Agent skill

Visualization Chooser

Visualization type selection matrix by data type and analysis purpose, matplotlib/seaborn/plotly implementation pattern guide.

Apache-2.0Auto-check passedData & Analytics

Install Visualization Chooser

skills CLI

$ npx skills add revfactory/harness-100 --skill visualization-chooser -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install revfactory/harness-100 visualization-chooser --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .claude/skills && cp -r skills-src/en/32-data-analysis/.claude/skills/visualization-chooser .claude/skills/visualization-chooser && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "visualization-chooser" agent skill from https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser into .claude/skills/visualization-chooser/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-chooser", 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

$skill-installer install https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser

Type 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.

skills CLI

$ npx skills add revfactory/harness-100 --skill visualization-chooser -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install revfactory/harness-100 visualization-chooser --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .agents/skills && cp -r skills-src/en/32-data-analysis/.claude/skills/visualization-chooser .agents/skills/visualization-chooser && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "visualization-chooser" agent skill from https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser into .agents/skills/visualization-chooser/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-chooser", 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.

skills CLI

$ npx skills add revfactory/harness-100 --skill visualization-chooser -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install revfactory/harness-100 visualization-chooser --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/en/32-data-analysis/.claude/skills/visualization-chooser .cursor/skills/visualization-chooser && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "visualization-chooser" agent skill from https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser into .cursor/skills/visualization-chooser/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-chooser", 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

$ gemini skills install https://github.com/revfactory/harness-100.git --path en/32-data-analysis/.claude/skills/visualization-chooser

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add revfactory/harness-100 --skill visualization-chooser -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install revfactory/harness-100 visualization-chooser --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/en/32-data-analysis/.claude/skills/visualization-chooser .gemini/skills/visualization-chooser && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "visualization-chooser" agent skill from https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser into .gemini/skills/visualization-chooser/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-chooser", 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.

GitHub CLI

$ gh skill install revfactory/harness-100 visualization-chooser

Installs 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).

skills CLI

$ npx skills add revfactory/harness-100 --skill visualization-chooser -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .github/skills && cp -r skills-src/en/32-data-analysis/.claude/skills/visualization-chooser .github/skills/visualization-chooser && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "visualization-chooser" agent skill from https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser into .github/skills/visualization-chooser/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-chooser", 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.

skills CLI

$ npx skills add revfactory/harness-100 --skill visualization-chooser -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install revfactory/harness-100 visualization-chooser --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/en/32-data-analysis/.claude/skills/visualization-chooser .opencode/skills/visualization-chooser && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "visualization-chooser" agent skill from https://github.com/revfactory/harness-100/tree/main/en/32-data-analysis/.claude/skills/visualization-chooser into .opencode/skills/visualization-chooser/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-chooser", 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: visualization-chooser
GitHub stars: 1.3k
Token cost: ~1.3k tokens
SKILL.md length: 289 words
Files: 1
Skills in repo: 464
Repo updated: Mar 22, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Visualization type selection matrix by data type and analysis purpose, matplotlib/seaborn/plotly implementation pattern guide.

Data visualization design involving visualization selection
SKILL.md covers Visualization Selection Matrix, Implementation Code Patterns, Visualization Anti-patterns and Interactive Visualization…, plus 1 more section
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
Dashboard layout

What it does

Visualization Chooser is an agent skill from revfactory/harness-100. Visualization type selection matrix by data type and analysis purpose, matplotlib/seaborn/plotly implementation pattern guide. Use this skill for data visualization design involving 'visualization selection', 'chart type', 'graph types', 'matplotlib', 'seaborn', 'plotly', 'heatmap', 'scatter plot', 'box plot', 'dashboard layout', etc. Enhances the visualizer's visualization design capabilities. Note: statistical analysis and data cleaning are outside this skill's scope.

Its SKILL.md is about 1.3k 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 Plotly, Matplotlib and Seaborn. The licence is Apache-2.0.

When your agent uses it

Data visualization design involving visualization selection
Dashboard layout

Example prompts

“visualization selection”
“chart type”
“graph types”
“/visualization-chooser”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 8e8d35c. 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

Visualization Chooser loads about 1.3k tokens when it runs. Until then it costs about 124 tokens; SKILL.md has 289 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~124
When it runs · the whole SKILL.md, loaded when a task matches: ~1.3k

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 revfactory/harness-100 at commit 8e8d35c, republished under its Apache-2.0 licence (© revfactory). 289 words, ~1,294 tokens.

