Brainstorming for Academic Writing

Overview

Help generate a well-structured outline for academic papers through collaborative dialogue. Start by understanding the research topic and requirements, then develop a logical paper structure following academic conventions.

The Process

Understanding the research:

•Review the requirement file (title, topic, length, style, references)
•Ask clarifying questions about the research focus and objectives
•Identify the target venue/journal and its typical structure requirements

Exploring structure approaches:

•Propose 2-3 different outline structures with trade-offs
•Consider IMRAD (Introduction, Methods, Results, Discussion) or alternative formats
•Present options conversationally with recommendations

Presenting the outline:

•Once the topic is understood, present the structured outline
•Break it into sections with key points for each section
•Include suggested subsections and content hints
•Ask whether the structure looks appropriate

Key Principles

•Academic structure - Follow IMRAD or discipline-specific conventions
•One question at a time - Don't overwhelm with multiple questions
•Multiple choice preferred - Easier to answer than open-ended when possible
•YAGNI ruthlessly - Remove unnecessary sections from the outline
•Incremental validation - Present outline in sections, validate each
•Be flexible - Go back and adjust when structure doesn't fit

Output Format

markdown

# Paper Outline

## 1. Introduction
- Context and background
- Research problem statement
- Gap in current knowledge
- Study objectives/research questions

## 2. Related Work
- Key prior studies
- Current approaches and limitations
- How this work advances the field

## 3. Methods
- Study design
- Data collection
- Analysis approach
- Rationale for chosen methods

## 4. Results
- Primary findings
- Secondary outcomes
- Statistical significance

## 5. Discussion
- Interpretation of results
- Comparison with prior work
- Limitations
- Implications and future directions

## 6. Conclusion
- Key contributions summary
- Broader impact

## References
- Primary citations

Integration

Uses Sub-Skills

•None (standalone skill for outline generation)

Input Format

markdown

{
  "requirement": {
    "title": "Paper Title",
    "topic": "Research topic description",
    "length": 3000,
    "style": "academic",
    "background": "Optional background context",
    "outline_hints": "Optional structural preferences"
  }
}

Output Format

markdown

{
  "outline": {
    "sections": [
      {
        "title": "Section Title",
        "key_points": ["Point 1", "Point 2", ...],
        "content_hints": "Optional guidance for writing"
      }
    ],
    "total_sections": 5,
    "estimated_words": 3000
  }
}

Example

markdown

Input:
{
  "requirement": {
    "title": "Deep Learning for Image Classification",
    "topic": "CNN architectures for medical image diagnosis",
    "length": 2500,
    "style": "academic"
  }
}

Output:
# Paper Outline: Deep Learning for Image Classification

## 1. Introduction
- Medical imaging challenges
- Deep learning potential for diagnosis
- Research objectives

## 2. Related Work
- CNN evolution (LeNet, AlexNet, VGG)
- Medical imaging applications
- Diagnostic accuracy studies

## 3. Methods
- Dataset description
- Architecture choices
- Training procedure
- Evaluation metrics

## 4. Results
- Classification accuracy
- Comparison with baselines
- Sensitivity analysis

## 5. Discussion
- Clinical implications
- Limitations
- Future directions