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Color Grading Memory Colors

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geegl
color-grading-memory-colors

当用户需要校准画面色彩准确性、诊断'肤色不对'、或理解观众对色彩的心理预期时调用。核心 trigger：用户提到'肤色不对'、'天空颜色'、'色彩记忆'、'画面看起来不自然'。不适用于：用户讨论创意风格（用 look-development）。

Overview

Publishergeegl
Repositorydirectorskills
Skill namecolor-grading-memory-colors
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 Memory Colors 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-memory-colors
  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-memory-colors .claude/skills/color-grading-memory-colors
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Color Grading Memory Colors 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 Memory Colors 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 Memory Colors 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.

记忆色彩三大要素校准法

R — 原文 (Reading)

记忆色彩三大要素：肤色、天空、植物。观众对这三种颜色有强烈的记忆预期——如果偏离太多，画面会'看起来不对'。

— Van Hurkman, 第8章, p.g_0000

I — 方法论骨架 (Interpretation)

观众对三种颜色有强烈的记忆预期：肤色（所有人种在矢量示波器上落在同一狭窄楔形内）、天空（蓝色，不是紫色或绿色）、植物（绿色，不是黄色或蓝色）。这三种颜色如果偏离观众的记忆预期，画面会'看起来不对'，即使技术上是准确的。

独特价值：记忆色彩比实际色彩更饱和——研究显示观众记忆中的色彩比实际约饱和0.95孟塞尔色度值。这意味着调色师需要将记忆色彩调整到比实际更饱和的水平，才符合观众的心理预期。

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: 纪录片调色师发现，将天空调整到技术准确的蓝色后，观众觉得'不够蓝'。原因：观众记忆中的天空比实际更蓝。解决方案：将天空的饱和度略微提高到记忆色彩水平，而非技术准确水平。
  • 结论: 记忆色彩的容忍度极低——天空偏绿 5% 观众就能感知到，但衣服偏色 15% 可能没人注意。优先校准天空和肤色
  • 结果: 天空和肤色回到观众心理预期的"正确"色域，画面整体看起来"舒服"而非"技术准确但违和"

案例 2: 《指环王》中土世界植被校色

  • 问题: 新西兰实景拍摄的绿色植被在调色后偏黄，观众反馈'看起来不像中土世界'
  • 方法论的使用: 调色师发现植被色彩被调整到了技术准确的绿色，但观众记忆中的森林比实际更绿更浓郁。将植被饱和度提高到记忆色彩水平（比技术值约高1个孟塞尔色度），同时保持天空和肤色在各自记忆色彩范围内
  • 结论: 三大记忆色彩（肤色、天空、植物）都需要超越技术准确值才符合观众心理预期
  • 结果: 植被看起来更符合观众对'魔法森林'的想象，画面整体更自然

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 肤色不对怎么办
  2. 天空颜色怎么调
  3. 画面看起来不自然

语言信号 (用户的话里出现这些就应激活)

  • "肤色"
  • "天空"
  • "植物"
  • "记忆色彩"
  • "不自然"
  • "看起来不对"

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. 检查三大记忆色彩

    • 完成标准: 用矢量示波器检查肤色是否在楔形内、天空是否偏蓝、植物是否偏绿。完成标准：三种记忆色彩都在观众预期范围内

  2. 与技术准确值对比

    • 完成标准: 记忆色彩比技术准确值更饱和。完成标准：将色彩调整到记忆色彩水平而非技术准确水平
    • 判停条件: 若条件不满足，先确认素材质量和监视器校准

  3. 检查整体平衡

    • 完成标准: 三种记忆色彩的相对关系要正确。完成标准：肤色、天空、植物的色彩关系协调

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 不要只关注肤色而忽略天空和植物——三者需要协调
  • 不要将记忆色彩调整到技术准确值——观众会觉得'不够'

作者在书中警告的失败模式

  • 只校准肤色但天空偏紫——观众会觉得画面'不对'但说不出为什么
  • 将记忆色彩调整到技术准确水平——观众觉得'不够饱和'

作者的盲点

作者的记忆色彩研究主要基于西方观众，不同文化对记忆色彩的预期可能有差异。此外，数字摄影机的色彩科学可能已经预校正了记忆色彩。

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 Memory Colors AI skill do?

当用户需要校准画面色彩准确性、诊断'肤色不对'、或理解观众对色彩的心理预期时调用。核心 trigger：用户提到'肤色不对'、'天空颜色'、'色彩记忆'、'画面看起来不自然'。不适用于：用户讨论创意风格（用 look-development）。

Why use Color Grading Memory Colors on TypingMind?

Because you install it once and use it with any model. Color Grading Memory Colors 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 Memory Colors 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-memory-colors. 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 Memory Colors?

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 Memory Colors?

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

Is the Color Grading Memory Colors 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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