Matplotlib
zLanqing/codex-claude-academic-skills
Low-level plotting library for full customization. An agent skill from zLanqing/codex-claude-academic-skills.
A skill your agent uses when creating, reviewing, or styling charts, graphs, dashboards, sparklines, or any data visualization.
$ npx skills add caylent/tufte-data-viz --skill tufte-data-viz -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install caylent/tufte-data-viz tufte-data-viz --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
Claude Code skills documentation · loads skills from .claude/skills/
Install the "tufte-data-viz" agent skill from https://github.com/caylent/tufte-data-viz/tree/main into .claude/skills/tufte-data-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tufte-data-viz", 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.
$ npx skills add caylent/tufte-data-viz --skill tufte-data-viz -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install caylent/tufte-data-viz tufte-data-viz --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tufte-data-viz" agent skill from https://github.com/caylent/tufte-data-viz/tree/main into .agents/skills/tufte-data-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tufte-data-viz", 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 caylent/tufte-data-viz --skill tufte-data-viz -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install caylent/tufte-data-viz tufte-data-viz --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "tufte-data-viz" agent skill from https://github.com/caylent/tufte-data-viz/tree/main into .cursor/skills/tufte-data-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tufte-data-viz", 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.
$ npx skills add caylent/tufte-data-viz --skill tufte-data-viz -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install caylent/tufte-data-viz tufte-data-viz --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "tufte-data-viz" agent skill from https://github.com/caylent/tufte-data-viz/tree/main into .gemini/skills/tufte-data-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tufte-data-viz", 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 caylent/tufte-data-viz tufte-data-vizInstalls 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 caylent/tufte-data-viz --skill tufte-data-viz -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "tufte-data-viz" agent skill from https://github.com/caylent/tufte-data-viz/tree/main into .github/skills/tufte-data-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tufte-data-viz", 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 caylent/tufte-data-viz --skill tufte-data-viz -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install caylent/tufte-data-viz tufte-data-viz --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "tufte-data-viz" agent skill from https://github.com/caylent/tufte-data-viz/tree/main into .opencode/skills/tufte-data-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tufte-data-viz", 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.
tufte-data-vizA skill your agent uses when creating, reviewing, or styling charts, graphs, dashboards, sparklines, or any data visualization.
Tufte Data Viz is an agent skill from caylent/tufte-data-viz. Use when creating, reviewing, or styling charts, graphs, dashboards, sparklines, or any data visualization. Applies to Recharts, ECharts, Chart.js, matplotlib, Plotly, seaborn, D3.js, and SVG. Enforces Tufte principles (data-ink ratio, direct labeling, range-frame axes) plus modern screen-first standards (accessibility, responsive, dark mode).
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 36 other files (for example `README.md`, `_docs/generate_showcase.py` and `examples/chartjs-tufte-plugin.js`).
It sits in Data & Analytics, covering Data visualization and Accessibility. It works with Chart.js, Matplotlib, Plotly and D3.js. The repository describes itself as: Agent skill: Edward Tufte's data visualization principles for clean, honest, high-data-ink-ratio charts. Recharts, ECharts, Chart.js, matplotlib, Plotly, D3/SVG. The licence is MIT.
12 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ae7ca0d. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadGlobGrepFrom allowed-tools in the SKILL.md frontmatter.
Ships script files (Python, JavaScript and TypeScript, from the files we listed), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Tufte Data Viz loads about 3.5k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 1,757 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.
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.
The full file from caylent/tufte-data-viz at commit ae7ca0d, republished under its MIT licence (© caylent). 1,757 words, ~3,472 tokens.
.claude/skills/tufte-data-viz/SKILL.md (or your agent's skills folder). This skill also uses 33 other files; get the full folder from GitHub.Apply Edward Tufte's principles whenever generating or reviewing code that renders data visually. This skill covers chart generation, not slide/presentation design.
Follow these steps in order when creating any chart:
Before writing code, determine:
Review the rules below. Every rule is a default — deviate only when the user explicitly requests otherwise.
Use the Library quick reference table to find the essential overrides for the target library. For complete code examples and helper functions, read ONE rule file from rules/ matching the library.
Run through the validation checklist at the bottom of this file before presenting the chart.
