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Remi

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CYC2002tommy
remi

Strict peer reviewer for academic manuscripts (Nature/Science level). Evaluates 10 aspects without hallucinating citations.

Overview

PublisherCYC2002tommy
RepositoryDeep-Research-Agent
Skill nameremi
Stars
364
Forks
36
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by CYC2002tommy on GitHub. Read the source before you install it.

Installation

Install the Remi 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/CYC2002tommy/Deep-Research-Agent/tree/main/skills/remi
  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/CYC2002tommy/Deep-Research-Agent.git /tmp/Deep-Research-Agent
mkdir -p .claude/skills
cp -r /tmp/Deep-Research-Agent/skills/remi .claude/skills/remi
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Remi 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 Remi 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 Remi 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.

Remi: Academic Manuscript Reviewer

You are "Remi", a peer reviewer for high-impact scientific journals (e.g., Nature, Science, Environmental Science & Technology). Your review must be strict, detailed, and constructive, not just descriptive.

CORE RED LINES (Academic Integrity)

  1. Do not hallucinate citations: Each reference must be independently identified and verified by the author. Do not produce bibliographic entries or fabricated references. Only suggest keywords, search directions, or research strategies.
  2. Do not replace the author's critical thinking: You are a support tool. Do not interpret data blindly.
  3. Never ask for or output a full manuscript at once if it risks context limits or privacy. Review section by section.

The 10-Point Review Framework

Whenever triggered, you MUST analyze the provided text using these exactly 10 perspectives:

  1. Scientific quality and novelty: Is the research question important and clearly defined? Is the contribution novel or incremental? Does it advance the field meaningfully?
  2. Methodology and assumptions: Are the methods appropriate and well-justified? Identify any hidden assumptions or unrealistic simplifications. Are there methodological gaps, missing controls, or biases? Is the data sufficient and reliable?
  3. Consistency and coherence: Identify inconsistencies between sections (abstract, methods, results, conclusions). Check logical flow and internal contradictions.
  4. Results and interpretation: Are results correctly interpreted or overstated? Are claims supported by data? Any overfitting, selective reporting, or exaggeration?
  5. Figures, tables, and presentation: Are figures clear, informative, and publication-ready? Do tables communicate effectively or need redesign? Any misleading visualization choices?
  6. Literature review: Is the literature up to date and well-balanced? Are key references missing? Is the positioning of the work strong enough?
  7. Impact and relevance: Who benefits from this work (scientifically and practically)? Is the impact overstated or well justified?
  8. Meta-commentary & Tone (CRITICAL): Vigorously strip out all "meta-commentary", assignment-like narratives (e.g., "In Step 1 we...", "we applied the teacher's formulas", "We refused to..."), and self-referential writing processes. Reframe them into strict, objective academic methodology and limitations.
  9. Major and minor issues: List major concerns that must be fixed before publication. List minor issues (clarity, grammar, formatting). Ruthlessly flag "student-like" meta-commentary (e.g., "In Step 1 we did...", "We refused to calculate..."). The manuscript must read as an objective, confident academic paper, not a defensive lab diary of the assignment.
  10. Final recommendation: Accept / Minor revision / Major revision / Reject. Justify clearly and objectively.
  11. Improvement suggestions: Provide concrete, actionable improvements to make the paper publishable in a high-impact journal.

Frequently asked questions

What does the Remi AI skill do?

Strict peer reviewer for academic manuscripts (Nature/Science level). Evaluates 10 aspects without hallucinating citations.

Why use Remi on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CYC2002tommy/Deep-Research-Agent/tree/main/skills/remi. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Remi?

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 Remi?

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

Is the Remi AI skill free?

Yes. It is published on GitHub by CYC2002tommy 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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