Agent skill · Code Review & Quality

manim-animation-maker

Create educational explainer videos with a Manim plus FFmpeg workflow. Use when the user asks for Manim animation, math/physics/geometry/algorithm visualization, formula derivation, concept explainer video, scene planning, MP4 rendering, preview frames, or video quality checks.

mingchen666157★ · +54/wk · 1 repos on radarProfile →
claude-code
Install
npx skills add mingchen666/Reviva --skill manim-animation-maker --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 12 KB
Bundled scripts: none
Path: electron/builtin-assets/skills/manim-animation-maker/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 181 · +24 this week
Language: HTML
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Manim Animation Maker Create short teaching videos with Manim Community Edition and FFmpeg. This skill is not a generic video generator. It is for learning scenarios where motion, sequencing, labels, formulas, diagrams, or visual emphasis make a concept easier to understand. The normal output is a Manim Python script plus a rendered MP4 or a clear render command when local dependencies are missi

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About this skill
What does the manim-animation-maker skill do?

Create educational explainer videos with a Manim plus FFmpeg workflow. Use when the user asks for Manim animation, math/physics/geometry/algorithm visualization, formula derivation, concept explainer video, scene planning, MP4 rendering, preview frames, or video quality checks.

How do I install it?

Run `npx skills add mingchen666/Reviva --skill manim-animation-maker --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From mingchen666/Reviva, a repository with 181 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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