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Dialogue Task Overload

Community
geegl
dialogue-task-overload

任务过载、本能表演、演员反对、洗碗/泡咖啡/摆道具

Overview

Publishergeegl
Repositorydirectorskills
Skill namedialogue-task-overload
Stars
68
Forks
7
Bundled files
1
LicenseMIT
Links
  • 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 Dialogue Task Overload 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/master-shots-v2/dialogue-task-overload
  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/master-shots-v2/dialogue-task-overload .claude/skills/dialogue-task-overload
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dialogue Task Overload 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 Dialogue Task Overload 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 Dialogue Task Overload 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.

R — 原文 (Reading)

当你给演员安排越多的任务时,他们的表现反而往往越出色……要解决这一问题,最好的方法就是给演员增加更多的任务,直到他们的脑子转不过来为止。那他们就只能凭本能去表演了。 — master-shots-v2, p.g_0060

——《大师镜头 第二卷》结语

I — 方法论骨架 (Interpretation)

演员反对意见的真实原因不是"不符合角色",而是心慌——同时处理太多任务让他们焦虑。多数导演会在此刻退让、减少要求,但这恰恰是错误的。当演员说"这个走位不对"但说不出具体原因时,说明你已经接近突破点。

正确做法:和颜悦色地继续增加更多任务——走位+手部动作+道具互动+头部角度+视线方向——直到演员的意识没有余力自我怀疑,只能凭本能表演。本能表演比精心设计的表演更真实生动。

任务组合示例:洗碗(手部任务)+转身面向摄影机(走位任务)+不看对方眼睛(视线任务)+说台词(语言任务)。当演员同时处理这四件事时,他们没有精力"表演",只能"存在"——这正是好表演的本质。

演员反对时不要安慰或退让,也不要强硬命令。告诉他们"只有这么拍才能展现你的表演功力",用结果说服而非用权威压制。

A1 — Book Cases

案例1:结语——导演的秘密:给演员越多任务表现越好,直到脑子转不过来只能凭本能表演。演员反对的真实原因是心慌,而非"不符合角色"。和颜悦色地增加要求,不要退让。

案例2:《决不妥协》(ch6.9)——查理兹·塞隆在洗碗场景中接收重要信息。洗碗这个手头任务给了她走到背景去的理由(收盘子),同时也让她有事可做而非僵硬地站着。任务本身推动了叙事。

案例3:全书多个场景(ch3.5/4.5/11.3/11.4)——"给演员找事干"贯穿全书:洗碗、泡咖啡、弹钢琴、吃东西、摆弄道具。每个任务都让演员有理由转身、低头、看向别处,表演因此更自然。

案例4:ch9.3"头靠头"——新手让演员一直盯着对方说是常见错误。现实生活中熟人之间几乎不看对方眼睛。让演员有事可看(道具、环境)比强制对视更真实。

A2 — Future Triggers

触发场景:

  • 演员表演生硬、不自然
  • 演员反复说"这个走位不对"但说不清原因
  • 对话场景缺乏活力,角色像在"背台词"
  • 需要让两个不太熟的演员快速建立化学反应

语言信号:

  • "演员表演不自然/太僵硬"
  • "演员说走位不对"
  • "对话场景太平淡"
  • "需要让表演更真实"
  • "演员一直在想怎么演"
  • "需要给演员找点事做"

E — Execution

步骤1:设计任务组合 为每个演员设计至少3个同时进行的任务:(1)手部任务——洗碗、泡咖啡、摆弄道具、做手工;(2)走位任务——转身、走向某处、坐下/站起;(3)视线任务——不看对方眼睛、看向窗外、低头看手。任务必须有合理性(符合角色身份和场景逻辑)。

步骤2:逐步叠加而非一次性给完 先给一个任务让演员适应,再叠加第二个,最后加第三个。每次叠加时观察演员反应——如果他们开始抱怨"太难了",说明你正在接近突破点。此时不要退让,和颜悦色地继续。

步骤3:拍摄并观察 当演员同时处理多个任务时,他们的注意力被分散,自我意识降低,表演会从"设计"转向"本能"。观察演员在任务过载状态下的即兴反应——这些反应往往比精心排练的版本更真实。保留这些瞬间。

完成标准: 每个演员至少有3个同时进行的任务;任务组合有场景合理性;演员在任务过载状态下表演更自然。

B — Boundaries

边界:

  • 任务不能多到影响台词表达——如果演员连台词都记不住就是过多了
  • 任务必须有合理性——不能为了增加任务而让角色做不合理的事
  • 不适合需要高度控制的精确走位场景(如舞蹈编排)

反例:

  • 让演员同时洗碗、弹钢琴、打电话——任务之间冲突
  • 演员明显慌乱但导演仍不停增加要求——这是虐待而非技巧
  • 任务设计与角色身份不符(如让一个不食人间烟火的角色做家务)

作者盲点: Kenworthy 的"任务过载"理论主要基于他个人的导演经验,缺乏表演理论的系统支撑(如斯坦尼斯拉夫斯基的"任务-动作"理论或迈斯纳技巧中的"重复练习")。他将演员的反对一律解读为"心慌",忽略了合理反对的可能——有时候演员说"不对"确实是因为走位有问题。此外,他未讨论不同类型演员(方法派vs技术派vs非专业演员)对任务过载的承受差异——非专业演员可能在第一个任务时就已过载。

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 Dialogue Task Overload AI skill do?

任务过载、本能表演、演员反对、洗碗/泡咖啡/摆道具

Why use Dialogue Task Overload on TypingMind?

Because you install it once and use it with any model. Dialogue Task Overload 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 Dialogue Task Overload in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/geegl/directorskills/tree/main/output/books/master-shots-v2/dialogue-task-overload. 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 Dialogue Task Overload?

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 Dialogue Task Overload?

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

Is the Dialogue Task Overload 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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