Download SKILL.mdSave it as .claude/skills/visualization-chooser/SKILL.md (or your agent's skills folder).

name: visualization-chooser
description: Visualization type selection matrix by data type and analysis purpose, matplotlib/seaborn/plotly implementation pattern guide. Use this skill for data visualization design involving 'visualization selection', 'chart type', 'graph types', 'matplotlib', 'seaborn', 'plotly', 'heatmap', 'scatter plot', 'box plot', 'dashboard layout', etc. Enhances the visualizer's visualization design capabilities. Note: statistical analysis and data cleaning are outside this skill's scope.

Visualization Chooser — Visualization Type Selection Matrix Guide

A framework for selecting optimal visualizations based on data type and communication purpose.

Visualization Selection Matrix

Comparison

Purpose	Chart	Suitable	Example
Item comparison	Bar chart	5-15 categories	Sales by product
Time trend comparison	Line chart	Continuous time, 2-5 series	Monthly sales trend
Part-to-whole	Stacked bar	Ratio comparison	Sales by channel share
Few ratios	Pie chart	2-5 items only	Market share
Many ratios	Treemap	Hierarchical data	Sales by category

Distribution

Purpose	Chart	Suitable	Example
Single distribution	Histogram	Continuous variable	Age distribution
Distribution comparison	Box plot	Group comparison	Salary by department
Density comparison	Violin plot	Distribution shape matters	Score distribution
Outlier emphasis	Strip plot	Small data	Individual data points

Relationship

Purpose	Chart	Suitable	Example
Two-variable relationship	Scatter plot	Continuous×Continuous	Ad spend vs sales
Multi-variable correlation	Heatmap	Correlation matrix	Inter-variable correlation
Trend line	Regression plot	Linear relationship	Experience vs salary
Density scatter	2D density	Too many data points	Location data
Bubble chart	Scatter + size	3 variables	GDP/population/life expectancy by country

Time

Purpose	Chart	Suitable	Example
Trend	Line chart	Continuous time series	Daily stock price
Seasonality	Decomposition chart	Periodic patterns	Monthly electricity usage
Event highlight	Annotated line	Specific time points	Marketing campaign effect
Range	Area chart	Cumulative/ratio	Traffic by channel

Implementation Code Patterns

Font Configuration (Essential for non-Latin scripts)

python

import matplotlib.pyplot as plt
import platform

if platform.system() == 'Darwin':  # macOS
    plt.rcParams['font.family'] = 'AppleGothic'
elif platform.system() == 'Windows':
    plt.rcParams['font.family'] = 'Malgun Gothic'
else:  # Linux
    plt.rcParams['font.family'] = 'NanumGothic'
plt.rcParams['axes.unicode_minus'] = False

Color Palettes

python

# Sequential (continuous values)
palette_sequential = 'YlOrRd'

# Categorical (discrete)
palette_categorical = ['#4C72B0', '#55A868', '#C44E52', '#8172B3', '#CCB974']

# Diverging (bipolar)
palette_diverging = 'RdBu_r'

# Accessibility-friendly
palette_colorblind = sns.color_palette('colorblind')

Dashboard Layout

python

fig, axes = plt.subplots(2, 3, figsize=(18, 10))
fig.suptitle('Sales Analysis Dashboard', fontsize=16, fontweight='bold')

# KPI Card (text-based)
axes[0,0].text(0.5, 0.5, f'Total Sales\n${total:,.0f}', ha='center', va='center', fontsize=20)

# Trend chart
axes[0,1].plot(dates, sales, '-o')

# Distribution
axes[0,2].boxplot([q1, q2, q3, q4])

# Comparison
axes[1,0].barh(categories, values)

# Correlation
sns.heatmap(corr_matrix, ax=axes[1,1], annot=True, cmap='RdBu_r')

# Pie
axes[1,2].pie(shares, labels=channels, autopct='%1.1f%%')

plt.tight_layout()

Visualization Anti-patterns

Anti-pattern	Problem	Solution
3D charts	Distortion, hard to read	Use 2D
Dual Y-axes	Misleading comparisons	Separate charts or normalize
Pie with >5 slices	Cannot compare	Switch to bar chart
Rainbow colors	Hard to distinguish patterns	Use sequential/categorical palettes
Y-axis not starting at 0	Exaggerates differences	Start Y-axis from 0
Information overload	Misses the point	Focus on one highlight
No legend	Cannot interpret	Clear legends/labels

