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Story To Handdrawn Video

CommunityPopular
gnipbao
story-to-handdrawn-video

Convert Chinese story copy or ordered local images into a silent hand-drawn Remotion story video. Supports a locked user-approved colored-pencil diary default plus a built-in 20-style library covering doodle, crayon, line explainer, ink, watercolor, gouache, storybook, zine, whiteboard, and printmaking looks. Use when the user asks to generate, import, restyle, preview, or render a hand-drawn story video, asks for the bundled diary-comic look, or wants to choose and compare hand-drawn visual styles.

Overview

Publishergnipbao
Repositorystory-to-handdrawn-video
Skill namestory-to-handdrawn-video
Stars
2K
Forks
277
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Story To Handdrawn Video 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/gnipbao/story-to-handdrawn-video.git /tmp/story-to-handdrawn-video
mkdir -p .claude/skills
cp -r /tmp/story-to-handdrawn-video/skill-package/story-to-handdrawn-video .claude/skills/story-to-handdrawn-video
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Story To Handdrawn Video 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 Story To Handdrawn Video 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 Story To Handdrawn Video 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.

Story to Hand-drawn Video

Use the project renderer through this Skill's scripts/run_story_video.py. Set STORY_VIDEO_PROJECT when the project is not the current working directory. The wrapper must not rely on an author-specific absolute path.

Workflow

  1. Accept inline Chinese story text, a UTF-8 text file, or ordered local images.
  2. Preserve the user's wording. For text input, keep one complete sentence as one beat by default and split only long compound sentences at natural narrative turns.
  3. For uploaded composite pages, automatically crop the handwritten caption and illustration, then derive an aligned black-and-white plate locally.
  4. In direct-cut mode, keep the order text → bw_full → color; reveal every stage from left to right.
  5. In page-flip mode, preserve the untouched uploaded master and show it statically before curling the page from the bottom-right corner. Do not add caption, black-and-white, or recoloring stages. Retain a faded version of the source page on the paper underside.
  6. Keep all illustration marks inside the white safe border. Use contained framing and never cover cropping.
  7. Produce a silent MP4. Voiceover and optional BGM are post-production tasks.
  8. Report the scene count, duration, output path, and whether the result is plan-only, preview, or final.

Default visual lock

The immutable default style id is colored-pencil-diary. When the user does not request another style, preserve these fixed project resources:

  • references/target-diary-style.txt: prompt-ready visual grammar.
  • references/style-bw.png: black-and-white mark-making board.
  • references/style-color.png: colored-pencil technique and palette board.
  • references/style-layout.png: full-page caption and composition board.
  • references/style-approved.png: user-approved final-output anchor and default quality bar.

Treat the boards as style evidence only. Ignore their depicted people, actions, props, dates, and Chinese wording. Let the character sheet control identity and continuity. When visual instructions conflict or remain ambiguous, follow style-approved.png for line weight, pencil density, figure scale, facial simplicity, negative space, and final finish.

Match these non-negotiable traits: pure white digital page; blunt wobbly black felt-tip contours; oversized rounded heads and short compact bodies; simple expressive faces; visible short colored-pencil strokes with white gaps; a small dusty-blue, brick-red, charcoal, beige, tan, muted-yellow, and light-gray palette; sparse contextual props and abundant unfilled white space. Avoid anime, vector polish, smooth fills, watercolor, gradients, realistic lighting, paper grain, and dense scenery.

Do not replace or bypass the fixed default resources unless the user explicitly requests a different visual family. The renderer fingerprints the selected recipe and its reference images, so switching styles automatically creates a new generated-asset batch instead of reusing stale images.

Built-in style library

The machine-readable source of truth is <project>/references/handdrawn-style-library.json. Use python3 scripts/run_story_video.py --list-styles to show the current menu. --style accepts the order number, id, Chinese name, English name, or any registered alias. Use the catalog-level contact_sheet and each style's example_image to compare visual families before selection; treat those images as style evidence, not scene or character references.

#Style id中文名Best fit
1colored-pencil-diary彩铅日记漫画(默认)家庭、生活、纪实情感
2minimal-line-explainer极简黑白线条讲解科普、流程、观点
3kid-crayon五岁儿童蜡笔坏画童年、亲子、轻喜剧
4rawkid-crayon潦草家庭投稿蜡笔家庭连载、温暖日常
5bean-doodle-infographic小豆人涂鸦信息图步骤、清单、知识卡
6ms-paint-bad-doodle鼠标烂涂鸦吐槽、反转、荒诞
7ballpoint-scribble圆珠笔缠绕线速写肖像、动物、独白
8real-crayon-paper真实蜡笔纸实拍儿童视角、成长记录
9ink-wash水墨写意文化、寓言、感悟
10emotional-watercolor-sketch情绪叙事淡彩速写回忆、关系、克制纪实
11retro-gouache-concept中古动画水粉概念稿怀旧、城市、温暖剧情
12sunlit-storybook暖光童画绘本治愈、童话、亲情
13nordic-gouache-storybook北欧低饱和水粉绘本安静日常、自然、睡前故事
14inked-storybook墨线淡彩绘本角色、青春、对白
15warm-flat-storybook暖色几何扁平绘本关系、品牌、轻科普
16naive-marker-notes稚拙马克笔笔记社媒、观点、年轻化内容
17zine-riso-collageZine 孔版拼贴成长、旅行、音乐文化
18organic-contour-doodle有机轮廓品牌涂鸦生活方式、餐饮、品牌故事
19whiteboard-explainer白板讲解动画教程、商业解释、时间线
20linocut-editorial粗粝木刻社论插画社会议题、历史、寓言

