Ieee Figure Table
CloudWave818/ieee-skills
Audit, redesign, generate, and improve IEEE manuscript figures, tables, captions, result presentation, plotting scripts, visual polish, hybrid Python/R plus vector-editor workflows…
Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations.
Install Charting
$ npx skills add oaustegard/claude-skills --skill charting -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install oaustegard/claude-skills charting --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/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/charting .claude/skills/charting && 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 "charting" agent skill from https://github.com/oaustegard/claude-skills/tree/main/charting into .claude/skills/charting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "charting", 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/oaustegard/claude-skills/tree/main/chartingType 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 oaustegard/claude-skills --skill charting -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install oaustegard/claude-skills charting --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/charting .agents/skills/charting && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "charting" agent skill from https://github.com/oaustegard/claude-skills/tree/main/charting into .agents/skills/charting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "charting", 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 oaustegard/claude-skills --skill charting -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install oaustegard/claude-skills charting --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/charting .cursor/skills/charting && 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 "charting" agent skill from https://github.com/oaustegard/claude-skills/tree/main/charting into .cursor/skills/charting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "charting", 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/oaustegard/claude-skills.git --path charting--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 oaustegard/claude-skills --skill charting -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install oaustegard/claude-skills charting --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/charting .gemini/skills/charting && 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 "charting" agent skill from https://github.com/oaustegard/claude-skills/tree/main/charting into .gemini/skills/charting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "charting", 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 oaustegard/claude-skills chartingInstalls 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 oaustegard/claude-skills --skill charting -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/charting .github/skills/charting && 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 "charting" agent skill from https://github.com/oaustegard/claude-skills/tree/main/charting into .github/skills/charting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "charting", 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 oaustegard/claude-skills --skill charting -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install oaustegard/claude-skills charting --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/charting .opencode/skills/charting && 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 "charting" agent skill from https://github.com/oaustegard/claude-skills/tree/main/charting into .opencode/skills/charting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "charting", 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
charting- GitHub stars
- 150
- Token cost
- ~1.5k tokens
- SKILL.md length
- 543 words
- Files
- 2
- Skills in repo
- 93
- Repo updated
- First seen
- Licence
- MIT
At a glance
Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations.
- Works in 4 steps: Create chart in /home/claude/ → Save as PNG (default) or SVG (if user… → Copy to /mnt/user-data/outputs/ → …
- Creating charts
- SKILL.md covers Library Selection Framework, Quick Reference: Chart Type →…, Production Defaults and Output Workflow
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Charting is an agent skill from oaustegard/claude-skills. Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations. Use when creating charts, plots, graphs, diagrams, heatmaps, visualizations from data, or when choosing between matplotlib/seaborn/graphviz. Also triggers for network diagrams, flowcharts, dependency trees, state machines, and entity-relationship diagrams. For interactive browser-rendered charts or uploaded data exploration, defer to charting-vega-lite instead.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `CHANGELOG.md`).
It sits in Data & Analytics, covering Data visualization and Diagrams. It works with Seaborn, Matplotlib and Python. The repository describes itself as: My collection of Claude skills. The licence is MIT.
When your agent uses it
- Creating charts
- Visualizations from data
- Choosing between matplotlib/seaborn/graphviz
- Network diagrams
Example prompts
- “/charting”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Create chart in /home/claude/
- Save as PNG (default) or SVG (if user needs vector)
- Copy to /mnt/user-data/outputs/
- Present via present_files
What it can do on your machine
Read from SKILL.md and the folder at commit 559a6cd. 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 (its code samples are python).
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
Charting loads about 1.5k tokens when it runs. Until then it costs about 125 tokens; SKILL.md has 543 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 oaustegard/claude-skills at commit 559a6cd, republished under its MIT licence (© oaustegard). 543 words, ~1,527 tokens.
Download SKILL.mdSave it as
.claude/skills/charting/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- charting
- description
- Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations. Use when creating charts, plots, graphs, diagrams, heatmaps, visualizations from data, or when choosing between matplotlib/seaborn/graphviz. Also triggers for network diagrams, flowcharts, dependency trees, state machines, and entity-relationship diagrams. For interactive browser-rendered charts or uploaded data exploration, defer to charting-vega-lite instead.