Interactive Visualization (Plotly)

python

import plotly.express as px

# Scatter + color + size + hover
fig = px.scatter(
    df, x='ad_spend', y='sales',
    color='category', size='customers',
    hover_data=['product_name'],
    title='Ad Spend vs Sales Analysis'
)
fig.show()

# Plotly → HTML export
fig.write_html('interactive_chart.html')

Executive Report Visualization Principles

1. One key message: One insight per chart
2. Title = Conclusion: "Sales declined 15%" (O) vs "Monthly Sales" (X)
3. Color = Meaning: Red=bad, Green=good, Gray=baseline
4. Annotations: Display key figures directly
5. Comparison baseline: Prior month, prior year, target, industry average

Files

Just SKILL.md in en/32-data-analysis/.claude/skills/visualization-chooser of revfactory/harness-100.

Open the folder on GitHubat commit 8e8d35c

Compare with similar skills

Visualization Chooser 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.

Visualization Chooser compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Visualization Chooser this skillrevfactory/harness-100	1.3k	—	~1.3k	Automated safety check: Pass	Apache-2.0	6 mo ago
MatplotlibzLanqing/codex-claude-academic-skills	4.6k	17 repos	~2.9k	Automated safety check: Pass	MIT	4 mo ago
Scientific Visualizationmims-harvard/OptimusKG	146	19 repos	~6.3k	Automated safety check: Pass	MIT	16 days ago
SeabornzLanqing/codex-claude-academic-skills	4.6k	16 repos	~4.9k	Automated safety check: Pass	BSD-3-Clause	4 mo ago
CJK Font Setup for Plotsxjtulyc/MedgeClaw	617	1 repos	~1.3k	Automated safety check: Pass	None	6 mo ago
Tufte Data Vizcaylent/tufte-data-viz	222	—	~3.5k	Automated safety check: Pass	MIT	7 mo ago

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Questions about Visualization Chooser

What does Visualization Chooser do?

Visualization type selection matrix by data type and analysis purpose, matplotlib/seaborn/plotly implementation pattern guide. Visualization Chooser is an agent skill from revfactory/harness-100. Visualization type selection matrix by data type and analysis purpose, matplotlib/seaborn/plotly implementation pattern guide.

When should I use Visualization Chooser?

Visualization Chooser fits situations like: data visualization design involving visualization selection; dashboard layout.

How do I install Visualization Chooser in Claude Code?

Run `npx skills add revfactory/harness-100 --skill visualization-chooser -a claude-code`. Or copy the skill folder (en/32-data-analysis/.claude/skills/visualization-chooser in revfactory/harness-100) into .claude/skills/visualization-chooser in your project. Claude Code loads it when a task matches its description.

How do I install Visualization Chooser in Codex?

Run `npx skills add revfactory/harness-100 --skill visualization-chooser -a codex`. Or copy the skill folder (en/32-data-analysis/.claude/skills/visualization-chooser in revfactory/harness-100) into .agents/skills/visualization-chooser in your project. Codex loads it when a task matches its description.

Can I use Visualization Chooser 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 revfactory/harness-100 --skill visualization-chooser -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/visualization-chooser, .gemini/skills/visualization-chooser, .github/skills/visualization-chooser and .opencode/skills/visualization-chooser in your project.

What does Visualization Chooser need to run?

SKILL.md names no scripts, command-line tools or credentials: Visualization Chooser is instructions for the agent only. Our summary lists: Python 3.

Does Visualization Chooser 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 Visualization Chooser 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 Visualization Chooser use?

Visualization Chooser is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Visualization Chooser use?

About 1.3k tokens (SKILL.md is roughly 5.2k 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 Visualization Chooser?

Skills that share tags, products or a category with Visualization Chooser: 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 CJK Font Setup for Plots (xjtulyc/MedgeClaw, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Visualization Chooser?

revfactory (a GitHub user) maintains it in revfactory/harness-100, which has 1,290 GitHub stars. The repository holds 464 skills in this directory. The repository was last updated on March 22, 2026.

Source: revfactory/harness-100 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Visualization Chooser

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Visualization Chooser — Visualization Type Selection Matrix Guide

Visualization Selection Matrix

Comparison

Distribution

Relationship

Time

Implementation Code Patterns

Font Configuration (Essential for non-Latin scripts)

Color Palettes

Dashboard Layout

Visualization Anti-patterns

Interactive Visualization (Plotly)

Executive Report Visualization Principles

Files

Compare with similar skills

Similar skills

More from revfactory/harness-100

Related

Questions about Visualization Chooser