Scientific Visualization

Q: Why use Scientific Visualization on TypingMind?

Because you install it once and use it with any model. Scientific Visualization 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.

Q: How do I install Scientific Visualization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/scientific-visualization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Q: Which AI models can use Scientific Visualization?

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.

Q: How many AI models can I use with Scientific Visualization?

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

Q: Is the Scientific Visualization AI skill free?

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

Q: 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.

Q: 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.

OrganizationPopular

aiming-lab

scientific-visualization

Publication-ready scientific figure design with matplotlib and seaborn. Use when creating journal submission figures with proper formatting, accessibility, and statistical annotations.

Overview

Publisher	aiming-lab
Repository	`AutoResearchClaw`
Skill name	`scientific-visualization`
Stars	14.4K
Forks	1.7K
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 aiming-lab on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/scientific-visualization

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/aiming-lab/AutoResearchClaw.git /tmp/AutoResearchClaw
mkdir -p .claude/skills
cp -r /tmp/AutoResearchClaw/researchclaw/skills/builtin/experiment/scientific-visualization .claude/skills/scientific-visualization

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scientific Visualization 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 Scientific Visualization 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 Scientific Visualization 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.

Scientific Visualization Best Practice

Figure Design Principles

Every figure must have a clear, self-contained message
Minimize chartjunk: remove gridlines, background shading, and 3D effects
Use direct labeling instead of legends when possible
Remove top and right spines for cleaner appearance
Ensure all text is readable at final print size (minimum 6pt font)

Journal Figure Sizing

Single column: 3.3-3.5 inches (85-89 mm) wide
1.5 column: 4.5-5.5 inches (114-140 mm) wide
Double column / full width: 6.5-7.1 inches (165-180 mm) wide
Resolution: 300 DPI minimum for raster; prefer vector formats (PDF, EPS, SVG)
Check target journal author guidelines for exact specifications

Colorblind-Safe Design

Use colorblind-friendly palettes: seaborn "colorblind", Okabe-Ito, viridis, cividis
NEVER rely on color alone — combine with shape, pattern, or line style
Avoid red-green combinations; prefer blue-orange or blue-yellow contrasts
Test figures with a colorblind simulator before submission
Ensure figures work in grayscale for print journals

Multi-Panel Layouts

Label panels with uppercase letters: (A), (B), (C) in bold, top-left corner
Use consistent axis scales across panels when comparing related data
Share axes where appropriate to reduce redundancy
Maintain consistent font sizes and line widths across all panels
Use plt.subplots() with constrained_layout=True for automatic spacing

Statistical Annotations on Figures

Show individual data points alongside summary statistics (box + strip plots)
Always include error bars; specify type in caption (SEM, SD, 95% CI)
Use significance brackets with stars: * p<.05, ** p<.01, *** p<.001
Annotate effect sizes or key statistics directly on the figure when helpful
Never use bar charts for small-n data — use dot plots or box plots instead

Export and Quality Checklist

Save in vector format (PDF/SVG) for line art; TIFF/PNG for photographs
Embed fonts or convert text to outlines for cross-platform consistency
Verify axis labels include units in parentheses: "Time (s)", "Force (N)"
Ensure figure caption fully explains all symbols, abbreviations, and panels
Check that color-coded elements match between figure and caption

Frequently asked questions

What does the Scientific Visualization AI skill do?

Publication-ready scientific figure design with matplotlib and seaborn. Use when creating journal submission figures with proper formatting, accessibility, and statistical annotations.

Why use Scientific Visualization on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/experiment/scientific-visualization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Scientific Visualization?

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 Scientific Visualization?

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

Is the Scientific Visualization AI skill free?

Yes. It is published on GitHub by aiming-lab 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Scientific Visualization Best Practice

Figure Design Principles

Journal Figure Sizing

Colorblind-Safe Design

Multi-Panel Layouts

Statistical Annotations on Figures

Export and Quality Checklist

Frequently asked questions

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