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Agent skill

Visualization Chooser

by revfactory in revfactory/harness-100

데이터 유형과 분석 목적에 따른 시각화 유형 선택 매트릭스, matplotlib/seaborn/plotly 구현 패턴 가이드.

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/ko/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/

Facts

Skill name
visualization-chooser
GitHub stars
1.3k
Token cost
~820 tokens
SKILL.md length
258 words
Files
1
Skills in repo
464
Repo updated
First seen
Licence
Apache-2.0

At a glance

데이터 유형과 분석 목적에 따른 시각화 유형 선택 매트릭스, matplotlib/seaborn/plotly 구현 패턴 가이드.

  • Tasks that involve Data visualization
  • SKILL.md covers 시각화 선택 매트릭스, 구현 코드 패턴, 시각화 안티패턴 and 인터랙티브 시각화 (Plotly), plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Visualization Chooser is an agent skill from revfactory/harness-100. 데이터 유형과 분석 목적에 따른 시각화 유형 선택 매트릭스, matplotlib/seaborn/plotly 구현 패턴 가이드. '시각화 선택', '차트 유형', '그래프 종류', 'matplotlib', 'seaborn', 'plotly', '히트맵', '산점도', '박스플롯', '대시보드 레이아웃' 등 데이터 시각화 설계 시 이 스킬을 사용한다. visualizer의 시각화 설계 역량을 강화한다. 단, 통계 분석이나 데이터 정제는 이 스킬의 범위가 아니다.

Its SKILL.md is about 820 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

  • Tasks that involve Data visualization

Example prompts

  • “matplotlib”
  • “seaborn”
  • “plotly”
  • “/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 820 tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 258 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~820

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). 258 words, ~820 tokens.

Download SKILL.mdSave it as .claude/skills/visualization-chooser/SKILL.md (or your agent's skills folder).
name
visualization-chooser
description
데이터 유형과 분석 목적에 따른 시각화 유형 선택 매트릭스, matplotlib/seaborn/plotly 구현 패턴 가이드. '시각화 선택', '차트 유형', '그래프 종류', 'matplotlib', 'seaborn', 'plotly', '히트맵', '산점도', '박스플롯', '대시보드 레이아웃' 등 데이터 시각화 설계 시 이 스킬을 사용한다. visualizer의 시각화 설계 역량을 강화한다. 단, 통계 분석이나 데이터 정제는 이 스킬의 범위가 아니다.

Visualization Chooser — 시각화 유형 선택 매트릭스 가이드

데이터 유형과 커뮤니케이션 목적에 맞는 최적의 시각화를 선택하는 프레임워크.

시각화 선택 매트릭스

비교
목적차트적합예시
항목 비교막대 차트5~15개 카테고리제품별 매출
시간 추이 비교라인 차트연속 시간, 2~5 시리즈월별 매출 추이
부분-전체스택 막대비율 비교채널별 매출 비중
소수 비율파이 차트2~5개 항목만시장 점유율
다수 비율트리맵계층적 데이터카테고리별 매출
분포
목적차트적합예시
단일 분포히스토그램연속 변수나이 분포
분포 비교박스플롯그룹별 비교부서별 급여
밀도 비교바이올린 플롯분포 형태 중요점수 분포
이상치 강조스트립 플롯소규모 데이터개별 데이터 포인트
관계
목적차트적합예시
두 변수 관계산점도연속×연속광고비 vs 매출
다변수 상관히트맵상관 매트릭스변수 간 상관
추세선회귀 플롯선형 관계경험 vs 급여
밀도 산점도2D 밀도데이터 과다위치 데이터
버블 차트산점도 + 크기3변수국가별 GDP/인구/기대수명
시간
목적차트적합예시
추세라인 차트연속 시계열일별 주가
계절성분해 그래프주기 패턴월별 전력 사용
이벤트 강조어노테이션 라인특정 시점마케팅 캠페인 효과
범위영역 차트누적/비율채널별 트래픽

구현 코드 패턴

한글 설정 (필수)
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
색상 팔레트
python
# 순서형 (연속 값)
palette_sequential = 'YlOrRd'

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

# 발산형 (양극)
palette_diverging = 'RdBu_r'

# 접근성 고려
palette_colorblind = sns.color_palette('colorblind')
대시보드 레이아웃
python
fig, axes = plt.subplots(2, 3, figsize=(18, 10))
fig.suptitle('매출 분석 대시보드', fontsize=16, fontweight='bold')

# KPI 카드 (텍스트 기반)
axes[0,0].text(0.5, 0.5, f'총 매출\n₩{total:,.0f}', ha='center', va='center', fontsize=20)

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

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

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

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

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

plt.tight_layout()

시각화 안티패턴

안티패턴문제해결
3D 차트왜곡, 읽기 어려움2D 사용
이중 Y축비교 오해 유발별도 차트 또는 정규화
파이 5개 초과비교 불가막대 차트 전환
레인보우 색상패턴 구분 어려움순서/범주 팔레트
0이 아닌 Y축 시작차이 과장Y축 0부터 시작
정보 과부하핵심 놓침강조점 하나에 집중
범례 없음해석 불가명확한 범례/라벨

인터랙티브 시각화 (Plotly)

python
import plotly.express as px

# 산점도 + 색상 + 크기 + 호버
fig = px.scatter(
    df, x='광고비', y='매출',
    color='카테고리', size='고객수',
    hover_data=['제품명'],
    title='광고비 대비 매출 분석'
)
fig.show()

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

경영진 보고서용 시각화 원칙

1. 핵심 메시지 하나: 차트당 하나의 인사이트
2. 제목 = 결론: "매출이 15% 하락했다" (O) vs "월별 매출" (X)
3. 색상 = 의미: 빨강=나쁨, 초록=좋음, 회색=기준
4. 어노테이션: 핵심 수치 직접 표시
5. 비교 기준: 전월, 전년, 목표, 업계 평균

© revfactory, Apache-2.0. 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 ko/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
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Visualization Chooser this skillrevfactory/harness-1001.3k—~820Automated safety check: PassApache-2.0
MatplotlibzLanqing/codex-claude-academic-skills4.6k17 repos~2.9kAutomated safety check: PassMIT
Scientific Visualizationmims-harvard/OptimusKG14619 repos~6.3kAutomated safety check: PassMIT
SeabornzLanqing/codex-claude-academic-skills4.6k16 repos~4.9kAutomated safety check: PassBSD-3-Clause
CJK Font Setup for Plotsxjtulyc/MedgeClaw6171 repos~1.3kAutomated safety check: PassNone
Tufte Data Vizcaylent/tufte-data-viz222—~3.5kAutomated safety check: PassMIT

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Works with

Categories

Questions about Visualization Chooser

What does Visualization Chooser do?

데이터 유형과 분석 목적에 따른 시각화 유형 선택 매트릭스, matplotlib/seaborn/plotly 구현 패턴 가이드. Visualization Chooser is an agent skill from revfactory/harness-100. 데이터 유형과 분석 목적에 따른 시각화 유형 선택 매트릭스, matplotlib/seaborn/plotly 구현 패턴 가이드.

When should I use Visualization Chooser?

Visualization Chooser fits situations like: tasks that involve Data visualization.

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 (ko/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 (ko/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 820 tokens (SKILL.md is roughly 3.3k 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.