Research Integration Skill

Provides AI with cross-disciplinary research insights and mental models to help users grow.

Core Capabilities

1. Research Knowledge Retrieval: Retrieves most relevant research insights and mental models based on problem context
2. Mental Model Application: Provides 20+ structured thinking tools
3. Insight Composition Engine: Automatically combines multiple insights to form analytical frameworks
4. Practical Case Library: Provides real-world application examples

Five Core Research Areas

This skill integrates 50 years of research in the following five areas:

• AI/ML: Artificial Intelligence and Machine Learning
• Entrepreneurship: Entrepreneurship and Innovation Management
• Automation/HCI: Automation and Human-Computer Interaction
• Organizational Behavior: Organizational Behavior and Team Collaboration
• Software Engineering: Software Engineering and Product Development

Quick Start

1. Retrieve Research Insights

When users ask questions, automatically identify relevant areas and retrieve:

User: "How should I validate my startup idea?"
→ Retrieve Lean Startup, Effectuation, customer development theories
→ Recommend applicable mental models: Lean Canvas, MVP Framework
→ Provide practical advice and examples

2. Apply Mental Models

Recommend appropriate thinking tools based on problem type:

• Strategic Decisions → First Principles, Second-Order Thinking, SWOT
• Product Design → User Journey Map, Minimum Viable Product
• Growth Optimization → AARRR Funnel, North Star Metric
• Organization Management → OKRs, Team Topologies

3. Compose Analytical Frameworks

For complex problems, combine multiple models:

Market Entry Decision
= Porter's Five Forces (Industry Analysis)
+ SWOT (Competitive Positioning)
+ Lean Canvas (Hypothesis Validation)
+ Unit Economics (Financial Viability)

Directory Structure

research-integration/
├── SKILL.md (this file)
└── references/
    ├── ai-ml/                    # AI/ML Area
    │   ├── foundational-papers.md
    │   ├── key-insights.md
    │   └── mental-models.md
    ├── entrepreneurship/         # Entrepreneurship Area
    │   ├── foundational-papers.md
    │   ├── key-insights.md
    │   └── mental-models.md
    ├── automation-hci/           # Automation/HCI Area
    │   ├── foundational-papers.md
    │   ├── key-insights.md
    │   └── mental-models.md
    ├── organizational-behavior/  # Organizational Behavior Area
    │   ├── foundational-papers.md
    │   ├── key-insights.md
    │   └── mental-models.md
    └── software-engineering/     # Software Engineering Area
        ├── foundational-papers.md
        ├── key-insights.md
        └── mental-models.md

Usage Patterns

Pattern 1: On-Demand Loading (Recommended)

When needing to dive deep into an area:

1. View references/<area>/foundational-papers.md
2. Read relevant insights in key-insights.md
3. Apply mental models from mental-models.md

Pattern 2: Proactive Recommendation

Proactively recommend based on user questions:

User question → Identify area → Retrieve insights → Recommend models → Provide examples

Pattern 3: Composed Application

For complex problems:

1. Decompose problem dimensions
2. Select appropriate models for each dimension
3. Combine to form complete analytical framework
4. Provide implementation suggestions

Mental Model Library (20+)

Decision-Making Models

• First Principles Thinking
• Second-Order Thinking
• Inversion Thinking
• Map Is Not the Territory
• Minimize Surprises

Strategic Analysis Models

• SWOT Analysis
• Porter's Five Forces
• Ansoff Matrix
• PEST Analysis

Product & Growth Models

• Lean Canvas
• Business Model Canvas
• AARRR Funnel
• North Star Metric
• User Journey Map

Organization Management Models

• OKR Framework
• Team Topologies
• MTF Analysis
• Unit Economics

Best Practices

1. Framework Before Details: Recommend models first, then dive into insights
2. Theory + Practice: Pair every theory with examples
3. Explicit Limitations: Label inapplicable scenarios
4. Continuous Updates: Iterate based on user feedback

Trigger Keywords

This skill automatically activates when:

• "how to make decisions"
• "what analysis methods"
• "market analysis"
• "business model"
• "learn XX theory"
• "thinking frameworks"
• "user growth strategy"
• "product development methods"
• "team management"
• "strategic planning"

Limitations & Notes

1. Knowledge Cutoff: This skill is based on public research before 2024
2. Area Coverage: Primarily focuses on business and technology areas
3. Cultural Adaptation: Some models may need adjustment for local markets
4. Update Frequency: Core insights are stable, examples need regular updates

Extension Suggestions

To extend this skill:

1. Add new research areas to references/
2. Add papers and insights in existing format
3. Add new models in mental-models.md
4. Update usage guide in this file

Related Skills

• Product Development Skill: Apply theories from this skill to specific products
• Marketing Growth Skill: Combine with marketing research insights
• Decision Support Skill: Deepen decision framework application

Interface Definition

Metadata

{
  "name": "research-integration",
  "version": "2.0.0",
  "description": "Integrates 50 years of cross-disciplinary academic research for actionable insights",
  "author": "SOLO CORN SKILLS",
  "category": ["research", "insights"],
  "tags": ["research-integration", "mental-models", "academic-insights"]
}

Input Schema

{
  "inputs": [
    {
      "name": "question",
      "type": "string",
      "required": true,
      "description": "Question or problem to research"
    },
    {
      "name": "area",
      "type": "string",
      "required": false,
      "description": "Research area (ai-ml, entrepreneurship, automation-hci, organizational-behavior, software-engineering)"
    }
  ]
}

Output Schema

{
  "outputs": [
    {
      "name": "insights",
      "type": "array",
      "description": "Relevant research insights and findings"
    },
    {
      "name": "models",
      "type": "array",
      "description": "Applicable mental models"
    },
    {
      "name": "framework",
      "type": "object",
      "description": "Composed analytical framework"
    },
    {
      "name": "examples",
      "type": "array",
      "description": "Practical application examples"
    }
  ]
}

Invoke Method

async invoke(params: InvocationParams): Promise<SkillResult> {
  // Execute research integration
  // 1. Analyze question and identify relevant areas
  // 2. Retrieve research insights from knowledge base
  // 3. Select and apply appropriate mental models
  // 4. Compose analytical framework
  // 5. Return results with examples
}

Usage via CLI

# Basic invocation
scs invoke research-integration --input '{"question": "How to validate my startup idea"}'

# Interactive mode
scs invoke research-integration --interactive

# With specific area
scs invoke research-integration --input '{"question": "Team management", "area": "organizational-behavior"}'