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Paper Revision

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lingzhi227
paper-revision

Revise papers based on reviewer feedback. Map reviewer concerns to specific sections, apply targeted edits, run additional experiments if needed, and verify improvements. Use after receiving peer review with revision requests.

Overview

Publisherlingzhi227
Repositoryagent-research-skills
Skill namepaper-revision
Stars
426
Forks
46
Bundled files
1
Links
Skill sourceRepository
  • 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.

  • 1 bundled files

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

  • Open source

    Published by lingzhi227 on GitHub. Read the source before you install it.

Installation

Install the Paper Revision 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.
    https://github.com/lingzhi227/agent-research-skills/tree/main/skills/paper-revision
  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/lingzhi227/agent-research-skills.git /tmp/agent-research-skills
mkdir -p .claude/skills
cp -r /tmp/agent-research-skills/skills/paper-revision .claude/skills/paper-revision
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Revision 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 Paper Revision 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 Paper Revision 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.

Paper Revision

Systematically revise papers based on reviewer feedback.

Input

  • $0 — Reviewer comments/feedback
  • $1 — Current paper draft (main.tex or paper directory)

References

  • Revision workflow and prompts: ~/.claude/skills/paper-revision/references/revision-prompts.md

Workflow

Step 1: Parse and Prioritize Concerns

For each reviewer comment:

  1. Extract the specific concern
  2. Classify: major revision, minor revision, question, suggestion
  3. Map to affected paper section(s)
  4. Prioritize: address major concerns first

Step 2: Plan Revisions

Create a revision plan:

Concern → Affected Section → Required Action → New Content/Experiment

Categories of actions:

  • Clarification: Rewrite text for clarity
  • Additional experiment: Run new experiment, add results
  • New analysis: Add ablation, statistical test, or comparison
  • Structural change: Move, merge, or split sections
  • Citation: Add missing references

Step 3: Execute Revisions

For each planned revision:

  1. Read the current section
  2. Apply targeted edits (preserve surrounding structure)
  3. If new experiments needed: use experiment-code skill
  4. If new figures/tables needed: use figure-generation / table-generation skills
  5. Mark changes (use \textcolor{blue}{...} for revised text)

Step 4: Verify Improvements

  • Re-run self-review skill to check if scores improved
  • Verify all reviewer concerns are addressed
  • Check that revisions don't introduce new issues
  • Ensure page count still fits venue requirements

Step 5: Write Revision Summary

Generate a diff summary:

  • List all changes made with section references
  • Note any new experiments, figures, or tables added
  • Cross-reference each change to the reviewer concern it addresses

Rules

  • Address EVERY reviewer concern — do not skip any
  • Preserve paper structure unless structural change is explicitly needed
  • New results must come from actual experiments, not hallucinated
  • Mark all revised text clearly for the reviewers
  • Keep a copy of the previous version before revising
  • Compare new scores vs previous scores after revision

Related Skills

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 Paper Revision AI skill do?

Revise papers based on reviewer feedback. Map reviewer concerns to specific sections, apply targeted edits, run additional experiments if needed, and verify improvements. Use after receiving peer review with revision requests.

Why use Paper Revision on TypingMind?

Because you install it once and use it with any model. Paper Revision 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 Paper Revision in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lingzhi227/agent-research-skills/tree/main/skills/paper-revision. 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 Paper Revision?

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 Paper Revision?

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

Is the Paper Revision AI skill free?

It is published on GitHub by lingzhi227. Check the repository for licensing terms. 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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