- metadata.version
- 0.1.0
Charting: Python Static Visualizations
Select the optimal Python charting library and produce clean, publication-quality output.
Library Selection Framework
Choose the library based on what the visualization represents, not habit.
Seaborn — DEFAULT for statistical/analytical charts
Seaborn wraps matplotlib with better defaults, tighter pandas integration, and fewer lines of code. Reach for seaborn first when the data lives in a DataFrame and the goal is analytical.
Use for: distributions (histograms, KDEs, violin plots, ECDFs), categorical comparisons (box plots, swarm plots, strip plots, bar plots), correlation (heatmaps, pair plots, regression plots), grouped/faceted views (FacetGrid, catplot, relplot).
Why: Automatic axis labeling from column names, coherent color palettes, built-in aggregation with confidence intervals, and hue/col/row faceting with minimal code.
Practical rule: If the code would call plt.bar(), plt.hist(), plt.scatter(), or build a heatmap with plt.imshow() — use the seaborn equivalent instead. It will look better with less effort.
Matplotlib — fine-grained control and non-standard layouts
Drop to raw matplotlib only when seaborn doesn't support the chart type or when pixel-level layout control is required.
Use for: custom multi-panel figures mixing chart types, unusual annotations (arrows, shaded regions, custom legends), non-standard axes (polar, broken axes, insets), animations, image overlays, or any layout where the default seaborn API is insufficient.
Combine with seaborn: Seaborn plots return matplotlib Axes objects. Apply matplotlib customization on top of seaborn output rather than rebuilding from scratch.
Graphviz — graph/network structures
Graphviz operates in a fundamentally different domain: nodes and edges, not x/y data.
Use for: dependency trees, flowcharts, state machines, org charts, entity-relationship diagrams, DAGs, call graphs, any directed or undirected graph structure.
Python interface: Use the graphviz Python package (installed). Create graphviz.Digraph() or graphviz.Graph(), add nodes/edges, render to PNG/SVG/PDF.
import graphviz
g = graphviz.Digraph(format='png')
g.node('A', 'Start')
g.node('B', 'Process')
g.edge('A', 'B')
g.render('/home/claude/output', cleanup=True)Layout engines: dot (hierarchical, default), neato (spring model), fdp (force-directed), circo (circular), twopi (radial). Set via g.engine = 'neato'.
Vega-Lite — interactive browser charts
When the user wants interactive, browser-rendered visualizations (tooltips, zoom, selection, filtering) or uploads data for exploratory charting, defer to the charting-vega-lite skill. That skill handles React artifact generation with inline data islands.
Decision shortcut: Static image file → this skill. Interactive artifact → charting-vega-lite.
Show full SKILL.md (203 more words)Show less
Quick Reference: Chart Type → Library
| Need | Library | Function |
|---|---|---|
| Histogram / KDE | seaborn | sns.histplot(), sns.kdeplot() |
| Box / Violin / Swarm | seaborn | sns.boxplot(), sns.violinplot() |
| Bar (categorical) | seaborn | sns.barplot(), sns.countplot() |
| Correlation heatmap | seaborn | sns.heatmap() |
| Scatter + regression | seaborn | sns.scatterplot(), sns.regplot() |
| Pair plot (multi-var) | seaborn | sns.pairplot() |
| Faceted grid | seaborn | sns.FacetGrid, catplot, relplot |
| Time series line | seaborn | sns.lineplot() (handles CI bands) |
| Custom multi-panel | matplotlib | fig, axes = plt.subplots() |
| Polar / radar | matplotlib | projection='polar' |
| Annotated diagrams | matplotlib | ax.annotate(), arrows, patches |
| Dependency tree | graphviz | Digraph |
| Flowchart / FSM | graphviz | Digraph with shape attrs |
| ER diagram | graphviz | Graph with record shapes |
| Network graph | graphviz | Graph with layout engine |
Production Defaults
Apply these defaults to produce clean output without per-chart fiddling.
