Matplotlib
zLanqing/codex-claude-academic-skills
Low-level plotting library for full customization. An agent skill from zLanqing/codex-claude-academic-skills.
Publication-ready scientific figure design with matplotlib and seaborn.
Install Scientific Visualization
$ npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/AutoResearchClaw scientific-visualization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/scientific-visualization .claude/skills/scientific-visualization && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "scientific-visualization" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualization into .claude/skills/scientific-visualization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scientific-visualization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/AutoResearchClaw scientific-visualization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/scientific-visualization .agents/skills/scientific-visualization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "scientific-visualization" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualization into .agents/skills/scientific-visualization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scientific-visualization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/AutoResearchClaw scientific-visualization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/scientific-visualization .cursor/skills/scientific-visualization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "scientific-visualization" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualization into .cursor/skills/scientific-visualization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scientific-visualization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aiming-lab/AutoResearchClaw.git --path .claude/skills/scientific-visualization--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/AutoResearchClaw scientific-visualization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/scientific-visualization .gemini/skills/scientific-visualization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "scientific-visualization" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualization into .gemini/skills/scientific-visualization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scientific-visualization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aiming-lab/AutoResearchClaw scientific-visualizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/scientific-visualization .github/skills/scientific-visualization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "scientific-visualization" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualization into .github/skills/scientific-visualization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scientific-visualization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aiming-lab/AutoResearchClaw scientific-visualization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/scientific-visualization .opencode/skills/scientific-visualization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "scientific-visualization" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/.claude/skills/scientific-visualization into .opencode/skills/scientific-visualization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scientific-visualization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
scientific-visualization- GitHub stars
- 15k
- Token cost
- ~709 tokens
- SKILL.md length
- 337 words
- Files
- 1
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
Publication-ready scientific figure design with matplotlib and seaborn.
- Works in 5 steps: Every figure must have a clear,… → Minimize chartjunk: remove gridlines,… → Use direct labeling instead of legends… → …
- Creating journal submission figures with proper formatting
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Statistical annotations
What it does
Scientific Visualization is an agent skill from aiming-lab/AutoResearchClaw. Publication-ready scientific figure design with matplotlib and seaborn. Use when creating journal submission figures with proper formatting, accessibility, and statistical annotations.
Its SKILL.md is about 710 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data visualization. It works with Seaborn and Matplotlib. The repository describes itself as: Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞. The licence is MIT.
When your agent uses it
- Creating journal submission figures with proper formatting
- Statistical annotations
Example prompts
- “/scientific-visualization”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 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)
What it can do on your machine
Read from SKILL.md and the folder at commit be4ba47. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Scientific Visualization loads about 709 tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 337 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from aiming-lab/AutoResearchClaw at commit be4ba47, republished under its MIT licence (© aiming-lab). 337 words, ~709 tokens.
Download SKILL.mdSave it as
.claude/skills/scientific-visualization/SKILL.md (or your agent's skills folder).- name
- scientific-visualization
- description
- Publication-ready scientific figure design with matplotlib and seaborn. Use when creating journal submission figures with proper formatting, accessibility, and statistical annotations.
- metadata.category
- writing
- metadata.trigger-keywords
- figure,plot,chart,visualization,matplotlib,seaborn,colorblind,publication
- metadata.applicable-stages
- 14,17,22
- metadata.priority
- 3
- metadata.version
- 1.0
- metadata.author
- researchclaw
- metadata.references
- adapted from K-Dense-AI/claude-scientific-skills
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()withconstrained_layout=Truefor 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
© aiming-lab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .claude/skills/scientific-visualization of aiming-lab/AutoResearchClaw.
Open the folder on GitHubat commit be4ba47
Compare with similar skills
Scientific Visualization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Scientific Visualization this skillaiming-lab/AutoResearchClaw | 15k | — | ~709 | Automated safety check: Pass | MIT | |
| MatplotlibzLanqing/codex-claude-academic-skills | 4.6k | 18 repos | ~2.9k | Automated safety check: Pass | MIT | |
| Scientific Visualizationmims-harvard/OptimusKG | 146 | 19 repos | ~6.3k | Automated safety check: Pass | MIT | |
| SeabornzLanqing/codex-claude-academic-skills | 4.6k | 16 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Scientific VisualizationOleafly/Oleafly | 206 | 1 repos | ~3.4k | Automated safety check: Notes | MIT | |
| Ieee Figure TableCloudWave818/ieee-skills | 355 | — | ~1k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Scientific Visualization
What does Scientific Visualization do?
Publication-ready scientific figure design with matplotlib and seaborn. Scientific Visualization is an agent skill from aiming-lab/AutoResearchClaw. Publication-ready scientific figure design with matplotlib and seaborn.
When should I use Scientific Visualization?
Scientific Visualization fits situations like: creating journal submission figures with proper formatting; statistical annotations.
How do I install Scientific Visualization in Claude Code?
Run `npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a claude-code`. Or copy the skill folder (.claude/skills/scientific-visualization in aiming-lab/AutoResearchClaw) into .claude/skills/scientific-visualization in your project. Claude Code loads it when a task matches its description.
How do I install Scientific Visualization in Codex?
Run `npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a codex`. Or copy the skill folder (.claude/skills/scientific-visualization in aiming-lab/AutoResearchClaw) into .agents/skills/scientific-visualization in your project. Codex loads it when a task matches its description.
Can I use Scientific Visualization in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aiming-lab/AutoResearchClaw --skill scientific-visualization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scientific-visualization, .gemini/skills/scientific-visualization, .github/skills/scientific-visualization and .opencode/skills/scientific-visualization in your project.
What does Scientific Visualization need to run?
SKILL.md names no scripts, command-line tools or credentials: Scientific Visualization is instructions for the agent only.
Does Scientific Visualization access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Scientific Visualization safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Scientific Visualization use?
Scientific Visualization is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Scientific Visualization use?
About 709 tokens (SKILL.md is roughly 2.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Scientific Visualization?
Skills that share tags, products or a category with Scientific Visualization: Matplotlib (zLanqing/codex-claude-academic-skills, 4.6k stars), Scientific Visualization (mims-harvard/OptimusKG, 146 stars), Seaborn (zLanqing/codex-claude-academic-skills, 4.6k stars) and Scientific Visualization (Oleafly/Oleafly, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Scientific Visualization?
aiming-lab (a GitHub organization) maintains it in aiming-lab/AutoResearchClaw, which has 14,595 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on August 19, 2026.
Source: aiming-lab/AutoResearchClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.