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Color Grading Contrast Saturation

Community
geegl
color-grading-contrast-saturation

用户提到对比度调完颜色变了、饱和度、RGB处理

Overview

Publishergeegl
Repositorydirectorskills
Skill namecolor-grading-contrast-saturation
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 Contrast Saturation 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-contrast-saturation
  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-contrast-saturation .claude/skills/color-grading-contrast-saturation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Color Grading Contrast Saturation 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 Contrast Saturation 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 Contrast Saturation 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.

对比度与饱和度联动效应

R — 原文 (Reading)

在RGB色彩空间中处理对比度时，饱和度会随之增加。扩大对比度后需检查并补偿饱和度增加。

— Van Hurkman, 第3章、第4章、第9章, p.g_0042

I — 方法论骨架 (Interpretation)

对比度和饱和度在RGB色彩空间中是联动的——扩大对比度会同时增加饱和度，降低对比度会降低饱和度。这是RGB处理的物理特性，不是软件bug。

核心规则：每次调整对比度后，必须检查饱和度是否过度增加。如果使用Y-only（亮度-only）处理对比度则不会有此问题，但大多数软件默认使用RGB处理。

独特价值：很多调色师发现'调完对比度颜色不对了'但不知道原因——联动效应是根本原因。

A1 — 书中的应用 (Past Application)

案例 1

  • 问题: 如何在实际调色中应用此原理
  • 方法论的使用: 调色师扩大了画面对比度（提高Gain降低Lift），发现角色肤色变得过于饱和。原因：RGB处理对比度时，高光和暗部的饱和度都被推高了。解决方案：在调整对比度后，略微降低全局饱和度来补偿。
  • 结论: 对比度和饱和度是联动的——调对比度时必须同时检查饱和度，否则皮肤会变成塑料感
  • 结果: 高对比度画面中肤色保持自然血色，不再出现"对比度拉满后人脸变蜡像"的问题

案例 2: 《疯狂的麦克斯：狂暴之路》沙漠场景

  • 问题: 调色师提高对比度强化沙漠的灼热感后，橙色沙地和蓝色天空的饱和度同时暴涨，画面变得刺眼
  • 方法论的使用: 发现RGB处理下Gain提升直接推高了饱和度。解决方案：先调好对比度，再用色相/饱和度曲线单独压低橙色和蓝色通道的饱和度，保留对比度的同时恢复自然色彩
  • 结论: 对比度与饱和度的联动是物理特性而非软件bug，必须主动补偿
  • 结果: 画面保持了强烈的对比度但色彩不再过饱和

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 对比度调完颜色变了
  2. 饱和度太高怎么办
  3. RGB处理的副作用

语言信号 (用户的话里出现这些就应激活)

  • "对比度"
  • "饱和度"
  • "RGB"
  • "颜色变了"
  • "太饱和"

与相邻 skill 的区分

  • 与 color-grading-primary-workflow 的区别: primary-workflow 是整体工作流，本 skill 聚焦特定技术原理
  • 与 color-grading-look-development 的区别: look-development 是创意风格，本 skill 是技术校准

E — 可执行步骤 (Execution)

当 skill 被激活后, agent 应按以下步骤执行:

  1. 调整对比度

    • 完成标准: 按正常流程调整Lift/Gamma/Gain。完成标准：对比度范围符合预期

  2. 检查饱和度变化

    • 完成标准: 用矢量示波器检查饱和度是否过度增加。完成标准：肤色仍在楔形范围内
    • 判停条件: 若条件不满足，先确认素材质量和监视器校准

  3. 补偿饱和度

    • 完成标准: 如果饱和度过度，降低全局饱和度或用HSL选色只补偿问题区域。完成标准：色彩自然

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 不要忽略对比度调整后的饱和度变化——这是最常见的隐蔽错误
  • 不要在不理解RGB vs Y-only差异的情况下选择处理方式

作者在书中警告的失败模式

  • 对比度调整后肤色过度饱和——最常见的联动效应问题
  • 降低对比度后画面变得灰暗——同时降低了饱和度但没有补偿

作者的盲点

作者假设调色师理解RGB处理的物理特性，但很多初学者不知道联动效应的存在。此外，某些软件的对比度控件可能使用Y-only处理，不会产生联动效应。

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 Contrast Saturation AI skill do?

用户提到对比度调完颜色变了、饱和度、RGB处理

Why use Color Grading Contrast Saturation on TypingMind?

Because you install it once and use it with any model. Color Grading Contrast Saturation 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 Contrast Saturation 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-contrast-saturation. 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 Contrast Saturation?

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 Contrast Saturation?

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

Is the Color Grading Contrast Saturation 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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