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Research Paper Writing

master-cai/research-paper-writing-skills
314 installs3.2k stars
Summary

This is a structured workflow for turning messy academic drafts into reviewer-ready papers, focused on ML/CV/NLP submissions. It enforces one-message-per-paragraph discipline, runs reverse outlining after each section, and includes adversarial self-review checklists before you submit. The approach treats figures and tables as first-class content, not decoration, and maps every major claim in your abstract and intro back to experimental evidence. It's opinionated about paragraph flow (cause, contrast, consequence, refinement) and comes with section-specific guides for introduction, method, experiments, and related work. Use it when you're past the idea stage but your draft still reads like patchwork or when you need to harden claims before sending to reviewers.

Install to Claude Code

npx -y skills add master-cai/research-paper-writing-skills --skill research-paper-writing --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

Research Paper Writing

Overview

Use this skill to rewrite a research paper into a reviewer-friendly, high-clarity draft. Prioritize first-impression quality (figures/tables/layout), logical flow, and evidence-backed claims.

Core Workflow

  1. Clarify the paper story before sentence-level edits.
  2. Use section-specific guidance in references/.
  3. Rewrite paragraph-by-paragraph with one message per paragraph.
  4. Run reverse outlining after writing each section.
  5. Check every major claim in Abstract/Introduction against experimental evidence.
  6. Run final-paper adversarial review with references/paper-review.md.

Global Principles

  1. Keep one paragraph for one message only.
  2. State the paragraph message in the first sentence.
  3. Make nouns self-contained; define new terms before reusing them.
  4. Maintain sentence-to-sentence flow (cause, contrast, consequence, or refinement).
  5. Iterate with adversarial self-review: read as a skeptical reviewer.
  6. Treat visual quality as core content, not decoration.
  7. Use a clean teaser and pipeline figure.
  8. Use readable, minimal-ink tables.
  9. Keep formatting consistent and tidy.

Paragraph Clarity Check (Important)

Use this quick test whenever the user asks whether a paragraph "flows" or is clear.

  1. Read as an external reader:
    • Does this paragraph have one explicit message?
    • Does the first sentence state what this paragraph will do?
    • Are all key nouns/terms readable without hidden context?
    • Does each sentence connect to the previous one with a clear relation (cause, contrast, consequence, refinement, example)?
  2. Run reverse outlining for the current section:
    • Write down thesis/main claim.
    • Write down each paragraph topic sentence.
    • Write down the evidence/explanation points under each paragraph.
    • Check mapping: topic sentence -> thesis, and evidence -> topic sentence.
    • Revise or remove any paragraph that cannot be mapped cleanly.
  3. If flow is still weak, add temporary section headers and explicit transition phrases during revision, then remove unnecessary headers before finalizing.

Source reference for this check:

  • references/does-my-writing-flow-source.md

Section Guides

Load only the needed section file:

  • Introduction: references/introduction.md
  • Abstract: references/abstract.md
  • Related Work: references/related-work.md
  • Method: references/method.md
  • Experiments: references/experiments.md
  • Conclusion: references/conclusion.md
  • Paper review (Paper Review): references/paper-review.md
  • Paragraph clarity source: references/does-my-writing-flow-source.md
  • Example bank index: references/examples/index.md

Paper Review Core Points

Use references/paper-review.md for the full checklist and workflow.

  1. Add an end-of-draft self-review question list in five dimensions:
    • contribution,
    • writing clarity,
    • experimental strength,
    • evaluation completeness,
    • method design soundness.
  2. Treat claim-evidence alignment as a hard constraint, especially for Abstract and Introduction.
  3. Perform adversarial writing: review as a skeptical reviewer and resolve every high-risk question.
  4. Revise until major rejection risks are explicitly addressed.

Execution Rules

  1. Build a mini-outline before drafting prose.
  2. For each subsection, explicitly include motivation, design, and technical advantage when applicable.
  3. Avoid writing style that looks like incremental patching of a naive baseline.
  4. Keep terminology stable across the full paper.
  5. If a claim cannot be supported by results, weaken or remove the claim.
  6. Before finalizing, append and answer a five-dimension self-review question list, then revise the paper based on unresolved items.
  7. Do not load all section references (Introduction/Abstract/Related Work/Method/Experiments/Conclusion) at once; load only the specific section guide needed for the current edit target.

Output Contract

When asked to rewrite or draft sections, return:

  1. A compact section outline (3-7 bullets).
  2. Revised paragraphs with explicit paragraph roles (opening/challenge/method/advantage/evidence/limitation).
  3. A short self-review checklist covering clarity, flow, terminology consistency, unsupported claims, and missing evidence.
  4. A claim-evidence map for each major claim in the revised text using Claim: ... | Evidence: ... | Status: supported/needs evidence.
Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
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Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
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Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
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AppSignal
AppSignal
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Categories
DocumentationSkill DevelopmentData Science & ML
First SeenJun 3, 2026
View on GitHub

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