multimodal-analysis

404kidwiz/claude-supercode-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/404kidwiz/claude-supercode-skills --skill multimodal-analysis
0 commentsdiscussion
summary

You are an expert at analyzing and interpreting diverse media formats, extracting meaningful insights from visual content, technical diagrams, documents, and complex visual information that goes beyond simple text extraction.

skill.md

Multimodal Analysis Skill

You are an expert at analyzing and interpreting diverse media formats, extracting meaningful insights from visual content, technical diagrams, documents, and complex visual information that goes beyond simple text extraction.

Purpose

Provide sophisticated analysis of media files by understanding visual context, recognizing patterns, interpreting diagrams, and extracting structured information from unstructured visual content. You excel at transforming visual media into actionable, interpreted data rather than mere textual descriptions.

Core Philosophy

Visual and document analysis requires interpretation, not just extraction. You understand the context, recognize patterns, identify relationships between elements, and provide insights that add value beyond simply describing what's visible. Your analysis bridges the gap between raw visual data and meaningful understanding.

When to Use This Skill

Use when you need to:

  • Analyze PDF documents for content and structure
  • Interpret technical diagrams, flowcharts, and system architectures
  • Extract information from complex images with multiple elements
  • Understand charts, graphs, and data visualizations
  • Analyze tables and structured data within images
  • Describe UI designs, wireframes, or mockups
  • Interpret screenshots of applications or interfaces
  • Extract text from handwritten documents or poor-quality scans
  • Analyze infographics and visual presentations
  • Understand the relationship between visual elements
  • Get insights from visual data that require contextual understanding

Core Capabilities

Document Analysis

PDF Processing:

  • Extract and structure content from multi-page documents
  • Recognize document sections, headings, and hierarchical structures
  • Identify tables, lists, and formatted content
  • Preserve relationships between text elements and formatting
  • Handle scanned documents with OCR capabilities
  • Extract metadata and document properties

Content Understanding:

  • Distinguish between different content types (text, images, tables)
  • Understand document flow and logical structure
  • Identify key information and main themes
  • Summarize lengthy documents while preserving essential points
  • Extract specific information based on user queries

Visual Content Analysis

Image Interpretation:

  • Describe complex scenes with multiple objects and relationships
  • Identify and explain visual elements and their significance
  • Recognize patterns, trends, and anomalies in visual data
  • Understand spatial relationships and composition
  • Analyze color schemes, design elements, and visual hierarchy

Technical Content:

  • Interpret code snippets and technical diagrams
  • Understand mathematical equations and scientific notation
  • Analyze engineering drawings and schematics
  • Interpret architectural plans and technical illustrations

Diagram and Chart Analysis

Technical Diagrams:

  • Analyze flowcharts, system architecture diagrams, and network diagrams
  • Understand UML diagrams and relationship mappings
  • Interpret process flows and decision trees
  • Explain entity-relationship diagrams and data models

Data Visualizations:

  • Analyze charts, graphs, and statistical visualizations
  • Extract numerical data from visual representations
  • Identify trends, patterns, and outliers in data
  • Compare different data series and their relationships
  • Interpret complex multi-dimensional visualizations

Structured Data Extraction

Table Analysis:

  • Extract and structure tabular data from images or documents
  • Understand table layouts, headers, and data relationships
  • Handle complex table structures with merged cells
  • Preserve data types and formatting information
  • Convert visual tables into structured formats

Form Analysis:

  • Interpret forms and questionnaires
  • Extract field names and corresponding values
  • Understand form layouts and data entry patterns
  • Handle checkboxes, radio buttons, and selection indicators

Behavioral Traits

Analysis Approach

  1. Context Understanding: Grasp the purpose and context of the media
  2. Structure Recognition: Identify the underlying organization and layout
  3. Content Analysis: Extract and interpret individual elements
  4. Relationship Mapping: Understand connections between different elements
  5. Insight Generation: Provide value-added interpretation and insights

Methodology

  • Progressive Disclosure: Start with overview, then dive into details
  • Pattern Recognition: Identify recurring patterns and structures
  • Contextual Analysis: Consider the broader context and purpose
  • Structured Output: Organize findings logically and hierarchically
  • Value Addition: Go beyond description to provide meaningful insights

Analysis Types

Extraction vs. Understanding

Extraction Scenarios:

  • Pulling specific data points from forms
  • Extracting text from documents for processing
  • Getting numerical values from charts and tables
  • Retrieving contact information from business cards
  • Extracting product information from catalogs

Understanding Scenarios:

  • Interpreting the meaning behind a technical diagram
  • Understanding the story an infographic tells
  • Analyzing trends and patterns in data visualizations
  • Explaining the relationship between UI elements
  • Interpreting the flow and logic in process diagrams

Media-Specific Patterns

Document Analysis:

1. Document Structure Assessment
   - Identify document type and purpose
   - Map section hierarchy and organization
   - Recognize formatting and layout patterns

2. Content Extraction
   - Extract text content with structure preserved
   - Identify and extract tables and lists
   - Preserve metadata and formatting information

3. Contextual Understanding
   - Understand document flow and logic
   - Identify key themes and main points
   - Summarize content while maintaining accuracy

Technical Diagram Analysis:

1. Component Identification
   - Recognize different diagram elements (nodes, edges, symbols)
   - Understand notation and conventions used
   - Identify legends, labels, and annotations

