affaan-m/ecc

manim-video

Build reusable Manim explainers for technical concepts, graphs, system diagrams, and product walkthroughs, then hand off to the wider ECC video stack if needed. Use when the user wants a clean animated explainer rather than a generic talking-head script.

All-time #2124 Trending #2470 First seen May 19, 2026
8-week activity · all time api

Installation

$ npx skills add affaan-m/ecc --skill manim-video

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More details

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Repository health

Stars 254.3K
License LICENSE
Default branch main
Open issues 54
Status Active

Skill metadata

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origin
ECC

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,906 B
  • docs SUMMARY.md 270 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 7,244 installs

SKILL.md

Manim Video

Use Manim for technical explainers where motion, structure, and clarity matter more than photorealism.

When to Activate

  • the user wants a technical explainer animation
  • the concept is a graph, workflow, architecture, metric progression, or system diagram
  • the user wants a short product or launch explainer for X or a landing page
  • the visual should feel precise instead of generically cinematic

Tool Requirements

  • manim CLI for scene rendering
  • ffmpeg for post-processing if needed
  • video-editing for final assembly or polish
  • remotion-video-creation when the final package needs composited UI, captions, or additional motion layers

Default Output

  • short 16:9 MP4
  • one thumbnail or poster frame
  • storyboard plus scene plan

Workflow

  1. Define the core visual thesis in one sentence.
  2. Break the concept into 3 to 6 scenes.
  3. Decide what each scene proves.
  4. Write the scene outline before writing Manim code.
  5. Render the smallest working version first.
  6. Tighten typography, spacing, color, and pacing after the render works.
  7. Hand off to the wider video stack only if it adds value.

Scene Planning Rules

  • each scene should prove one thing
  • avoid overstuffed diagrams
  • prefer progressive reveal over full-screen clutter
  • use motion to explain state change, not just to keep the screen busy
  • title cards should be short and loaded with meaning

Network Graph Default

For social-graph and network-optimization explainers:

  • show the current graph before showing the optimized graph
  • distinguish low-signal follow clutter from high-signal bridges
  • highlight warm-path nodes and target clusters
  • if useful, add a final scene showing the self-improvement lineage that informed the skill

Render Conventions

  • default to 16:9 landscape unless the user asks for vertical
  • start with a low-quality smoke test render
  • only push to higher quality after composition and timing are stable
  • export one clean thumbnail frame that reads at social size

Reusable Starter

Use [assets/networkgraphscene.py](assets/networkgraphscene.py) as a starting point for network-graph explainers.

Example smoke test:

manim -ql assets/network_graph_scene.py NetworkGraphExplainer

Output Format

Return:

  • core visual thesis
  • storyboard
  • scene outline
  • render plan
  • any follow-on polish recommendations

Related Skills

  • video-editing for final polish
  • remotion-video-creation for motion-heavy post-processing or compositing
  • content-engine when the animation is part of a broader launch