Rules 1–14 cover static principles; 15–19 extend them for screens; 20–22 address content and formatting.
No chart should have top or right axis lines, borders, or spines. The bottom and left axes are sufficient. Top and right lines are pure chartjunk.
Label each data series directly — at the endpoint of a line, on or beside a bar, next to a cluster. Remove the <Legend> component entirely. If there is only one series, the chart title provides that context; no label is needed.
The default is zero gridlines. For static charts where users need to read precise values, add horizontal-only gridlines at very low opacity (0.08–0.12). For interactive charts, prefer a contextual crosshair on hover instead (see rule 15). Never add vertical gridlines.
Axis lines should span only the range of the data, not from zero to some arbitrary maximum. The axis starts at (or near) the minimum data value and ends at the maximum.
No perspective, no depth, no shadows on chart elements. Two-dimensional data gets two-dimensional representation.
Default to a horizontal bar chart sorted by value. If the user explicitly asks for a pie chart: maximum 4 slices, 2D only, start at 12 o'clock, direct percentage labels on each slice.
Charts should be approximately 50% wider than tall. Standard sizes: 600x400, 750x500, 900x600. Exception: sparklines and small multiples may be more compact.
The default data series color is medium gray (#666). Use a single accent color to highlight the most important series or data point. Never use more than 4 distinct colors. Choose the right palette type: categorical (4-color muted) for unordered groups, sequential (single-hue ramp) for ordered magnitude, diverging (two-hue from center) for deviation from a midpoint. See rules/typography-and-color.md for hex values.
Light mode: #fffff8. Dark mode: #151515. Never use pure white (#ffffff) or pure black (#000000).
Use serif fonts for data labels, annotations, and chart titles: "ET Book", "Palatino Linotype", Palatino, "Book Antiqua", Georgia, serif. Sans-serif (system-ui, sans-serif) is acceptable only for small axis tick labels (11-12px).
Two y-axes on one chart create false implied correlations. Use small multiples instead — two charts stacked vertically with shared x-axis.
If the data contains a peak, trough, inflection point, or event boundary, add a text annotation pointing to it directly on the chart. Place annotations in the nearest clear space — offset from the data point with a short leader line if needed. When multiple annotations compete for space, keep only the most important; move others to a footnote or tooltip.
Include at least one reference element: a reference line (average, target, prior period), a shaded band, or a second series. A chart showing one line with no context fails the "Compared to what?" test.
Tooltips should be plain text with the data value and label. No colored background, no border, no arrow pointer, no shadow.
Default to the Tufte-clean overview — high data-ink, minimal chrome. Layer details through hover, tap, and click (values, annotations, comparisons). Don't frontload everything onto a single static view. A contextual crosshair on hover replaces permanent gridlines.
3:1 contrast ratio minimum for chart elements against their background; 4.5:1 for text in charts. Never use color as the sole differentiator — pair with shape, pattern, or direct label. Provide a text alternative for every chart (aria-label with key finding, or companion data table). Interactive charts must be keyboard-navigable.
Charts must have a responsive strategy — fluid (percentage width + viewBox), adaptive (breakpoint-based layout changes), or hybrid. At narrow viewports, change chart type or layout (horizontal bars for categories, reduced tick density, abbreviated labels), don't just shrink.
Transitions for data changes (sorting, filtering, time progression) are good — they help the viewer track transformations. Gratuitous entrance animations, bouncing, and decorative motion are chartjunk. Duration: 200–500ms, ease-out. Always respect prefers-reduced-motion.
Design both light and dark palettes intentionally. Never invert colors. Reduce saturation in dark mode (bright colors "vibrate" on dark backgrounds). Respect prefers-color-scheme. Use semantic color tokens (--tufte-bg, --tufte-text, --tufte-series-default) so charts adapt automatically.
The chart title states the key insight, not the axis description. "Revenue Surged 23% in Q3" not "Revenue by Quarter, 2024". The subtitle can provide context ("vs. prior year, USD millions"). If the data has no clear finding, the chart may not be needed (see rule 22).
Abbreviate large numbers: $1.2M not $1,200,000. Use thousand separators for mid-range numbers (12,450 not 12450). Match decimal precision to significance (don't show $4.2391M when $4.2M suffices). Right-align numbers in tables. Use consistent units and state them once (in the axis label or title), not on every data point.
