| name | write_skill |
| description | Academic writing skill for generating summaries, reports, literature reviews, and other research documents |
| version | 1.0.0 |
| author | PaperAgent Team |
Academic Writing Skill
This skill enables you to generate various types of academic writing, including summaries, literature reviews, research reports, and other scholarly documents. Use this skill when you need to produce well-structured academic content.
Available Tools
You have access to the following writing tools (registered in the Toolkit):
1. generate_summary
Generate a concise summary of given text.
Parameters:
text (str, required): Text to summarize
max_length (int, optional): Maximum length in words (default: 500)
style (str, optional): "academic", "casual", "technical" (default: "academic")
language (str, optional): Output language - "zh" or "en" (default: "zh")
Returns: Generated summary text.
Example:
generate_summary(
text=paper_abstract,
max_length=200,
style="academic",
language="zh"
)
2. generate_report_section
Generate a specific section of an academic report.
Parameters:
topic (str, required): Topic of the section
content (str, required): Source content or context
section_type (str, optional): "introduction", "body", "conclusion", "abstract", "methodology", "results", "discussion" (default: "body")
language (str, optional): Output language (default: "zh")
Returns: Generated section content.
Example:
generate_report_section(
topic="Transformer Architecture",
content=research_notes,
section_type="introduction",
language="en"
)
3. generate_literature_review
Generate a literature review from a set of papers.
Parameters:
papers (list[dict], required): List of paper metadata with abstracts
focus_topic (str, required): Central topic or research question
structure (str, optional): "thematic", "chronological", "methodological" (default: "thematic")
length (str, optional): "short", "medium", "long" (default: "medium")
language (str, optional): Output language (default: "zh")
Returns: Structured literature review with proper citations.
Example:
generate_literature_review(
papers=paper_list,
focus_topic="Applications of LLMs in Scientific Research",
structure="thematic",
length="long",
language="zh"
)
4. generate_outline
Generate an outline for a research document.
Parameters:
topic (str, required): Document topic
document_type (str, optional): "paper", "thesis", "report", "proposal" (default: "paper")
depth (int, optional): Outline depth level (default: 3)
language (str, optional): Output language (default: "zh")
Returns: Hierarchical outline structure.
Example:
generate_outline(
topic="Deep Learning for Drug Discovery",
document_type="paper",
depth=3,
language="en"
)
5. polish_text
Polish and improve existing text.
Parameters:
text (str, required): Text to polish
focus (str, optional): "grammar", "clarity", "conciseness", "academic_tone", "all" (default: "all")
preserve_meaning (bool, optional): Strictly preserve original meaning (default: True)
language (str, optional): Text language (default: "zh")
Returns: Polished text with optional change annotations.
Example:
polish_text(
text=draft_paragraph,
focus="academic_tone",
preserve_meaning=True,
language="en"
)
6. translate_academic
Translate academic text with domain awareness.
Parameters:
text (str, required): Text to translate
source_lang (str, required): Source language ("zh" or "en")
target_lang (str, required): Target language ("zh" or "en")
domain (str, optional): Academic domain for terminology (e.g., "computer_science", "biology")
Returns: Translated text preserving academic style and terminology.
Example:
translate_academic(
text=chinese_abstract,
source_lang="zh",
target_lang="en",
domain="computer_science"
)
7. generate_abstract
Generate an abstract for a research paper.
Parameters:
title (str, required): Paper title
content (str, required): Paper content or detailed notes
max_words (int, optional): Maximum words (default: 250)
structure (str, optional): "structured" (with sections) or "unstructured" (default: "unstructured")
language (str, optional): Output language (default: "en")
Returns: Generated abstract.
Example:
generate_abstract(
title="A Novel Approach to Neural Machine Translation",
content=full_paper_content,
max_words=300,
structure="structured",
language="en"
)
8. generate_related_work
Generate a related work section.
Parameters:
papers (list[dict], required): Related papers with metadata
own_contribution (str, required): Description of your own contribution
comparison_focus (str, optional): What to focus comparison on
language (str, optional): Output language (default: "zh")
Returns: Related work section with proper positioning.
Example:
generate_related_work(
papers=related_papers,
own_contribution="We propose a novel attention mechanism...",
comparison_focus="efficiency and scalability",
language="en"
)
Writing Styles
Academic Style
- Formal language
- Third person perspective
- Precise terminology
- Hedging language where appropriate
- Proper citations
Technical Style
- Focus on implementation details
- Code examples where relevant
- Precise specifications
- Step-by-step explanations
Casual Style
- More accessible language
- First/second person allowed
- Simplified explanations
- Engaging narrative
Document Structure Templates
Research Paper
- Abstract
- Introduction
- Related Work
- Methodology
- Experiments
- Results
- Discussion
- Conclusion
- References
Literature Review
- Introduction
- Search Methodology
- Thematic Analysis
- Synthesis and Gaps
- Conclusion
- References
Technical Report
- Executive Summary
- Introduction
- Background
- Methods
- Results
- Discussion
- Recommendations
- Appendices
Best Practices
- Provide rich context: The more context you provide, the better the output
- Specify structure: Indicate desired organization upfront
- Review and iterate: Use generated content as a starting point
- Check citations: Verify all referenced works exist
- Maintain consistency: Keep terminology consistent throughout
- Consider audience: Adjust style based on target readers
- Verify facts: LLM-generated content may contain errors
Output Format
All generated content is in markdown format with:
- Proper heading hierarchy
- Citation placeholders [1], [2], etc.
- Emphasis using bold and italic
- Lists for enumeration
- Block quotes for key points