When the user names a style, use it directly. When the user asks for options without naming one, recommend 3–5 styles based on story content instead of forcing a 20-item clarification. Never blend two recipes unless the user explicitly requests a hybrid. Keep character identity, safe framing, narrative isolation, and text accuracy independent of style.

Only the default style currently has fixed visual reference boards. Other styles are prompt-locked and must not inherit the default colored-pencil boards. Their recipe, caption handwriting, palette, negative constraints, source provenance, and aliases are all stored in the library. Repo-derived recipes retain MIT attribution in <project>/references/handdrawn-styles-LICENSE.txt.

Uploaded images

Preview:

bash
python3 scripts/run_story_video.py \
  --images /absolute/01.jpg /absolute/02.jpg \
  --title "故事标题" \
  --mode preview \
  --transition cut

Final direct-cut render:

bash
python3 scripts/run_story_video.py \
  --images /absolute/01.jpg /absolute/02.jpg \
  --title "故事标题" \
  --mode full \
  --transition cut \
  --page-duration 4.4

Final page-flip render:

bash
python3 scripts/run_story_video.py \
  --images /absolute/01.jpg /absolute/02.jpg \
  --title "故事标题" \
  --mode full \
  --transition page-flip \
  --transition-sec 0.7

Use --layout auto|composite|full to control how uploaded pages are interpreted.

Story text

Plan without generating images:

bash
python3 scripts/run_story_video.py \
  --input /absolute/story.txt \
  --title "故事标题" \
  --style colored-pencil-diary \
  --mode plan

Use a different built-in style:

bash
python3 scripts/run_story_video.py \
  --input /absolute/story.txt \
  --title "故事标题" \
  --style ink-wash \
  --mode generate

Prepare Codex Image2 jobs, then import and render:

bash
python3 scripts/run_story_video.py --input /absolute/story.txt --title "故事标题" --mode generate
python3 scripts/run_story_video.py --mode import
python3 scripts/run_story_video.py --mode render

Use --generator codex by default. Use --generator api only when the user explicitly selects the API fallback and OPENAI_API_KEY is available. Use --force only when the user explicitly wants an existing generated batch replaced.

Default to --text-mode font so the user's Chinese wording remains exact. Use --text-mode image2 only when the user explicitly prioritizes source-like handwritten captions and accepts that generated Chinese glyphs may need correction.

For time jumps, ambiguous pronouns, medical scenes, or age-sensitive characters, provide a JSON visual plan keyed by two-digit scene id through --visual-plan.

Output contract

  • Text-story final: <project>/out/picture_silent.mp4
  • Text-story preview: <project>/out/picture_silent-preview.mp4
  • Uploaded-image final: <project>/out/uploaded_picture_silent.mp4
  • Uploaded-image preview: <project>/out/uploaded_picture_silent-preview.mp4
  • Resolution: final 1080×1440; preview 720×960
  • Codec/audio: H.264, silent

After changing the renderer or style library, run the deterministic style-list command and one plan-only smoke test. Do not spend image-generation credits solely for validation unless the user requests visual samples.

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 Story To Handdrawn Video AI skill do?

Convert Chinese story copy or ordered local images into a silent hand-drawn Remotion story video. Supports a locked user-approved colored-pencil diary default plus a built-in 20-style library covering doodle, crayon, line explainer, ink, watercolor, gouache, storybook, zine, whiteboard, and printmaking looks. Use when the user asks to generate, import, restyle, preview, or render a hand-drawn story video, asks for the bundled diary-comic look, or wants to choose and compare hand-drawn visual styles.

Why use Story To Handdrawn Video on TypingMind?

Because you install it once and use it with any model. Story To Handdrawn Video 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 Story To Handdrawn Video in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gnipbao/story-to-handdrawn-video/tree/main/skill-package/story-to-handdrawn-video. 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 Story To Handdrawn Video?

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 Story To Handdrawn Video?

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

Is the Story To Handdrawn Video AI skill free?

Yes. It is published on GitHub by gnipbao 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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