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visualizing-data

visualizing-data is a skill for Claude Code from ancoleman/ai-design-components. It costs 109 tokens per session (2,315 once invoked), scanned A, original, MIT.

A guide to turning data into charts, graphs, dashboards, and reports. It explains how to choose a visual format based on the data and the question you want to answer.

In plain words
What is it for?
Use it to build data dashboards and reports showing trends, comparisons, distributions, relationships, composition, flows, hierarchies, or geographic data.
Why use it?
It helps prevent charts that hide important patterns or mislead readers. It also covers accessibility and handling datasets of different sizes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ui-data-skills plugin — 3 skills shipped together

not rated 525repo 10mo ago A scan 109 tokens original MIT

Good fit Use it to build data dashboards and reports showing trends, comparisons, distributions, relationships, composition, flows, hierarchies, or geographic data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ancoleman/ai-design-components/visualizing-data
View source ↗ ancoleman/ai-design-components
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ancoleman/ai-design-components --skill visualizing-data
Clone the repo
git clone --depth 1 https://github.com/ancoleman/ai-design-components

Made for: Claude Code.

Or install ui-data-skills, the plugin that ships this one along with the rest of its 3 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for visualizing-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/ancoleman/ai-design-components/visualizing-data/github.svg)](https://agentmods.dev/skills/ancoleman/ai-design-components/visualizing-data)
Your own site
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/visualizing-data"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/visualizing-data/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for visualizing-data

Your own site · 80×15
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/visualizing-data"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/visualizing-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,315 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00109 $0.02315
Opus 5.5 $0.00044 $0.00926
Sonnet 5.5 $0.00022 $0.00463
Haiku 4.5 $0.00011 $0.00231

Measured 1mo ago against content hash 31cda9f7f770, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

visualizing-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 5 executable files (examples/skill-library-viz/skillLibraryData.ts, examples/skill-library-viz/vite.config.ts, scripts/generate_color_palette.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/visualizing-data/SKILL.md · 330 lines

How it starts

The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Visualization Component Library

Systematic guidance for selecting and implementing effective data visualizations, matching data characteristics with appropriate visualization types, ensuring clarity, accessibility, and impact.

Overview

Data visualization transforms raw data into visual representations that reveal patterns, trends, and insights. This skill provides:

  1. Selection Framework: Systematic decision trees from data type + purpose → chart type
  2. 24+ Visualization Methods: Organized by analytical purpose
  3. Accessibility Patterns: WCAG 2.1 AA compliance, colorblind-safe palettes
  4. Performance Strategies: Optimize for dataset size (<1000 to >100K points)
  5. Multi-Language Support: JavaScript/TypeScript (primary), Python, Rust, Go

Quick Start Workflow

Step 1: Assess Data

What type? [categorical | continuous | temporal | spatial | hierarchical]
How many dimensions? [1D | 2D | multivariate]
How many points? [<100 | 100-1K | 1K-10K | >10K]

Step 2: Determine Purpose

What story to tell? [comparison | trend | distribution | relationship | composition | flow | hierarchy | geographic]

Step 3: Select Chart Type

Quick Selection:

  • Compare 5-10 categories → Bar Chart
  • Show sales over 12 months → Line Chart
  • Display distribution of ages → Histogram or Violin Plot
  • Explore correlation → Scatter Plot
  • Show budget breakdown → Treemap or Stacked Bar

Complete decision trees: See references/selection-matrix.md

Step 4: Implement

See language sections below for recommended libraries.

Step 5: Apply Accessibility

  • Add text alternative (aria-label)
  • Ensure 3:1 color contrast minimum
  • Use colorblind-safe palette
  • Provide data table alternative

Step 6: Optimize Performance

  • <1000 points: Standard SVG rendering

  • 1000 points: Sampling or Canvas rendering

  • Very large: Server-side aggregation

Purpose-First Selection

Match analytical purpose to chart type:

Purpose Chart Types
Compare values Bar Chart, Lollipop Chart
Show trends Line Chart, Area Chart
Reveal distributions Histogram, Violin Plot, Box Plot
Explore relationships Scatter Plot, Bubble Chart
Explain composition Treemap, Stacked Bar, Pie Chart (<6 slices)
Visualize flow Sankey Diagram, Chord Diagram
Display hierarchy Sunburst, Dendrogram, Treemap
Show geographic Choropleth Map, Symbol Map

Read the full file on GitHub · 330 lines

Files

What ships with it

43 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 330 lines · 109 tokens per session scan A 31cda9f7f770

Subscribe to this mod's changes

visualizing-data is a skill published in the GitHub repository ancoleman/ai-design-components (525 stars, last pushed 10mo ago), licensed MIT. It adds 109 tokens to every session and 2,315 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Analytics and metricsClaude Codeai-designanthropicclaudeclaude-skillsdesign-system
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