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Sci Review

Community
ShZhao27208
sci-review

Specialized workflows for drafting, refining, and responding to academic literature reviews and peer review feedback. Use this skill for literature review outlines, research-gap synthesis, reviewer rebuttals, response letters, and academic writing tone repair.

Overview

PublisherShZhao27208
RepositoryAut_Sci_Write
Skill namesci-review
Stars
211
Forks
28
Bundled files
8
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.

  • 8 bundled files

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

  • Open source

    Published by ShZhao27208 on GitHub. Read the source before you install it.

Installation

Install the Sci Review 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/ShZhao27208/Aut_Sci_Write/tree/main/skills/sci-review
  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/ShZhao27208/Aut_Sci_Write.git /tmp/Aut_Sci_Write
mkdir -p .claude/skills
cp -r /tmp/Aut_Sci_Write/skills/sci-review .claude/skills/sci-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sci Review 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 Sci Review 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 Sci Review 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.

Sci-Review

Use this skill to produce structured literature-review writing and professional reviewer responses.

Literature Review Structure

Use this four-part structure unless the user requests a different journal format:

  1. Introduction: background, problem definition, gap identification, and contribution.
  2. Methodology: taxonomy, method classes, comparison dimensions, and performance evidence.
  3. Challenges: phenomenon, cause, and direction. Make the problem visible before proposing a route forward.
  4. Conclusion: distilled insights and a future roadmap.

Prefer specific evidence over broad claims. Replace vague phrases such as "significantly better" with measured comparisons when data is available.

Rebuttal Structure

For each reviewer point, use:

  1. Reviewer concern: restate the concern accurately and neutrally.
  2. Response: answer with evidence, clarification, or a limitation acknowledgement.
  3. Revision plan: state the exact manuscript change, including section, table, figure, appendix, or experiment when possible.

Avoid adversarial phrasing such as "reviewer misunderstood" or "the reviewer is wrong". Use constructive language such as "we will clarify this point in the manuscript" or "we agree that additional evidence would improve the presentation".

Validation

The skill includes a lightweight validator. Run from the skills/sci-review/ directory:

bash
# From the skills/sci-review/ directory:
python scripts/validate_review_output.py --case literature-review --output output.md
python scripts/validate_review_output.py --case rebuttal --output output.md
python scripts/validate_review_output.py --list-golden

The validator checks required section names and banned phrases. Golden cases live in tests/golden_cases.json; they define expected output features rather than exact wording.

Best Practices

  • Read the source literature, reviewer comments, or draft before rewriting.
  • Preserve technical nuance. Do not invent experiments, results, baselines, or citations.
  • Mark uncertainty explicitly when source evidence is missing.
  • Keep tone professional, direct, and evidence-driven.

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 Sci Review AI skill do?

Specialized workflows for drafting, refining, and responding to academic literature reviews and peer review feedback. Use this skill for literature review outlines, research-gap synthesis, reviewer rebuttals, response letters, and academic writing tone repair.

Why use Sci Review on TypingMind?

Because you install it once and use it with any model. Sci Review 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 Sci Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ShZhao27208/Aut_Sci_Write/tree/main/skills/sci-review. 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 Sci Review?

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 Sci Review?

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

Is the Sci Review AI skill free?

Yes. It is published on GitHub by ShZhao27208 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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