Write, structure, or revise academic paper sections, keep notation consistent, refine figures and tables, and set up or fix the LaTeX build (TeX distribution, biber vs bibtex, venue templates, compilation). Use when the user says "write the abstract", "structure the methods", "improve this section", "notation consistency", "figure refinement", "paper structure", "setup latex", "biber vs bibtex", "latex compilation error", "install latex packages", "venue template", or "texlive setup".
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SKILL.md, read when the skill is used
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Install
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Paper Write: academic paper writing and LaTeX setup
For LaTeX environment setup, biber vs bibtex, venue templates and compilation, follow references/latex.md.
Core Principles
Precision over elegance. Every claim traces to code, data or a cited source.
Conciseness. Remove words that don't add information.
Writing Process
Read first. Always read the existing section before writing.
Identify the claim. What is this paragraph trying to say?
Find the evidence. Where in code/results does this come from?
Write the text. State claim, present evidence, interpret.
Verify. Re-read against source to catch any drift, then compile with the project pipeline from references/latex.md Step 5 and fix any error before the next edit.
Section-Specific Guidance
Abstract
Structure: problem → approach → key result → significance
Include 1-2 concrete numbers (dataset size, main metric improvement)
Every number must be traceable to a specific experiment
No citations in abstract unless venue requires it
Introduction
Paragraph 1: Problem and why it matters (societal/practical motivation)
Paragraph 2: Why existing approaches are insufficient (gap)
Paragraph 3: Your approach and why it addresses the gap
Paragraph 4: Contributions list (concrete, falsifiable claims)
Each contribution must map to a section that provides evidence
Related Work
Organize by theme/approach, not chronologically
For each group: what they do, what's missing, how your work differs
Be fair: acknowledge strengths of prior work, don't strawman
End each paragraph with how your work addresses the limitation
Methods
Define all notation in a single place (notation table or first-use definitions)
Each method component should be independently understandable
Include enough detail that someone could reimplement from the paper
Cross-reference equations with corresponding code
Experiments
Dataset: size, splits, preprocessing (cite or describe collection)
Metrics: define formally, explain why these metrics