If the data is 1–2 numbers, write a sentence with inline context ("Revenue was $4.2M, up 23% from Q2"). If the data is a simple ranking of 3–5 items, consider a table. Charts earn their space by revealing patterns, trends, or distributions that text and tables cannot. A chart of two bars is almost always worse than a sentence.
The universal rules above are sufficient for most charts. For complete code examples and library-specific helpers, read the appropriate rule file from the rules/ directory in this skill's folder. Only read ONE rule file per task.
| Library | Rule file to read | Essential config (apply even without reading the file) |
|---|---|---|
| Recharts | rules/recharts.md | <CartesianGrid stroke="none" />, remove <Legend />, <YAxis axisLine={false} tickLine={false} />, <Line dot={false} strokeWidth={1.5} /> |
| ECharts | rules/echarts.md | splitLine: { show: false }, legend: { show: false }, grid: { show: false }, use endLabel on series |
| Chart.js | rules/chartjs.md | grid: { display: false }, border: { display: false }, plugins.legend.display: false, use chartjs-plugin-datalabels |
| matplotlib | rules/matplotlib.md | spines['top'].set_visible(False), spines['right'].set_visible(False), spines['bottom'].set_bounds(min, max), font.family: serif |
| Plotly | rules/plotly.md | showgrid=False, showlegend=False, plot_bgcolor='#fffff8', zeroline=False |
| D3/SVG/HTML | rules/svg-html.md | .domain { display: none }, no <rect> backgrounds, stroke-opacity: 0.1 for any gridlines |
| Type | Key settings |
|---|---|
| Line | 1.5–2px stroke, dot={false} unless <7 points (then r=2), direct label at rightmost point |
| Bar | Prefer horizontal for categories, sort by value descending, direct value labels, #7a7a7a default fill |
| Scatter | Gray dots #999 r=3, highlight key cluster/outlier with accent, regression line if meaningful (dashed, thin) |
| Time series | Label events on chart ("Recession", "Launch"), range-frame x-axis, YoY via opacity (current solid, prior 30%) |
| Small multiples | Same scale ALL panels, shared axis labels (x on bottom row, y on left column), no panel borders |
| Sparklines | ~80x20px, no axes/labels/gridlines, min/max dots r=1.5, embed inline in text or table cells |
| Data tables | No zebra striping, whitespace + thin rules every 3–5 rows, right-align numbers, font-feature-settings: 'onum' 1 |
| Slopegraph | Before/after categories, label both endpoints (value + name), gray default + highlight key slopes |
| Area | Prefer lines. If area: fillOpacity 0.03–0.08, no gradient, direct labels at endpoints |
| Stacked bar | Avoid — use small multiples instead. If forced: sort by total, direct labels per segment, max 4 segments |
| Heatmap | Sequential or diverging palette only, value labels in cells, companion data table for accessibility |
For small multiples, sparklines, and slopegraph implementation patterns, see rules/small-multiples-sparklines.md.
| Token | Light | Dark |
|---|---|---|
| Background | #fffff8 | #151515 |
| Text | #111 | #ddd |
| Text secondary | #666 | #999 |
| Axis/rule | #ccc | #444 |
| Grid (if used) | #eee (8-12% opacity) | #333 |
| Default series | #666 | #999 |
| Highlight | #e41a1c | #fc8d62 |
Categorical (max 4): #4e79a7 steel blue · #f28e2b tangerine · #e15759 coral · #76b7b2 sage
Font stacks in rule 10. For full palettes (sequential, diverging), font loading, and old-style figures, see rules/typography-and-color.md.
When reviewing existing chart code, check for: legends (→ direct labels), pie charts (→ horizontal bars), 3D effects (→ flat 2D), dual y-axes (→ small multiples), heavy gridlines (→ remove or 0.1 opacity), rainbow palettes (→ gray + accent), gauge widgets (→ number + sparkline), gradient fills (→ solid color), rotated labels (→ flip axes or abbreviate), pure white/black backgrounds (→ #fffff8/#151515), hover-only information (→ tap/focus fallback), missing text alternatives (→ aria-label), color-only encoding (→ add shape/pattern).