Seaborn Setup
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style="whitegrid", palette="muted", font_scale=1.1)Style options: whitegrid (default, good for most), white (cleaner for publications), darkgrid (data-dense plots), ticks (minimal).
Figure Sizing and DPI
fig, ax = plt.subplots(figsize=(10, 6))
# Or for seaborn figure-level functions:
g = sns.catplot(..., height=6, aspect=1.5)
# Save at publication quality
plt.savefig('/home/claude/chart.png', dpi=150, bbox_inches='tight', facecolor='white')Use dpi=150 for screen/web output, dpi=300 for print. Always use bbox_inches='tight' to avoid clipped labels.
Color Guidance
- Categorical:
"muted","Set2","tab10"— distinct, accessible - Sequential:
"viridis","YlOrRd","Blues"— ordered magnitude - Diverging:
"RdBu","coolwarm"— centered on zero/midpoint - Avoid:
"jet","rainbow"— perceptually non-uniform, colorblind-hostile
Common Refinements
# Rotate x-labels if overlapping
plt.xticks(rotation=45, ha='right')
# Remove top/right spines for cleaner look
sns.despine()
# Thousands separator for large numbers
ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f'{x:,.0f}'))Output Workflow
- Create chart in
/home/claude/ - Save as PNG (default) or SVG (if user needs vector)
- Copy to
/mnt/user-data/outputs/ - Present via
present_files
Always plt.close() after saving to free memory.
© oaustegard, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in charting of oaustegard/claude-skills.
- SKILL.md
- CHANGELOG.md
Open the folder on GitHubat commit 559a6cd
Compare with similar skills
Charting 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 |
|---|---|---|---|---|---|---|
| Charting this skilloaustegard/claude-skills | 150 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Ieee Figure TableCloudWave818/ieee-skills | 353 | — | ~1k | Automated safety check: Pass | MIT | |
| Nature FigureCitrus-bit/Anaxa | 120 | 2 repos | ~2.7k | Automated safety check: Pass | MIT | |
| CJK Font Setup for Plotsxjtulyc/MedgeClaw | 617 | 1 repos | ~1.3k | Automated safety check: Pass | None | |
| Release Evidence WorkflowAli-Marandi/ClimateDataAnalyzer | 107 | — | ~1.6k | Automated safety check: Pass | MIT | |
| IntelligrapherMrLee2R/Intelligrapher | 112 | — | ~388 | Automated safety check: Pass | MIT |
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Release Evidence Workflow
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Intelligrapher
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Scientific Figure Generation
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Related
Works with
Categories
Questions about Charting
What does Charting do?
Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations. Charting is an agent skill from oaustegard/claude-skills. Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations.
When should I use Charting?
Charting fits situations like: creating charts; visualizations from data; choosing between matplotlib/seaborn/graphviz; network diagrams.
How do I install Charting in Claude Code?
Run `npx skills add oaustegard/claude-skills --skill charting -a claude-code`. Or copy the skill folder (charting in oaustegard/claude-skills) into .claude/skills/charting in your project. Claude Code loads it when a task matches its description.
How do I install Charting in Codex?
Run `npx skills add oaustegard/claude-skills --skill charting -a codex`. Or copy the skill folder (charting in oaustegard/claude-skills) into .agents/skills/charting in your project. Codex loads it when a task matches its description.
Can I use Charting 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 oaustegard/claude-skills --skill charting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/charting, .gemini/skills/charting, .github/skills/charting and .opencode/skills/charting in your project.
What does Charting need to run?
SKILL.md names no scripts, command-line tools or credentials: Charting is instructions for the agent only. Our summary lists: Python 3.
Does Charting 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 Charting 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 Charting use?
Charting 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 Charting use?
About 1.5k tokens (SKILL.md is roughly 6.1k 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 Charting?
Skills that share tags, products or a category with Charting: Ieee Figure Table (CloudWave818/ieee-skills, 353 stars), Nature Figure (Citrus-bit/Anaxa, 120 stars), CJK Font Setup for Plots (xjtulyc/MedgeClaw, 617 stars) and Release Evidence Workflow (Ali-Marandi/ClimateDataAnalyzer, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Charting?
oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 2, 2026.
Source: oaustegard/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.