CJK Font Setup for Plots
xjtulyc/MedgeClaw
Detects a usable Chinese, Japanese or Korean font and configures matplotlib so chart labels, titles and legends render instead of showing empty boxes.
Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element.
Install Matplotlib Scientific Plotting
$ npx skills add jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills matplotlib-scientific-plotting --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/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/data-visualization/matplotlib-scientific-plotting .claude/skills/matplotlib-scientific-plotting && 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 "matplotlib-scientific-plotting" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plotting into .claude/skills/matplotlib-scientific-plotting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "matplotlib-scientific-plotting", 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/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plottingType 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 jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills matplotlib-scientific-plotting --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/data-visualization/matplotlib-scientific-plotting .agents/skills/matplotlib-scientific-plotting && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "matplotlib-scientific-plotting" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plotting into .agents/skills/matplotlib-scientific-plotting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "matplotlib-scientific-plotting", 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 jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills matplotlib-scientific-plotting --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/data-visualization/matplotlib-scientific-plotting .cursor/skills/matplotlib-scientific-plotting && 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 "matplotlib-scientific-plotting" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plotting into .cursor/skills/matplotlib-scientific-plotting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "matplotlib-scientific-plotting", 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/jaechang-hits/SciAgent-Skills.git --path skills/data-visualization/matplotlib-scientific-plotting--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 jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills matplotlib-scientific-plotting --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/data-visualization/matplotlib-scientific-plotting .gemini/skills/matplotlib-scientific-plotting && 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 "matplotlib-scientific-plotting" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plotting into .gemini/skills/matplotlib-scientific-plotting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "matplotlib-scientific-plotting", 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 jaechang-hits/SciAgent-Skills matplotlib-scientific-plottingInstalls 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 jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/data-visualization/matplotlib-scientific-plotting .github/skills/matplotlib-scientific-plotting && 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 "matplotlib-scientific-plotting" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plotting into .github/skills/matplotlib-scientific-plotting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "matplotlib-scientific-plotting", 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 jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills matplotlib-scientific-plotting --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/data-visualization/matplotlib-scientific-plotting .opencode/skills/matplotlib-scientific-plotting && 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 "matplotlib-scientific-plotting" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/data-visualization/matplotlib-scientific-plotting into .opencode/skills/matplotlib-scientific-plotting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "matplotlib-scientific-plotting", 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
matplotlib-scientific-plotting- GitHub stars
- 370
- Used in
- 1 other repo
- Token cost
- ~4k tokens
- SKILL.md length
- 638 words
- Files
- 1
- Skills in repo
- 163
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element.
- Works in 7 steps: Always use the OO interface (fig, ax =… → Use constrained_layout=True to prevent… → Choose accessible colormaps: Use… → …
- Tasks that involve Data visualization
- SKILL.md covers Overview, When to Use, Prerequisites and Quick Start, plus 7 more sections
- Calls pip
What it does
Matplotlib Scientific Plotting is an agent skill from jaechang-hits/SciAgent-Skills. Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element. PNG/PDF/SVG export. Use seaborn for quick stats, plotly for interactive.
Its SKILL.md is about 4k 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 Matplotlib, Python, Seaborn and Plotly. The repository describes itself as: 197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Powers OmicsHorizon.
When your agent uses it
- Tasks that involve Data visualization
Example prompts
- “/matplotlib-scientific-plotting”
Requirements
- Python 3
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Always use the OO interface (fig, ax = plt.subplots()) for production code. Reserve plt.plot() for quick interactive exploration only
- Use constrained_layout=True to prevent overlapping labels and titles
- Choose accessible colormaps: Use viridis, cividis, or plasma (perceptually uniform, colorblind-safe). Avoid jet and rainbow
- Close figures after saving to prevent memory leaks in loops
- Set DPI appropriately: 300 for print/journal, 150 for web/slides, 72 for screen-only
- Use rasterized=True for large datasets to reduce PDF/SVG file size
- Label panels consistently: Use bold letters (A, B, C, D) at top-left of each subplot for multi-panel figures
What it can do on your machine
Read from SKILL.md and the folder at commit 82c862c. 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
Shell commands in SKILL.md call:
pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
matplotlib.org
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
Matplotlib Scientific Plotting loads about 4k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 638 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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 638 words (~3,974 tokens).
“Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots. It provides both a MATLAB-style pyplot interface and an object-oriented API for full control over figures, axes, and artists. Essential for generating publication-quality scientific figures.”
- name
- matplotlib-scientific-plotting
- license
- PSF-based
Files
Just SKILL.md in skills/data-visualization/matplotlib-scientific-plotting of jaechang-hits/SciAgent-Skills.
Open the folder on GitHubat commit 82c862c
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in jaechang-hits/SciAgent-Skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Matplotlib Scientific Plotting 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 |
|---|---|---|---|---|---|---|
| Matplotlib Scientific Plotting this skilljaechang-hits/SciAgent-Skills | 370 | 1 repos | ~4k | Automated safety check: Pass | Custom licence | |
| CJK Font Setup for Plotsxjtulyc/MedgeClaw | 617 | 1 repos | ~1.3k | Automated safety check: Pass | None | |
| SeabornK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.4k | Automated safety check: Notes | BSD-3-Clause | |
| Data Visualizationw95/awesome-claude-corporate-skills | 237 | 2 repos | ~2.8k | Automated safety check: Pass | MIT | |
| Python Dataviz Guidewentorai/research-plugins | 298 | 1 repos | ~1.8k | Automated safety check: Pass | MIT | |
| MatplotlibzLanqing/codex-claude-academic-skills | 4.6k | 18 repos | ~2.9k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Matplotlib Scientific Plotting
What does Matplotlib Scientific Plotting do?
Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element. Matplotlib Scientific Plotting is an agent skill from jaechang-hits/SciAgent-Skills. Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element.
When should I use Matplotlib Scientific Plotting?
Matplotlib Scientific Plotting fits situations like: tasks that involve Data visualization.
How do I install Matplotlib Scientific Plotting in Claude Code?
Run `npx skills add jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a claude-code`. Or copy the skill folder (skills/data-visualization/matplotlib-scientific-plotting in jaechang-hits/SciAgent-Skills) into .claude/skills/matplotlib-scientific-plotting in your project. Claude Code loads it when a task matches its description.
How do I install Matplotlib Scientific Plotting in Codex?
Run `npx skills add jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a codex`. Or copy the skill folder (skills/data-visualization/matplotlib-scientific-plotting in jaechang-hits/SciAgent-Skills) into .agents/skills/matplotlib-scientific-plotting in your project. Codex loads it when a task matches its description.
Can I use Matplotlib Scientific Plotting 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 jaechang-hits/SciAgent-Skills --skill matplotlib-scientific-plotting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/matplotlib-scientific-plotting, .gemini/skills/matplotlib-scientific-plotting, .github/skills/matplotlib-scientific-plotting and .opencode/skills/matplotlib-scientific-plotting in your project.
What does Matplotlib Scientific Plotting need to run?
Going by SKILL.md and its folder, Matplotlib Scientific Plotting needs the command-line tools its instructions call (pip). Our summary lists: Python 3.
Does Matplotlib Scientific Plotting access the network?
SKILL.md names 1 domain. As links in the text: matplotlib.org. This is read from the text; nothing was executed.
Is Matplotlib Scientific Plotting 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 Matplotlib Scientific Plotting use?
Matplotlib Scientific Plotting has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Matplotlib Scientific Plotting use?
About 4k tokens (SKILL.md is roughly 16k 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 Matplotlib Scientific Plotting?
Skills that share tags, products or a category with Matplotlib Scientific Plotting: CJK Font Setup for Plots (xjtulyc/MedgeClaw, 617 stars), Seaborn (K-Dense-AI/scientific-agent-skills, 48k stars), Data Visualization (w95/awesome-claude-corporate-skills, 237 stars) and Python Dataviz Guide (wentorai/research-plugins, 298 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Matplotlib Scientific Plotting?
jaechang-hits (a GitHub user) maintains it in jaechang-hits/SciAgent-Skills, which has 370 GitHub stars. The repository holds 163 skills in this directory. The repository was last updated on September 29, 2026.
Source: jaechang-hits/SciAgent-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.