For the full table with per-library detection patterns and one-liner fixes, see rules/anti-patterns.md.
Before presenting any chart, verify:
#fffff8 (light) or #151515 (dark), not pure white/black#666); color used only for emphasisprefers-reduced-motionLibrary rules (read ONE per task): rules/recharts.md, rules/echarts.md, rules/chartjs.md, rules/matplotlib.md, rules/plotly.md, rules/svg-html.md — complete code examples, helpers, and theme registrations.
Cross-cutting (read when specifically needed):
rules/interactive-and-accessible.md — progressive disclosure, WCAG, responsive, animation, dark moderules/typography-and-color.md — font loading, full palette tables, old-style figuresrules/anti-patterns.md — per-library detection heuristics and fixesrules/small-multiples-sparklines.md — layout patterns for small multiples, sparklines, slopegraphsWorking examples in examples/ — one per library, plus an inline SVG sparkline.
© caylent, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 33 other files in the repository root of caylent/tufte-data-viz.
Open the folder on GitHubat commit ae7ca0d
Tufte Data Viz 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 |
|---|---|---|---|---|---|---|
| Tufte Data Viz this skillcaylent/tufte-data-viz | 223 | — | ~3.5k | Automated safety check: Pass | MIT | |
| MatplotlibzLanqing/codex-claude-academic-skills | 4.7k | 17 repos | ~2.9k | Automated safety check: Pass | MIT | |
| Scientific Visualizationmims-harvard/OptimusKG | 147 | 19 repos | ~6.3k | Automated safety check: Pass | MIT | |
| SeabornzLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Ieee Figure TableCloudWave818/ieee-skills | 359 | — | ~1k | Automated safety check: Pass | MIT | |
| CJK Font Setup for Plotsxjtulyc/MedgeClaw | 617 | 1 repos | ~1.3k | Automated safety check: Pass | None |
zLanqing/codex-claude-academic-skills
Low-level plotting library for full customization. An agent skill from zLanqing/codex-claude-academic-skills.
mims-harvard/OptimusKG
Create publication figures with matplotlib/seaborn/plotly. An agent skill from mims-harvard/OptimusKG.
zLanqing/codex-claude-academic-skills
Statistical visualization with pandas integration. An agent skill from zLanqing/codex-claude-academic-skills.
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…
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.
Oleafly/Oleafly
Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly.
Works with
Categories
A skill your agent uses when creating, reviewing, or styling charts, graphs, dashboards, sparklines, or any data visualization. Tufte Data Viz is an agent skill from caylent/tufte-data-viz. Use when creating, reviewing, or styling charts, graphs, dashboards, sparklines, or any data visualization.
Tufte Data Viz fits situations like: any data visualization; tasks that involve Data visualization; tasks that involve Accessibility.
Run `npx skills add caylent/tufte-data-viz --skill tufte-data-viz -a claude-code`. Or copy the skill folder (the caylent/tufte-data-viz repository) into .claude/skills/tufte-data-viz in your project. Claude Code loads it when a task matches its description.
Run `npx skills add caylent/tufte-data-viz --skill tufte-data-viz -a codex`. Or copy the skill folder (the caylent/tufte-data-viz repository) into .agents/skills/tufte-data-viz in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add caylent/tufte-data-viz --skill tufte-data-viz -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tufte-data-viz, .gemini/skills/tufte-data-viz, .github/skills/tufte-data-viz and .opencode/skills/tufte-data-viz in your project.
Going by SKILL.md and its folder, Tufte Data Viz needs Python, JavaScript and TypeScript for the scripts in its folder. Our summary lists: Python 3; Node.js. Its frontmatter pre-approves these tools: Read, Glob, Grep.
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.
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.
Tufte Data Viz is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Tufte Data Viz: Matplotlib (zLanqing/codex-claude-academic-skills, 4.7k stars), Scientific Visualization (mims-harvard/OptimusKG, 147 stars), Seaborn (zLanqing/codex-claude-academic-skills, 4.7k stars) and Ieee Figure Table (CloudWave818/ieee-skills, 359 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
caylent (a GitHub organization) maintains it in caylent/tufte-data-viz, which has 223 GitHub stars. The repository was last updated on February 19, 2026.
Source: caylent/tufte-data-viz on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.