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Research Paper Writing

CommunityPopular
Master-cai
research-paper-writing

Improve academic paper writing quality for ML/CV/NLP-style papers with clear section structure, paragraph flow, and reviewer-facing presentation. Use when drafting or revising Abstract, Introduction, Related Work, Method, Experiments, or Conclusion; polishing figures/tables; checking claim-support alignment; or performing self-review before submission.

Overview

PublisherMaster-cai
RepositoryResearch-Paper-Writing-Skills
Skill nameresearch-paper-writing
Stars
6.9K
Forks
328
Bundled files
38
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 38 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Master-cai on GitHub. Read the source before you install it.

Installation

Install the Research Paper Writing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Master-cai/Research-Paper-Writing-Skills.git /tmp/Research-Paper-Writing-Skills
mkdir -p .claude/skills
cp -r /tmp/Research-Paper-Writing-Skills/research-paper-writing .claude/skills/research-paper-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Paper Writing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Research Paper Writing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Research Paper Writing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Research Paper Writing AI skill do?

Improve academic paper writing quality for ML/CV/NLP-style papers with clear section structure, paragraph flow, and reviewer-facing presentation. Use when drafting or revising Abstract, Introduction, Related Work, Method, Experiments, or Conclusion; polishing figures/tables; checking claim-support alignment; or performing self-review before submission.

Why use Research Paper Writing on TypingMind?

Because you install it once and use it with any model. Research Paper Writing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Research Paper Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Master-cai/Research-Paper-Writing-Skills/tree/main/research-paper-writing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Research Paper Writing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Research Paper Writing?

As many as you like. As long as a model supports skills, you can use Research Paper Writing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Research Paper Writing AI skill free?

Yes. It is published on GitHub by Master-cai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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