Wechat 2d Render logo

Wechat 2d Render

OrganizationPopular
vibe-motion
wechat-2d-render

Clone or update https://github.com/sxhzju/wechat-2d and render the default WeChat-style 2D chat motion video with Remotion. Use when users ask for 微信聊天动画, wechat 2d chat render, 微信视频消息动效, or exporting the default demo from the wechat-2d project.

Overview

Publishervibe-motion
Repositoryskills
Skill namewechat-2d-render
Stars
1.2K
Forks
79
Bundled files
2
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 vibe-motion on GitHub. Read the source before you install it.

Installation

Install the Wechat 2d Render 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/vibe-motion/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/wechat-2d-render .claude/skills/wechat-2d-render
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wechat 2d Render 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 Wechat 2d Render 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 Wechat 2d Render 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.

WeChat 2D Render

Workflow

  1. Use scripts/render_wechat_2d.sh from this skill.
  2. Pass workspace_dir as the first argument when the user specifies a folder; otherwise use the current directory.
  3. Pass output_path as the second argument when the user specifies output; otherwise use out/wechat-2d-transparent.mov.
  4. Pass a props JSON path as the third argument when the user provides custom Remotion props; otherwise use shared/project/render-presets/default.json.
  5. Run the script and wait for completion.
  6. Return the final absolute output path printed by the script.

Command

bash
bash scripts/render_wechat_2d.sh [workspace_dir] [output_path] [props_file]

Installed Skill Resolution

Use the installed skill copy, not the source repo checkout:

bash
skill_dir=""
for base in "${AGENTS_HOME:-$HOME/.agents}" "${CLAUDE_HOME:-$HOME/.claude}" "${CODEX_HOME:-$HOME/.codex}"; do
  if [ -d "$base/skills/wechat-2d-render" ]; then
    skill_dir="$base/skills/wechat-2d-render"
    break
  fi
done
[ -n "$skill_dir" ] || { echo "wechat-2d-render skill not found under ~/.agents, ~/.claude, or ~/.codex"; exit 1; }

bash "$skill_dir/scripts/render_wechat_2d.sh" "$(pwd)" "$(pwd)/out/wechat-2d-transparent.mov"

Behavior

  • Reuse local repo if workspace_dir/wechat-2d exists; otherwise clone from GitHub.
  • Track remote default branch (origin/HEAD) when updating an existing repo.
  • Install dependencies with pnpm install; if pnpm is missing, enable it through corepack.
  • Run the project Remotion scripts:
    • pnpm run remotion:ensure-browser
    • REMOTION_OUTPUT=... REMOTION_PROPS_FILE=... pnpm run remotion:render
  • Default render target is the active composition from shared/project/projectConfig.js, currently the wechat-chat-motion plugin via ScaffoldDemo30fps.
  • Default output is ProRes 4444 with yuva444p10le pixel format and PNG image format, suitable for transparent-background workflows.

Project Notes

  • The project uses a scaffold/plugin split:
    • preview/* for local UI controls and browser preview.
    • remotion/* for Remotion entry wrappers.
    • shared/scaffold/* for common runtime.
    • shared/project/* for plugin and composition registry.
    • shared/features/demoMotion/* for the WeChat chat scene.
  • Animation state must be deterministic per frame. Remotion renders frames in parallel and out of order, so do not rely on timers, mutable cursors, previous renders, or render order.
  • Frame-specific data should be built from {frame, fps, loop, sceneContext, pluginParams} in buildSceneProps.
  • Keep videoWidth and videoHeight as layout props; use a props JSON file for custom sizes.

Requirements

  • git
  • node
  • corepack or pnpm
  • network access for clone/update and dependency install

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 Wechat 2d Render AI skill do?

Clone or update https://github.com/sxhzju/wechat-2d and render the default WeChat-style 2D chat motion video with Remotion. Use when users ask for 微信聊天动画, wechat 2d chat render, 微信视频消息动效, or exporting the default demo from the wechat-2d project.

Why use Wechat 2d Render on TypingMind?

Because you install it once and use it with any model. Wechat 2d Render 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 Wechat 2d Render in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vibe-motion/skills/tree/main/wechat-2d-render. 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 Wechat 2d Render?

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 Wechat 2d Render?

As many as you like. As long as a model supports skills, you can use Wechat 2d Render with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wechat 2d Render AI skill free?

It is published on GitHub by vibe-motion. 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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