Paper Writing Assistant Skill

Value Proposition

Transforms raw experimental data and informal notes into high-quality academic text suitable for paper submissions or professor meetings.

When to Use

• Drafting Sections: When the user asks to write "Abstract", "Methodology", or "Results".
• Meeting Prep: When creating summaries for advisor meetings (e.g., "Prepare for the Friday meeting").
• Reformatting: When converting code comments or rough notes into LaTeX or polished Markdown.

Instructions

1. Structure: Adhere to the user's preferred structure:
   • Background: Context of the problem.
   • Analysis: Method of investigation.
   • Findings: Data-backed results.
   • Conclusion: Summary and next steps.
2. Data First: Always prioritize quantitative data (metrics, tables) over qualitative descriptions.
3. Comparison: When comparing models, use tables.
   • Compare parameters, training data size, inference speed, and accuracy.
4. Citations: Use standard citation markers (e.g.,

   [Author, Year]

   ) or BibTeX keys if provided.

Best Practices

• Visuals: Suggest placeholder figures where data is dense (e.g.,

  [Figure 1: Success Rate vs Training Steps]

  ).
• Tone: Maintain a formal, academic tone. Avoid slang or overly casual language.
• LaTeX Support: Be ready to generate LaTeX snippets for tables and equations.