Anything2explainer — Development skill for Claude Code
Topic in, narrated explainer video out.
How to install Anything2explainer
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open Vincentwei1021/anything2explainer and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Anything2explainer does
Topic in, narrated explainer video out. A Claude Code / Codex skill that turns any topic into a black-canvas motion-graphics explainer video with TTS voiceover, subtitles and a chapter progress bar. Chinese or English; every frame drawn in code with Remotion.
Alternatives in Development
- Add Voiceover — Generate a voiceover narration and add it to your Remotion project 113 ★
- Vibetube — Desktop multicam recorder for macOS: records your screen and webcam in sync, then Claude Code or Codex edits t 31 ★
- Paper Share Skills — 📦 论文分享技能包:PDF 论文 → SUSTech Beamer 幻灯片 → 配音讲解视频 → B 站投稿(Claude Code / Codex / OMP 三端通用) Paper-to-Bilibili skil 28 ★
README
anything2explainer
[](https://claude.com/claude-code) [](https://openai.com/codex) [](https://remotion.dev) [](LICENSE)
**English** | [简体中文](README_ZH.md)
**Topic in, narrated explainer video out.** anything2explainer is a [Claude Code](https://claude.com/claude-code) / [Codex](https://openai.com/codex) skill that turns any topic into a black-canvas motion-graphics explainer video with TTS voiceover, subtitles and a chapter progress bar, in Chinese or English. Every frame is drawn in code with [Remotion](https://remotion.dev) (React + TypeScript). No stock footage, no generative video model, no frames lifted from anyone else's work.
It is not a CLI. What ships here is the whole method an AI coding agent needs to finish the film: a compilable Remotion template, a primitives and lighting library, tooling for voiceover / storyboard / rendering / quantitative QC, written style and motion specs, a multi-agent division-of-labour protocol, and one complete reference film as the quality bar.
**English cut** — *RAG & Knowledge Bases*, 5′02″, 44 lines / 785 words, voiced by kokoro-82m `am_liam` at natural speed:
https://github.com/user-attachments/assets/e2771c68-a28c-4459-ac5a-a5b685181eeb
**Chinese cut** — *RAG 与知识库* v2, 4′54″, 44 lines / 1490 characters, dot-field backdrop (`bg: 'dots'`), voiced through the bring-your-own-TTS path (Volcengine TTS 2.0 + forced alignment):
https://github.com/user-attachments/assets/5c213990-cbba-439e-8371-fbb3aa348e05
Both cuts share one storyboard and 44 shots; the English cut re-times every shot to the English voiceover. The full paper trail of the original Chinese cut (4′35″, star-field backdrop, 8 build agents in parallel for
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