Academic Writing Workflow

Name: academic-writing-workflow
Rating: 65
Author: hyperbolic-c

Overview

Main workflow skill that orchestrates the complete academic writing process: parse requirements, search references, parse papers, and generate academic writing output.

When to Use

•User confirms requirement file and wants to proceed with writing
•This is the main entry point for the academic writing process

Workflow Steps

code

1. Parse Requirements
   └── requirement-parser skill

2. Generate Outline
   └── brainstorming skill (built-in)
   └── Create structured outline based on topic

3. Search References
   └── reference-manager skill
   └── Multi-phase retrieval + PDF parsing

4. Generate Paper
   └── paper-writer skill
   └── Built-in academic writing capabilities

5. Output Result
   └── Return output file path

Input Format

markdown

{
  "requirement_file_path": "./path/to/requirement.md",
  "skip_outline_confirmation": false,
  "skip_reference_confirmation": true
}

Output Format

markdown

**学术写作流程完成**

**输出文件:** {output_path}

**写作统计:**
- 标题: {title}
- 目标字数: ~{length}
- 风格: {style}
- 参考文献: {n} 篇
- 生成字数: ~{actual_length}

**建议下一步:**
- [审阅] 查看生成的论文
- [修改] 提出修改意见
- [导出] 导出为其他格式

Integration Points

Requires Sub-Skills

•brainstorming - For outline generation (built-in)
•requirement-parser - For parsing requirements
•reference-manager - For reference management
•paper-writer - For paper generation (includes writing capabilities)

Output Format for Next Steps

This skill passes structured data to downstream skills:

python

{
  "requirement": Requirement,
  "outline": Outline,
  "references": List[Reference],
  "output_path": str
}

Error Handling

•Requirement parse error: Return error details
•Reference search failed: Report and suggest alternatives
•Paper generation failed: Return partial results + error
•File write error: Report and suggest retry

Example

markdown

Input: {"requirement_file_path": "./requirements.md"}

Output:
**学术写作流程完成**

**输出文件:** ./output/deep-learning-paper.md

**写作统计:**
- 标题: Deep Learning for Image Classification
- 目标字数: ~2000
- 风格: academic
- 参考文献: 15 篇
- 生成字数: ~2150

**建议下一步:**
- [审阅] 查看生成的论文
- [修改] 提出修改意见
- [导出] 导出为其他格式