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Editorial Collage Motion

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Pluviobyte
editorial-collage-motion

将参考图或简要描述解码为可编辑的半色调纸张拼贴规范,默认使用 Codex 内置 image_gen 生成品牌一致的静帧和透明图层,再用本地 FFmpeg 或 HyperFrames 制作“从空背景逐件组装”的确定性动态视频。用户提到半色调拼贴、纸张拼贴、剪纸拼贴、编辑式拼贴、杂志拼贴、复古印刷拼贴、拼贴动效、拼贴动画、剪纸动画、纸片组装、逐层组装、从无到有、元素飞入拼装、定格拼贴、定格动画、Arcads 风格、参考图拆解、风格拆解、反向拆解视觉、照这个风格做、做类似的、生成拼贴静帧、让这张图动起来、让这些元素组装起来、制作拼贴广告或拼贴解释视频时使用。英文触发语义包括 editorial collage、halftone collage、paper collage、paper-cut motion、stop-motion graphic、assemble from empty、build-on motion、analyze this、break this down、reverse-engineer this look、generate the stills、animate this、make these move。默认不调用 Arcads、Nano Banana、Seedance 或 Kling;只有用户明确要求且对应连接器可用时才进入外部生成路径。

Overview

PublisherPluviobyte
Repositoryrnskill
Skill nameeditorial-collage-motion
Stars
1.6K
Forks
181
Bundled files
10
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.

  • 10 bundled files

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

  • Open source

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

Installation

Install the Editorial Collage Motion 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.
  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/Pluviobyte/rnskill.git /tmp/rnskill
mkdir -p .claude/skills
cp -r /tmp/rnskill/skills/editorial-collage-motion .claude/skills/editorial-collage-motion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Editorial Collage Motion 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 Editorial Collage Motion 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 Editorial Collage Motion 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.

半色调拼贴动效

把创作分成两段:先将视觉解码为可编辑规范,再从获批静帧或透明图层构建动画。默认使用本地兼容工作流,真实记录每个生成器和渲染器。

选择交付范围

先判断用户要哪一层:

  1. 仅分析:交付拆解、通用提示词和 JSON 视觉规范。
  2. 仅静帧:完成分析并生成、筛选静帧。
  3. 拼贴动效:完成静帧审批后制作无声动画底片。
  4. 完整视频:把本 Skill 作为视觉阶段,继续服从视频生产契约、字幕、配音、数字人和归档规则。

缺参考图但用户明确要求“照这张图分析”时,先索取图片。只有简述时,直接草拟规范,不重复询问已知信息。

选择执行路径

默认采用本地路径:

  • 静帧或图层:加载 imagegen Skill,使用 Codex 内置 image_gen。不得默认切换到 OpenAI API、CLI 或其他生图模型。
  • 简单逐层组装:使用 scripts/render_assembly.py
  • 复杂排版、多个转场或组件级时间轴:加载 hyperframes Skill,沿用本规范和来源声明。

只有用户明确要求 Arcads、Nano Banana、Seedance 或 Kling,并且对应工具在当前会话可调用时,才读取 references/provider-boundaries.md 并进入外部路径。上传本地品牌图、产品图或人物图前,必须说明上传位置、费用和用途并取得用户确认。

不得根据提示词、文件名或预期模型推断实际提供方。未实际调用的模型只能写成“目标提示词”或“兼容风格”,不能写成输出来源。

默认生产链路(硬默认)

严格按以下顺序执行:

  1. 解码参考图或简述,生成拆解、通用提示词和 JSON 视觉规范。
  2. 使用 Codex 内置 image_gen 为每幕单独生成完整静帧。品牌图、产品图或人物参考要在所有相关调用中保持可见。
  3. 把生成结果从 Codex 默认生成目录复制到工程 assets/stills/,不得让工程长期引用 $CODEX_HOME/generated_images/ 下的文件。
  4. 向用户展示完整静帧。用户未明确确认静帧前,禁止生成动画、FFmpeg 组装计划或正式视频。
  5. 静帧确认后,使用 Codex 内置 image_gen 生成各独立剪纸元素。需要透明 PNG 时,先生成纯色 chroma-key 背景,再调用 imagegen Skill 指定的 remove_chroma_key.py 本地抠像,并通过 alpha 预检。
  6. 使用获批静帧锁定最终构图,用透明图层建立 assembly-plan.json,再用本地 FFmpeg 或 HyperFrames 从空背景逐件组装。
  7. 完成媒体探针、关键帧检查和来源 manifest。默认记录 actual_still_provider: codex-image-genactual_motion_provider: local-ffmpeghyperframesexternal_uploads: false

如果用户直接提供全部静帧或透明图层,把 actual_still_provider 改为 user-supplied。只有真实发生外部调用时才能填写 Arcads、Nano Banana、Seedance 或 Kling。

阶段 A:解码参考

首次解码时完整阅读 references/visual-contract.mdreferences/schemas.md。按以下顺序输出:

  1. ### 拆解:媒介与工艺、色场、元素与切边、构图与层级、单幕创意、文字、安全区、情绪。
  2. ### 通用提示词:写成不依赖“上图”的自包含自然语言提示词。
  3. ### JSON 规范:从 assets/templates/collage-spec.json 复制并填写,保持有效 JSON。

把观察写成可复现参数。例如写“黑白圆点半色调,约 65 lpi,白色细描边,右下 6px 柔和阴影”,不要只写“有纸感”。

多张参考图要分别解码,再补一段共同风格摘要。用户要求“保持外观,只改颜色”时,只改相应字段,但重新输出完整 JSON。

阶段 B:规划场景

每幕只保留一个核心创意。为每幕锁定:

  • 背景色和画幅。
  • 主要元素、辅助元素、层级和最终坐标。
  • 文字内容、排版和可编辑方式。
  • 从空背景到完整构图的进入顺序。
  • 真人、数字人、字幕、Logo 和平台 UI 的避让区。

assets/templates/assembly-plan.json 建立组装计划。正式成片优先使用 layered 模式,每个元素提供一张带透明通道的 PNG。bands 模式只是将整张静帧切成条带滑入,只能用于快速预览或用户明确接受的简化版本。

阶段 C:生成与审批静帧

加载 imagegen Skill,使用 Codex 内置 image_gen 先生成或组合完整静帧,再展示给用户审批。保持品牌或产品参考在所有相关生成调用中可见。

本地正式模式按以下顺序工作:

  1. 每幕发起一次独立的内置 image_gen 调用,生成完整构图静帧;不同场景不要用一次调用拼成大图。
  2. 把选中的静帧复制到工程 assets/stills/,记录最终提示词和参考图角色。
  3. 展示静帧并获得用户明确确认。未确认时只允许调整提示词和重新生成。
  4. 确认后再生成独立拼贴元素。按 imagegen 的 chroma-key 加本地抠像路径取得透明 PNG,保留白色 keyline 和柔和阴影。
  5. 用获批静帧校准图层的大小、坐标和层级。文字默认保留为 HyperFrames、HTML 或 Remotion 的可编辑文本层。
  6. 导出场景静帧和图层清单,再进入动画阶段。

内置 image_gen 不可用或失败时,不得自动改用 CLI。先告知用户 CLI/API 路径需要 OPENAI_API_KEY,只在用户明确同意后切换。

如果只拿到一张完整静帧,可以先用 bands 模式做低成本运动预览,但不得把矩形条带滑入描述成真正的“逐元素组装”。

阶段 D:本地逐层组装

先验证规范和计划:

bash
python3 .claude/skills/editorial-collage-motion/scripts/validate_collage.py \
  --spec /absolute/path/collage-spec.json \
  --plan /absolute/path/assembly-plan.json \
  --project /absolute/path/project

再渲染无声底片:

bash
python3 .claude/skills/editorial-collage-motion/scripts/render_assembly.py \
  --project /absolute/path/project \
  --plan /absolute/path/assembly-plan.json \
  --output /absolute/path/project/renders/collage-assembly.mp4

动画必须从纯色空场开始,元素按计划从画面边缘进入并落位。禁止用镜头晃动、整图漂移或持续缩放冒充组装。落位后留足可读时间。

阶段 E:质检和来源声明

完整阅读 references/qc-and-provenance.md,至少完成:

  • 媒体探针:尺寸、比例、帧率、时长、编码和可解码性。
  • 首帧、每幕落位前后、幕中点和末帧抽查。
  • 空场起步、逐件进入、阴影稳定、文字可读、安全区和画面密度检查。
  • render-manifest.json 与实际输出、输入计划和生成器一致。

在制作说明中明确写出:

  • actual_still_provider
  • actual_motion_provider
  • external_uploads
  • 是否属于 compatible_render,以及兼容的是哪套视觉规范

当前会话没调用 Arcads MCP 时,固定使用“Arcads 风格兼容渲染”或“editorial collage 本地渲染”,不得写成 Nano Banana 或 Seedance 原生输出。

资源

  • references/visual-contract.md:风格词汇、硬性视觉合同和反例。
  • references/schemas.md:视觉规范与组装计划字段说明。
  • references/provider-boundaries.md:本地和外部生成路径的权限与披露边界。
  • references/qc-and-provenance.md:交付质检和来源记录。
  • assets/templates/collage-spec.json:可复制的视觉规范模板。
  • assets/templates/assembly-plan.json:可复制的本地组装计划模板。
  • assets/templates/assembly-plan-bands.json:只有完整静帧时使用的条带预览模板。
  • scripts/validate_collage.py:规范、计划和素材预检。
  • scripts/render_assembly.py:FFmpeg 确定性逐层或条带组装器。

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 Editorial Collage Motion AI skill do?

将参考图或简要描述解码为可编辑的半色调纸张拼贴规范,默认使用 Codex 内置 image_gen 生成品牌一致的静帧和透明图层,再用本地 FFmpeg 或 HyperFrames 制作“从空背景逐件组装”的确定性动态视频。用户提到半色调拼贴、纸张拼贴、剪纸拼贴、编辑式拼贴、杂志拼贴、复古印刷拼贴、拼贴动效、拼贴动画、剪纸动画、纸片组装、逐层组装、从无到有、元素飞入拼装、定格拼贴、定格动画、Arcads 风格、参考图拆解、风格拆解、反向拆解视觉、照这个风格做、做类似的、生成拼贴静帧、让这张图动起来、让这些元素组装起来、制作拼贴广告或拼贴解释视频时使用。英文触发语义包括 editorial collage、halftone collage、paper collage、paper-cut motion、stop-motion graphic、assemble from empty、build-on motion、analyze this、break this down、reverse-engineer this look、generate the stills、animate this、make these move。默认不调用 Arcads、Nano Banana、Seedance 或 Kling;只有用户明确要求且对应连接器可用时才进入外部生成路径。

Why use Editorial Collage Motion on TypingMind?

Because you install it once and use it with any model. Editorial Collage Motion 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 Editorial Collage Motion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Pluviobyte/rnskill/tree/main/skills/editorial-collage-motion. 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 Editorial Collage Motion?

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 Editorial Collage Motion?

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

Is the Editorial Collage Motion AI skill free?

It is published on GitHub by Pluviobyte. Check the repository for licensing terms. 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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