Paper Figures logo

Paper Figures

CommunityPopular
Muuuun
paper-figures

Extract figures from downloaded papers and include them in survey/review reports. Use when the report covers other groups' work and benefits from their architecture diagrams, experimental plots, or system schematics. Your brain prompt supplies the absolute path to the extract-figures script as {{EXTRACT_FIGURES}} — use that value wherever this skill writes `extract-figures`.

Overview

PublisherMuuuun
Repositoryluxas
Skill namepaper-figures
Stars
1.2K
Forks
18
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 Muuuun on GitHub. Read the source before you install it.

Installation

Install the Paper Figures 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/Muuuun/luxas/tree/main/skills/paper-figures
  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/Muuuun/luxas.git /tmp/luxas
mkdir -p .claude/skills
cp -r /tmp/luxas/skills/paper-figures .claude/skills/paper-figures
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Figures 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 Figures 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 Figures 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 Figures Skill

Figures are information. A survey/review report covering downloaded papers MUST include key figures — architecture diagrams, experimental results, comparisons. Do NOT write a text-only survey when figures are available.

3-step workflow

Step 1 — Extract figures from downloaded papers

Your brain prompt supplies the script's absolute path as {{EXTRACT_FIGURES}}. Invoke it once per paper:

bash
{{EXTRACT_FIGURES}} data/papers/<paper-id>.pdf   # single PDF
{{EXTRACT_FIGURES}} data/papers/<arxiv-id>        # arXiv source directory

This creates data/papers/<id>_figures/ with extracted images and a manifest.json listing each figure with caption and page number.

Step 2 — Review captions and classify every figure

Read every manifest:

bash
cat data/papers/*_figures/manifest.json

Record your decisions in notes/memory.md under a ## Figure Review section. Every figure must end up in one of three states:

  • USE — essential for understanding the topic; will be included in the report
  • SKIP — irrelevant, redundant, or low quality
  • UNREVIEWED — caption not yet read (only acceptable as a transient state)

Select figures that are:

  • Essential for understanding the topic (architecture diagrams, system schematics)
  • Key experimental results that support your narrative
  • Useful comparisons across methods, systems, or time periods
  • Visually informative (not just tables rendered as images)

Step 3 — Include USE figures in the report

For each figure marked USE, embed it directly in LaTeX:

latex
\begin{figure}[t]
  \centering
  \includegraphics[width=\linewidth]{../data/papers/<id>_figures/<filename>}
  \caption{<Your caption describing the figure in the context of your survey>. Adapted from \cite{<key>}.}
  \label{fig:<label>}
\end{figure}

Rules

  • Coverage: survey/review reports include at least 3-5 USE figures from downloaded papers, in addition to any figures you generate yourself.
  • Captions: write your OWN caption in the context of the survey narrative — do not copy the original caption.
  • Attribution: always cite the source paper with \cite{}.
  • No skipping the review step: every extracted figure must be classified before writing the report.
  • Complementary: you may also generate your own figures (see skills/matplotlib-figures/SKILL.md) for data summaries, timelines, or cross-paper comparisons not found in existing figures.

Frequently asked questions

What does the Paper Figures AI skill do?

Extract figures from downloaded papers and include them in survey/review reports. Use when the report covers other groups' work and benefits from their architecture diagrams, experimental plots, or system schematics. Your brain prompt supplies the absolute path to the extract-figures script as {{EXTRACT_FIGURES}} — use that value wherever this skill writes `extract-figures`.

Why use Paper Figures on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Muuuun/luxas/tree/main/skills/paper-figures. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Paper Figures?

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 Figures?

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

Is the Paper Figures AI skill free?

Yes. It is published on GitHub by Muuuun 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