A powerful skill for generating mathematical animations with integrated text-to-speech narration and synchronized subtitles.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install manim-animation-en
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install manim-animation-en using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Manim Animation?
The Manim Animation skill empowers developers and educators to transform mathematical concepts into high-fidelity animated videos. By leveraging the Manim Community library alongside the manim-voiceover plugin, this Openclaw Skills integration automates the complex process of syncing visual movements with audio narration.
It provides a complete local pipeline for video production, allowing users to generate code, render animations, and burn subtitles without relying on expensive external APIs. Whether you are building educational content or technical demonstrations, this skill ensures precise timing between what is seen and what is heard through a robust context-manager workflow.
Manim Animation Use Cases
- Creating educational YouTube videos or course materials explaining complex mathematical theories.
- Generating animated technical documentation or algorithm visualizations for developer advocacy.
- Developing social media content that requires high-quality geometric or algebraic motion graphics.
- Rapid prototyping of narrated presentations where voice-animation synchronization is critical.
How Manim Animation Works
- Requirement Analysis: The agent interprets the user's mathematical or educational prompt to design a visual scene.
- Code Generation: A Python script is generated using the Manim library, incorporating the VoiceoverScene class for narration support.
- TTS Synthesis: The skill utilizes gTTS (Google Text-to-Speech) or pyttsx3 to generate audio files and calculate precise durations for each speech segment.
- Animation Sync: Using the voiceover context manager, the skill aligns the run_time of animations to match the generated speech duration exactly.
- Rendering & Post-processing: The Manim engine renders the video, while FFmpeg is optionally used to burn in SRT subtitles and adjust playback speed.
Manim Animation Setup
To get started with this skill, ensure you have Python 3.9+ and FFmpeg installed. Follow these steps to prepare your environment for Openclaw Skills development:
# Install core animation and voiceover packages
pip install manim "manim-voiceover[gtts]"
# macOS users: Install FFmpeg via Homebrew for full codec support
brew install ffmpeg
# Linux users: Ensure necessary libraries are present
sudo apt install ffmpeg libx264-dev libass-dev
# Verify your environment
python3 scripts/check_environment.py
Manim Animation Data Schema & Taxonomy
The skill manages a structured output directory to keep animation assets organized:
| Directory/File | Purpose |
|---|---|
scene_file.py |
The generated Python source code for the Manim animation. |
manim.cfg |
Configuration file defining render quality (low, medium, high) and codecs. |
media/videos/ |
Root directory for all rendered MP4 video outputs. |
media/voiceover/ |
Cached audio files generated by the TTS engine. |
.srt files |
Automatically generated subtitle files for synchronization. |
Manim Animation Advanced Features
- One-Click Pipeline: Use
run_pipeline.pyto handle rendering, subtitle burning, and speed adjustments in a single command. - Dynamic Subtitle Scaling: Built-in logic to prevent subtitle text from overflowing screen boundaries using scale_to_fit_width.
- Multi-Engine TTS Support: Seamlessly switch between gTTS for high-quality online synthesis and pyttsx3 for fully offline workflows.
- Customizable Playback Speed: Automatically adjust final video tempo (default 1.35x) while maintaining pitch-perfect audio via FFmpeg filters.
SKILL.md
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