/simplify/visualize/omit applied
• Source material fully processed
• No important content overlooked

7. Academic Presentation Analysis

For conference talks, thesis defense, and research presentations.

Paper Structure to Slide Mapping

Paper Section	Slide Type	Suggested Layout
Title + Abstract	Cover + Motivation	paper-title, title-hero
Introduction	Problem Statement + Background	split-screen, bullet-list
Related Work	Context (optional, can condense)	comparison-matrix, hub-spoke
Methods	Architecture/Pipeline	methods-diagram, linear-progression
Experiments	Setup + Results	results-chart, qualitative-grid
Ablation Studies	Detailed Analysis	comparison-matrix, results-chart
Conclusions	Summary + Future Work	contributions, bullet-list
References	Key Citations	references-list

Academic Slide Count Guidelines

Talk Duration	Recommended Slides	Pace
5 min (spotlight)	5-7 slides	~1 min/slide
10 min (short)	8-12 slides	~1 min/slide
15 min (standard)	12-18 slides	~1 min/slide
20 min (full)	15-22 slides	~1 min/slide
30+ min (invited)	25-35 slides	~1 min/slide

Citation Handling

Inline Citations:

• Key works: "[Author et al., Year]" or "[1]"
• Include only most relevant citations on slides
• Full bibliographic details optional

Reference Slide:

• List 5-10 key references at end
• Format: [N] Author et al. "Title." Venue, Year.

Results Presentation Checklist

• Baseline comparisons clearly labeled
• Best results highlighted (bold or color)
• Statistical significance noted where applicable
• Units and metrics clearly stated
• Error bars or confidence intervals if available
• Ablation results in separate table/chart

Academic Talk Flow

1. Hook (1 slide): Problem motivation, why it matters
2. Background (1-2 slides): Essential context only
3. Approach (2-4 slides): Your method, architecture
4. Results (2-4 slides): Main experiments, comparisons
5. Analysis (1-2 slides): Ablations, insights (optional)
6. Conclusion (1 slide): Summary, contributions, future work
7. References (1 slide): Key citations

8. Automatic Figure Detection and Mapping

For academic papers, automatically detect and map figures/tables to slides.

Figure Detection Process

1. Run detection script on source PDF:

   npx -y bun ${SKILL_DIR}/scripts/detect-figures.ts --pdf source-paper.pdf --output figures.json
   

2. Parse detection results to identify:

   • Figure numbers, pages, and captions
   • Table numbers, pages, and captions
   • Total figure/table count

Figure-to-Slide Mapping Rules

Figure Type	Maps To	Extract?	Reasoning
Architecture/Pipeline diagram	Methods slide	Yes	Core visual, must be accurate
Network structure	Methods slide	Yes	Technical precision required
Quantitative results table	Results slide	Yes	Data accuracy critical
Qualitative comparison grid	Results slide	Yes	Visual comparison must be authentic
Ablation study table	Analysis slide	Yes	Precise numbers needed
Challenge/motivation illustration	Background slide	Maybe	Depends on complexity
Conceptual diagram	Any	No	Can be re-stylized by AI
Simple flowchart	Any	No	AI can render cleanly

Automatic Mapping Algorithm

For each detected figure:
  1. Analyze caption keywords:
     - "architecture", "framework", "pipeline", "network" → Methods slide
     - "comparison", "results", "performance" → Results slide
     - "ablation", "analysis" → Analysis slide
     - "qualitative", "visual" → Qualitative Results slide

  2. Determine extraction necessity:
     - Contains numerical data (tables) → Extract
     - Contains precise diagrams (architecture) → Extract
     - Contains comparison images → Extract
     - Simple conceptual illustration → Generate

  3. Match to outline slide:
     - Find slide with matching topic
     - Add IMAGE_SOURCE metadata automatically

Mapping Confidence Levels

Confidence	Action
High (>80%)	Auto-map and extract
Medium (50-80%)	Auto-map, flag for review
Low (<50%)	Skip, use AI generation

Figure Caption Keywords

Extract (High Priority):

• "architecture", "framework", "pipeline", "overview", "structure"
• "comparison", "results", "performance", "evaluation"
• "ablation", "analysis", "study"
• "qualitative", "visual", "segmentation", "detection"
• Table I/II/III, Table 1/2/3

Generate (Low Priority):

• "illustration", "example", "concept", "motivation"
• "schematic", "diagram" (simple ones)
• Generic workflow without specific data

Auto-Population Format

When auto-populating IMAGE_SOURCE in outline:

// IMAGE_SOURCE
Source: extract
Figure: Figure 2
Page: 4
Caption: Overview of the proposed two-stage framework
Confidence: high
Mapping: Methods slide - "architecture" keyword match

Review Checklist

After auto-detection, verify:

• All key figures detected (architecture, results tables)
• Page numbers correct
• No duplicate mappings
• Conceptual slides correctly marked as "generate"

9. Practical Implementation Notes

Lessons learned from real-world slide generation sessions.

PDF Figure Extraction

pdfjs-dist Compatibility:

• Use pdfjs-dist/legacy/build/pdf.mjs for Node.js compatibility
• The modern build requires browser APIs (DOMMatrix) not available in Node
• If extraction fails with "Image or Canvas expected", fall back to PyMuPDF

PyMuPDF (fitz) Fallback:

import fitz
doc = fitz.open("paper.pdf")
page = doc[page_num - 1]  # 0-indexed
mat = fitz.Matrix(3, 3)   # 3x scale for 4K quality
pix = page.get_pixmap(matrix=mat)
pix.save("output.png")

PyMuPDF is more reliable for complex PDFs with embedded images.

Gemini API Image Generation

Model: gemini-3-pro-image-preview

Config:

config=types.GenerateContentConfig(
    image_config=types.ImageConfig(
        aspect_ratio="16:9",
        image_size="4K"
    )
)

Response Handling:

• Image data is returned as raw bytes in part.inline_data.data
• Do NOT base64 decode - write bytes directly to file
• MIME type is image/jpeg even when requesting PNG output

Network Issues:

• Server disconnections are common for large image generation
• Implement retry logic with exponential backoff (3 retries recommended)
• Wait 5-15 seconds between retries

Optimization:

• Skip already-generated slides (check file size > 10KB)
• Run generation script multiple times if failures occur
• Script is idempotent - safe to re-run

Slide Output Organization

Directory Structure:

slide-deck/{topic-slug}/
├── source-paper.pdf          # Original PDF
├── figures.json              # Detection results
├── outline.md                # Final outline with IMAGE_SOURCE
├── extracted/                # Raw PDF page extractions
│   └── page-{N}.png
├── prompts/                  # Generation prompts
│   └── {NN}-slide-{name}.txt
├── slides/                   # Final slide images
│   └── {NN}-slide-{name}.png
├── {topic-slug}.pptx         # Merged PPTX
└── generate-slides.py        # Generated script (optional)

Common Issues and Solutions

Issue	Solution
pdfjs "DOMMatrix is not defined"	Use legacy build import
pdfjs "Image or Canvas expected"	Use PyMuPDF fallback
Gemini "Server disconnected"	Retry with delay
Small output files (~600 bytes)	Fix: Don't base64 decode response
pdf-lib "Cannot embed PNG"	Check actual image format (may be JPEG)
merge-to-pdf fails	Use PPTX as primary output, convert externally