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Color Grading Skin Tone Vectorscope logo

Color Grading Skin Tone Vectorscope

Community
geegl
color-grading-skin-tone-vectorscope

所有人种的肤色在矢量示波器上都落在围绕I-bar的狭窄楔形范围内。RGB分量示波器上肤色总是红色通道最强。调色师应利用这一物理事实作为色彩平衡的基准点。

Overview

Publishergeegl
Repositorydirectorskills
Skill namecolor-grading-skin-tone-vectorscope
Stars
68
Forks
7
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by geegl on GitHub. Read the source before you install it.

Installation

Install the Color Grading Skin Tone Vectorscope AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/geegl/directorskills/tree/main/output/books/color-grading/color-grading-skin-tone-vectorscope
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/geegl/directorskills.git /tmp/directorskills
mkdir -p .claude/skills
cp -r /tmp/directorskills/output/books/color-grading/color-grading-skin-tone-vectorscope .claude/skills/color-grading-skin-tone-vectorscope
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Color Grading Skin Tone Vectorscope in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Color Grading Skin Tone Vectorscope on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Color Grading Skin Tone Vectorscope is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

肤色在矢量示波器上的楔形范围原则

R — 原文 (Reading)

肤色有可能出现的所有色调范围被限制在很明显的一簇波形中，在这个范围内波形仍有足够的变化空间。 — Van Hurkman, 第8章, p.g_0068

I — 方法论骨架 (Interpretation)

肤色是调色中最重要的参考色彩之一，因为人类对肤色极为敏感。关键发现：所有人的肤色——无论种族——在矢量示波器上都落在围绕I-bar（肤色线）的狭窄楔形范围内，色相差异通常不超过5度。

物理原因：肤色由黑色素（棕/黄色）、血红蛋白（红色）和β-胡萝卜素（橙色）三种物质决定，这三种物质的组合比例决定了肤色在矢量示波器上的精确位置。深色皮肤吸收更多光线减少血红蛋白交互，但不显著改变色相。

在RGB分量示波器上，肤色总是表现为：红色通道最强、绿色通道较弱、蓝色通道最弱。这一规律是判断画面偏色的快速方法。

A1 — 书中的应用 (Past Application)

案例：210位泳装模特肤色采样分析 (第8章)

  • 问题: 不同人种的肤色在矢量示波器上的分布范围有多大？
  • 方法论的使用: 从210位模特（亚洲人、非裔、印度人、高加索人等）的肤色采样，在矢量示波器上分析
  • 结论: 所有肤色波形形成紧密的一簇，围绕I-bar在狭窄范围内变化

案例 2: 多人种群戏肤色平衡

  • 问题: 一场包含亚裔、非裔、白人演员的群戏，调色后非裔演员肤色偏绿、亚裔演员肤色偏黄，但白人肤色正常
  • 方法论的使用: 用矢量示波器逐一检查每位演员的肤色波形，发现非裔肤色偏离I-bar左侧15度（偏黄绿），亚裔偏离右侧8度（偏红橙）。用色彩平衡控件将所有肤色波形推回I-bar附近5度范围内，同时保留各人种间的自然色相差异
  • 结论: 肤色楔形范围是所有调色的隐性基准——偏离超过15度观众就会觉得'不对'
  • 结果: 所有演员肤色看起来健康自然，群戏画面色彩协调

A2 — 触发场景 (Future Trigger) ★

  1. 画面偏色但难以判断方向——检查肤色波形与I-bar的距离
  2. 需要快速判断一级校色是否正确——肤色是最快捷的参考
  3. 多人镜头中不同肤色需要平衡——参考楔形范围判断差异

语言信号

  • "肤色看起来不对/偏黄/偏绿/偏红"
  • "怎么判断画面偏色"
  • "肤色应该放在哪里"

E — 可执行步骤 (Execution)

  1. 在矢量示波器上找到肤色波形——应在I-bar附近

  2. 判断偏色方向——偏I-bar左侧=偏黄/橙，偏右侧=偏红

  3. 用色彩平衡控件调整——将肤色波形推回I-bar附近

  4. 在RGB分量示波器上确认——红>绿>蓝的顺序应保持

    • 🔴 判停条件: 若肤色在示波器上偏离肤色线超过15度，或不同肤色人物之间色差过大——检查是否在正确的色域（REC.709/LOG）下判断，用色相/饱和度曲线局部修正

B — 边界 (Boundary) ★

  • I-bar是参考而非标准——不同肤色在I-bar两侧有自然差异
  • 不要把所有肤色都推到同一点——保持自然差异
  • 失败模式: 过度追求I-bar对齐导致肤色失去个性和自然感

反模式与常见错误

  • 把所有肤色推到I-bar同一点：I-bar是参考范围而非精确目标，不同人种在I-bar两侧有自然差异（约5度色相），强制对齐会让所有肤色看起来"塑料化"
  • 在错误的色域空间判断示波器：REC.709的I-bar位置不适用于广色域素材（REC.2020/ACES），在错误色域下判断会导致校色偏差
  • 忽略RGB分量示波器的交叉验证：仅凭矢量示波器判断肤色不够可靠，必须同时确认RGB分量示波器上红>绿>蓝的顺序

作者的盲点 / 时代局限

Alexis Van Hurkman 的调色方法论基于专业 DaVinci Resolve 工作流，对轻量级工具（如 Premiere Lumetri、手机调色 App）的适配讨论不足。他假设调色师有参考级监视器和校色环境，独立创作者在消费级显示器上的调色策略覆盖较少。书中色彩科学理论偏重 REC.709，对 HDR/WCG 工作流的实操指导相对薄弱。

此外，示波器分析皮肤色调的方法偏重 REC.709 色域，对广色域素材（如 REC.2020、ACES）的皮肤色调判断标准讨论不足。此外，他假设所有肤色的'正确'向量位置相同，未充分讨论不同人种的皮肤色调差异和文化审美偏好。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Color Grading Skin Tone Vectorscope AI skill do?

所有人种的肤色在矢量示波器上都落在围绕I-bar的狭窄楔形范围内。RGB分量示波器上肤色总是红色通道最强。调色师应利用这一物理事实作为色彩平衡的基准点。

Why use Color Grading Skin Tone Vectorscope on TypingMind?

Because you install it once and use it with any model. Color Grading Skin Tone Vectorscope is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Color Grading Skin Tone Vectorscope in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/geegl/directorskills/tree/main/output/books/color-grading/color-grading-skin-tone-vectorscope. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Color Grading Skin Tone Vectorscope?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Color Grading Skin Tone Vectorscope?

As many as you like. As long as a model supports skills, you can use Color Grading Skin Tone Vectorscope with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Color Grading Skin Tone Vectorscope AI skill free?

Yes. It is published on GitHub by geegl under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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