# Visualization Best Practices

> Review chart choice, labeling, accessibility, and storytelling quality for existing visualizations. Use as an explicit/manual helper for critique and cleanup, not as the main owner for scientific figure production or general chart generation.

- Skill: `majiayu000/visualization-best-practices` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/visualization-best-practices`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/visualization-best-practices/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Web & Frontend
- License: MIT
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/visualization-best-practices

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# Visualization Best Practices

## Positioning

Treat this skill as an explicit/manual review helper.

## When to Use

Use this skill when:
- Reviewing whether an existing chart communicates clearly
- Fixing labels, legends, scales, color choices, or accessibility issues
- Deciding how to simplify a crowded dashboard or figure draft

## Not For / Boundaries

- Creating the chart from raw data: use `creating-data-visualizations`
- Journal-ready, multi-panel, publication submission figures: use `scientific-visualization`
- Schematics, flowcharts, or mechanism diagrams: use `scientific-schematics`

## Typical Outputs

- Critique of the current visualization problems
- Concrete fixes for encodings, layout, and readability
- A short checklist for accessibility and audience fit

## Related Skills

- `creating-data-visualizations` for general chart production
- `scientific-visualization` when the figure must meet publication standards