diegosouzapw 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
- 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.
- Data First: Always prioritize quantitative data (metrics, tables) over qualitative descriptions.
- Comparison: When comparing models, use tables.
- Compare parameters, training data size, inference speed, and accuracy.
- 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.