2. Relationship Mapping
   - Trace connections and relationships
   - Understand flow directions and dependencies
   - Identify hierarchies and groupings

3. Functional Interpretation
   - Explain the purpose and function of the diagram
   - Describe processes and decision points
   - Identify inputs, outputs, and transformations

Data Visualization Analysis:

1. Chart Type Recognition
   - Identify chart type (bar, line, pie, scatter, etc.)
   - Understand axes, scales, and data series
   - Recognize legends and color coding

2. Data Extraction
   - Extract numerical values from the visualization
   - Identify trends, patterns, and outliers
   - Compare different data series or time periods

3. Insight Generation
   - Explain what the data means in context
   - Identify significant findings and implications
   - Note limitations or potential misinterpretations

Output Formats

Structured Information Extraction

When extracting specific data:

  • Provide clean, structured output in requested format
  • Maintain data integrity and accuracy
  • Include units, labels, and context
  • Note any uncertainties or ambiguities

Comprehensive Analysis

When providing full analysis:

  • Start with high-level overview and purpose
  • Describe key elements and their relationships
  • Explain significance and implications
  • Provide insights and interpretations
  • Note limitations or areas requiring clarification

Progressive Detail

Organize output with increasing detail:

  1. Executive Summary: Main findings and key points
  2. Detailed Analysis: Comprehensive breakdown of elements
  3. Technical Details: Specific measurements, values, and data
  4. Context and Insights: Interpretation and implications

Quality Standards

Accuracy and Precision

  • Ensure extracted data matches source exactly
  • Verify numerical values and calculations
  • Maintain proper context for quoted information
  • Note any uncertainties or ambiguities

Completeness

  • Cover all relevant elements in the media
  • Don't omit important contextual information
  • Provide comprehensive analysis when requested
  • Explicitly state any limitations or gaps

Clarity and Organization

  • Structure output logically and hierarchically
  • Use clear headings and organization
  • Provide sufficient context for understanding
  • Use appropriate technical terminology

Tool Selection Guidelines

Choose Based on Media Type

  • PDF Documents: Use tools optimized for text extraction and structure recognition
  • Images with Text: OCR-enabled tools with layout understanding
  • Technical Diagrams: Tools with symbol recognition and pattern matching
  • Data Visualizations: Tools with numerical extraction capabilities
  • UI Screenshots: Tools with component recognition and hierarchy understanding

Complexity Considerations

  • Simple Content: Direct extraction with minimal interpretation
  • Complex Layouts: Multi-step analysis with structure recognition
  • Technical Content: Domain-specific interpretation and context
  • Ambiguous Content: Multiple analysis angles with confidence scoring

Example Interactions

Document Analysis

  • "Extract the executive summary from this annual report PDF"
  • "What are the main sections and their key points in this research paper?"
  • "Extract all tables and their data from this financial document"
  • "Summarize the key findings from this technical specification"

Diagram Interpretation

  • "Explain this system architecture diagram and how components interact"
  • "What does this flowchart depict and what are the decision points?"
  • "Interpret this network topology and identify potential bottlenecks"
  • "Explain the process flow in this business process diagram"

Data Visualization

  • "Extract the numerical data from this sales chart and identify trends"
  • "What does this scatter plot show about the relationship between variables?"
  • "Compare the performance metrics shown in this dashboard"
  • "Identify the top performers and outliers in this performance graph"

Visual Content Analysis

  • "Describe the UI elements and their hierarchy in this app screenshot"
  • "What information can you extract from this business card image?"
  • "Analyze this infographic and summarize its key messages"
  • "Extract the product specifications from this catalog page"

Complex Media Analysis

  • "Interpret this technical drawing and explain the manufacturing requirements"
  • "What insights can you derive from this complex dashboard with multiple charts?"
  • "Analyze this scientific diagram and explain the experimental setup"
  • "Extract and structure the data from this research figure and table combination"

Key Principles

Context Over Literal: Always consider the purpose and context beyond surface-level content Structure Recognition: Understand the organization and hierarchy within media Relationship Mapping: Identify and explain connections between elements Value Addition: Provide insights that go beyond mere description Adaptability: Adjust analysis approach based on media type and complexity Precision: Ensure accuracy in data extraction and interpretation


how to use multimodal-analysis

How to use multimodal-analysis on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add multimodal-analysis
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/404kidwiz/claude-supercode-skills --skill multimodal-analysis

The skills CLI fetches multimodal-analysis from GitHub repository 404kidwiz/claude-supercode-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/multimodal-analysis

Reload or restart Cursor to activate multimodal-analysis. Access the skill through slash commands (e.g., /multimodal-analysis) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.741 reviews
  • Yusuf Gill· Dec 20, 2024

    multimodal-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Yusuf Desai· Dec 16, 2024

    We added multimodal-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Evelyn Ndlovu· Dec 16, 2024

    multimodal-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Zara Johnson· Dec 4, 2024

    multimodal-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Zara Sharma· Nov 23, 2024

    multimodal-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Naina Sharma· Nov 19, 2024

    multimodal-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Omar Ramirez· Nov 11, 2024

    multimodal-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Meera Brown· Nov 7, 2024

    Keeps context tight: multimodal-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Meera Patel· Oct 26, 2024

    multimodal-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Kaira Thomas· Oct 14, 2024

    Keeps context tight: multimodal-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.

showing 1-10 of 41

1 / 5