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Shot Design Dialogue Staging

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geegl
shot-design-dialogue-staging

用户提到对话场景、对话怎么拍、两人/三人/多人对话、调度、staging

Overview

Publishergeegl
Repositorydirectorskills
Skill nameshot-design-dialogue-staging
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 Shot Design Dialogue Staging 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/shot-design/shot-design-dialogue-staging
  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/shot-design/shot-design-dialogue-staging .claude/skills/shot-design-dialogue-staging
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Shot Design Dialogue Staging 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 Shot Design Dialogue Staging 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 Shot Design Dialogue Staging 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.

I/L/A形态对话调度系统

R — 原文 (Reading)

形态决定摄影机位置，而摄影机位置又是根据动作轴线而来。位置决定了演员在画面中的站法，而站的位置又要依据基本的调度形态。 — Katz, 第十章, p.g_0052

重点并不是要我们记住所有可想到的关于演员和摄影机的调度，而是要强化你对构成一个镜头戏剧特性的元素彼此之间关系的知觉。 — Katz, 第九章

I — 方法论骨架 (Interpretation)

对话场景的调度可以用三种几何形态来系统化：

I形态：两位演员排成一条线（面对面、肩并肩、90°角等）。这是最基本的建构单位，可衍生出10种基本位置（位置一到位置十），覆盖从亲密对谈到激烈争吵的全部情感范围。

L形态：三位演员中，两位排成一组，第三位在侧翼。当一个单独的演员和两个人说话时，不论坐着或站着，都属于L形态。典型场景：一个面试者面对两位面试官。

A形态：三位演员中，一位被另两位从两侧夹击。当两位演员面对着第三位演员，且第三位被框在另两位之间时，属于A形态。典型场景：审讯室。

核心原则：

  1. I形态是最简单的建构单位，可以在A和L中出现
  2. 形态决定摄影机位置（基于动作轴线）
  3. 位置决定演员在画面中的站法
  4. 任何组合都可以减至I形态的10种位置之一

从双人到多人的扩展：

  • 双人对话 → I形态10种位置
  • 三人对话 → A/L形态 + I形态嵌套
  • 四人以上 → 将多人分组为可管理的子单元，每组视为I/L/A中的一个元素

A1 — 书中的应用 (Past Application)

案例1：A形态三人对话的过肩镜头策略（Ch.10）

  • 问题: 三人对话场景中，使用单人镜头会分割空间，观众无法同时看到说话者和倾听者
  • 方法论的使用: 使用A形态的过肩镜头来统一空间。在交代镜头之后，整场对话用过肩镜头处理，偶尔使用三人镜头或双人镜头变化节奏
  • 结论: 过肩镜头构图方式与双人对话场景的调度相同，I形态的各种过肩镜头变化全部适用
  • 结果: 空间统一性保持，观众能同时看到所有相关演员的反应

案例2：L形态的"故意保留全貌"策略（Ch.10）

  • 问题: 如何在三人对话开场时创造叙事张力
  • 方法论的使用: 以双人镜头开场（L形态的两人组），不到第三个画面不展示场景全貌（完整的三人L形态）
  • 结论: 故意保留场景全貌是一种有趣的开场策略，能创造好奇心和叙事动力
  • 结果: 观众在获得完整空间信息前已被吸引

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个skill?

  1. 用户有对话场景不知道怎么设计镜头 — "这段对话戏怎么拍？"
  2. 用户想增加对话场景的视觉变化 — "对话戏总是正反拍太单调了"
  3. 用户在设计多人对话场景 — "四个人吵架怎么安排摄影机？"

语言信号

  • "对话场景怎么拍"、"对话调度"
  • "两人/三人/多人对话"
  • "正反拍太单调"、"想增加视觉变化"
  • "怎么安排演员位置"、"摄影机放哪里"
  • "staging"、"blocking"、"场面调度"

E — 可执行步骤 (Execution)

步骤1：确定对话的形态

  • 分析对话中的人物关系：是两人面对面？三人中一人面对两人？还是三人互相对峙？
  • 选择基本形态：I（双人）、L（三人-侧翼）、A（三人-夹击）
  • 完成标准：能用一个字母（I/L/A）概括场景的基本几何关系

步骤2：确定位置和摄影机摆放

  • 根据选择的形态，确定演员的具体站位（参考10种基本位置）
  • 建立动作轴线，将摄影机放在轴线的同一侧
  • 决定主镜头（交代镜头）的角度和景别
  • 完成标准：能画出包含演员位置和摄影机位置的平面图

步骤3：设计覆盖镜头（coverage）

  • 用过肩镜头统一空间，替代单人特写

  • 为关键戏剧时刻添加特写或双人镜头

  • 用三人镜头或全景作为节奏变化

  • 完成标准：每个说话者和倾听者都能在镜头中被同时看到（除非刻意分割空间）

    • 🔴 判停条件: 若过肩镜头让观众分不清该看谁，或画面中人物关系不清晰——回到主机位确认视线方向和画面平衡，调整前景人物的遮挡比例（通常1/3到1/4画面）

B — 边界 (Boundary) ★

不要在以下情况使用此skill

  • 场景主要是动作而非对话（使用运动镜头调度系统）
  • 对话场景中演员数量超过8人（需要更复杂的分组策略）
  • 用户在设计非写实风格的对话（如戏剧化直视镜头的布莱希特式手法）

失败模式

  • 形态僵化: 严格套用I/L/A形态而忽略了场景的自然流动性。形态是起点不是终点。
  • 过肩镜头滥用: 所有对话都用过肩镜头处理，失去了场景的多样性。有时单人特写的分割空间恰恰是戏剧所需要的。
  • 忽略视线关系: 只关注几何形态而忽略了演员视线的方向和力量。"眼睛被清楚呈现的演员，将主宰该镜头。"

作者盲点

  • 系统假设所有对话场景都遵循好莱坞连续性剪辑风格
  • 对非正面对话（如背对背说话、隔墙对话）的覆盖不足
  • 10种位置的照片示例都是静态的，无法传达实际剪辑后的节奏感

反模式与常见错误

  • 过肩镜头万能论：所有对话场景都用过肩镜头处理，失去场景多样性——有时单人特写的分割空间恰恰是戏剧所需要的
  • 忽略视线权力关系："眼睛被清楚呈现的演员将主宰该镜头"，只关注几何形态而忽略演员视线方向会丢失叙事控制力
  • 形态僵化：严格套用I/L/A形态而忽略场景的自然流动性，形态是起点不是终点，不要为了符合形态而扭曲表演

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 Shot Design Dialogue Staging AI skill do?

用户提到对话场景、对话怎么拍、两人/三人/多人对话、调度、staging

Why use Shot Design Dialogue Staging on TypingMind?

Because you install it once and use it with any model. Shot Design Dialogue Staging 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 Shot Design Dialogue Staging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/geegl/directorskills/tree/main/output/books/shot-design/shot-design-dialogue-staging. 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 Shot Design Dialogue Staging?

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 Shot Design Dialogue Staging?

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

Is the Shot Design Dialogue Staging 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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