
Chart Color Audit
io.github.socraticstatic由 GitHub 账号 socraticstatic 发布v0.2.5更新于 Nov 1, 2026
CI-friendly accessibility audit for chart color palettes: WCAG contrast, CVD simulation, OKLab ΔE.
发布方自己的服务:audit.domains - Domain Valuation
概览
审计图表配色对色盲用户的区分度与 WCAG 对比度,让助手用测量数据而非主观判断来评估调色板。
- 可以做什么
- 审计粘贴的配色:模拟绿色盲、红色盲、蓝色盲及全色盲,测量 OKLab 两两色差与相对背景的对比度
- 审计配置文件中的设计令牌:从 CSS 自定义属性或 design-tokens JSON 读取数据系列、语义色与文字色,并给出具名问题
- 返回每种视觉模拟下的最小色差、最接近的一对、分级区间,以及通过或失败结论和可读的失败原因
- 适用场景
- 适合在挑选或评审仪表盘、图表配色时使用,需要以测量结果回答数据系列对色盲用户是否仍可区分、是否达到对比度下限,而不是凭感觉判断。
- 运行要求
- 通过 npx 从 npm 包 chart-color-audit 以 stdio 在本地运行;未声明认证、环境变量或请求头。令牌审计需读取 chartaudit.config.json 等配置文件,并指向 CSS 或 design-tokens 文件。审计本身不需要网络访问。
安装
在 SourceWeft 中
- 打开 控制台中的 Chart Color Audit,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
chart-color-audit
Accessibility audit for chart color palettes. Answers one question with math: can everyone still tell your data series apart?
Plenty of tools check text contrast. This one checks the thing dashboards actually break: whether your palette survives colorblindness. It simulates deuteranopia, protanopia, and tritanopia with the published Machado, Oliveira & Fernandes 2009 matrices, measures pairwise separation in OKLab, checks WCAG 2.2 contrast against your background, and fails your build when a change quietly breaks any of it.
Four ways in. Pick yours.
1 · Try a palette (nothing to install)
Those three colors separate cleanly under every colorblind simulation. The orange still fails: 2.42:1 against white, below the 3:1 floor for chart marks. Pale bars on white is one of the oldest dashboard sins, and this is it, caught in numbers.
Exit codes: 0 pass, 1 fail, 2 bad input. That is the whole CI
contract.
Reading the output
ΔE is perceptual color distance (OKLab × 100). About 2 is the edge of what a human eye can tell apart.
closest pair names the two slots (1-based) that came nearest. Fix those
two, re-run, repeat.
CLI
2 · Gate your CI
Two files, no dependencies added.
Step 1. Put chartaudit.config.json in your repo root, pointed at the
tokens you already have:
Step 2. Add the workflow:
Done. A token edit that breaks a floor now exits 1 with named findings, in the PR, before anyone screenshots anything.
Prefer a pinned dependency? npm i -D chart-color-audit and call it from a
package script. Same behavior.
The famous-palette test
That is Tableau 10, one of the most-shipped chart palettes on earth, on a white dashboard:
Its red and green sit ΔE 0.7 apart under deuteranopia simulation. Roughly 1 in 12 men has red-green color vision deficiency; for most of them, series 3 and series 5 on that chart are the same color. Nothing in code review catches this. Math does.
3 · Call it from code
Fully typed. Two data dependencies (culori for color math, the MCP SDK for the server). No DOM, no network.
4 · Wire it into an agent (MCP)
Let an agent audit colors mid-conversation:
Two read-only tools: audit_palette (paste colors) and audit_tokens
(point at a config). Ask "is this palette colorblind-safe on white?" and the
answer comes back with measurements instead of vibes.
Listed in the official MCP Registry
as io.github.socraticstatic/chart-color-audit and on
Glama.
Floors
Text tokens are checked at 4.5:1 in every mode. Changing default floors is a major version, always: a CI gate that tightens defaults in a patch release breaks builds and trust.
Honest scope
Tokens in, findings out. This audits declared palette colors. It does not render charts, screenshot pixels, or crawl pages. Contrast checkers for text exist in plenty; what this adds is the part I could not find anywhere else: CVD-simulated series separation, as a build gate and an MCP tool.
Where this came from
The engine was extracted from a chart color system whose own history proves the point: an "accuracy fix" commit once replaced the correct deuteranopia matrix with confident, plausible, fabricated values, and review passed it. Only a pinned regression test would have caught it, so this package pins the matrices against the published paper in its test suite, permanently.
The full story: docs/POSTMORTEM.md: nine weeks of a wrong matrix, the AI-co-authored commit that forged it, and why the math now checks the math.
Consulting
I audit dashboards and design systems for exactly these failures. 30 years of UX practice, and the math above to prove findings instead of arguing them. [email protected]
MIT © Micah Boswell
来源:README.md,提交 5624266
工具
0版本历史
2- v0.2.5最新Oct 4, 2026
- v0.2.4Sep 16, 2026
评分
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