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dataviz

Design guidance for charts, graphs, dashboards, maps, and data visualizations, including a local palette validator.

来源信息

仓库
QwenLM/qwen-code
最近来源活动
2026年7月3日 01:06
检测到的 SKILL.md 语言
英语
星标
28,508
分支
3,214

安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

检查来源文件

决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

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SKILL.md
来源说明 · 只读预览
name
dataviz
description
Design guidance for charts, graphs, dashboards, maps, and data visualizations, including a local palette validator.
when_to_use
When creating or revising charts, graphs, dashboards, maps, plots, inline SVG, D3, Plotly, Recharts, matplotlib, or any Artifact page that visualizes data.
allowedTools
["read_file"]
# Dataviz Use this skill before producing a chart, dashboard, map, or data visualization. ## Workflow 1. Identify the analytic task: comparison, trend, distribution, relationship, ranking, part-to-whole, geography, or status monitoring. 2. Choose the simplest chart form that answers that task. Read `references/choosing-a-form.md` when the form is not obvious. 3. Write the finding into the title, subtitle, axis label, or direct annotation. A viewer should know what changed, what is high or low, or what decision the chart supports. 4. Pick colors from `references/palette.md`, or validate any custom palette with the script below. 5. Check `references/anti-patterns.md` before finalizing the design. ## Palette Validation Resolve paths relative to the skill base directory shown above this skill body. Do not assume `$QWEN_SKILL_ROOT` is set for normal shell commands. Run: ```bash node <skill-base-directory>/scripts/validate_palette.js '#1d4ed8,#b45309,#166534' --mode light ``` Treat `FAIL` as a required palette change. Treat `WARN` as acceptable only when the chart also uses labels, shape, texture, ordering, or another secondary encoding. ## Mark Rules - Use categorical palettes for unordered groups; use sequential or diverging ramps only for ordered values. - Prefer direct labels over legends when the chart has a small number of series. - Keep gridlines subtle and fewer than the data marks. - Avoid dual axes unless both series share a clearly explained transformation. - Do not rely on color alone for critical distinctions. - Keep dashboards scan-friendly: align cards, use consistent number formats, and reserve saturated color for important state changes.
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