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Video Editing

CommunityPopular
affaan-m
video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

Overview

Publisheraffaan-m
RepositoryECC
Skill namevideo-editing
Stars
270.2K
Forks
40.4K
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by affaan-m on GitHub. Read the source before you install it.

Installation

Install the Video Editing 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.
    https://github.com/affaan-m/ECC/tree/main/.agents/skills/video-editing
  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/affaan-m/ECC.git /tmp/ECC
mkdir -p .claude/skills
cp -r /tmp/ECC/.agents/skills/video-editing .claude/skills/video-editing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Video Editing 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 Video Editing 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 Video Editing 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.

Video Editing

AI-assisted editing for real footage. Not generation from prompts. Editing existing video fast.

When to Activate

  • User wants to edit, cut, or structure video footage
  • Turning long recordings into short-form content
  • Building vlogs, tutorials, or demo videos from raw capture
  • Adding overlays, subtitles, music, or voiceover to existing video
  • Reframing video for different platforms (YouTube, TikTok, Instagram)
  • User says "edit video", "cut this footage", "make a vlog", or "video workflow"

Core Thesis

AI video editing is useful when you stop asking it to create the whole video and start using it to compress, structure, and augment real footage. The value is not generation. The value is compression.

The Pipeline

Screen Studio / raw footage
  → Claude / Codex
  → FFmpeg
  → Remotion
  → ElevenLabs / fal.ai
  → Descript or CapCut

Each layer has a specific job. Do not skip layers. Do not try to make one tool do everything.

Layer 1: Capture (Screen Studio / Raw Footage)

Collect the source material:

  • Screen Studio: polished screen recordings for app demos, coding sessions, browser workflows
  • Raw camera footage: vlog footage, interviews, event recordings
  • Desktop capture via VideoDB: session recording with real-time context (see videodb skill)

Output: raw files ready for organization.

Layer 2: Organization (Claude / Codex)

Use Claude Code or Codex to:

  • Transcribe and label: generate transcript, identify topics and themes
  • Plan structure: decide what stays, what gets cut, what order works
  • Identify dead sections: find pauses, tangents, repeated takes
  • Generate edit decision list: timestamps for cuts, segments to keep
  • Scaffold FFmpeg and Remotion code: generate the commands and compositions
Example prompt:
"Here's the transcript of a 4-hour recording. Identify the 8 strongest segments
for a 24-minute vlog. Give me FFmpeg cut commands for each segment."

This layer is about structure, not final creative taste.

Layer 3: Deterministic Cuts (FFmpeg)

FFmpeg handles the boring but critical work: splitting, trimming, concatenating, and preprocessing.

Extract segment by timestamp

bash
ffmpeg -i raw.mp4 -ss 00:12:30 -to 00:15:45 -c copy segment_01.mp4

Batch cut from edit decision list

bash
#!/bin/bash
# cuts.txt: start,end,label
while IFS=, read -r start end label; do
  ffmpeg -i raw.mp4 -ss "$start" -to "$end" -c copy "segments/${label}.mp4"
done < cuts.txt

Concatenate segments

bash
# Create file list
for f in segments/*.mp4; do echo "file '$f'"; done > concat.txt
ffmpeg -f concat -safe 0 -i concat.txt -c copy assembled.mp4

Create proxy for faster editing

bash
ffmpeg -i raw.mp4 -vf "scale=960:-2" -c:v libx264 -preset ultrafast -crf 28 proxy.mp4

Extract audio for transcription

bash
ffmpeg -i raw.mp4 -vn -acodec pcm_s16le -ar 16000 audio.wav

Normalize audio levels

bash
ffmpeg -i segment.mp4 -af loudnorm=I=-16:TP=-1.5:LRA=11 -c:v copy normalized.mp4

Layer 4: Programmable Composition (Remotion)

Remotion turns editing problems into composable code. Use it for things that traditional editors make painful:

When to use Remotion

  • Overlays: text, images, branding, lower thirds
  • Data visualizations: charts, stats, animated numbers
  • Motion graphics: transitions, explainer animations
  • Composable scenes: reusable templates across videos
  • Product demos: annotated screenshots, UI highlights

Basic Remotion composition

tsx
import { AbsoluteFill, Sequence, Video, useCurrentFrame } from "remotion";

export const VlogComposition: React.FC = () => {
  const frame = useCurrentFrame();

  return (
    <AbsoluteFill>
      {/* Main footage */}
      <Sequence from={0} durationInFrames={300}>
        <Video src="/segments/intro.mp4" />
      </Sequence>

      {/* Title overlay */}
      <Sequence from={30} durationInFrames={90}>
        <AbsoluteFill style={{
          justifyContent: "center",
          alignItems: "center",
        }}>
          <h1 style={{
            fontSize: 72,
            color: "white",
            textShadow: "2px 2px 8px rgba(0,0,0,0.8)",
          }}>
            The AI Editing Stack
          </h1>
        </AbsoluteFill>
      </Sequence>

      {/* Next segment */}
      <Sequence from={300} durationInFrames={450}>
        <Video src="/segments/demo.mp4" />
      </Sequence>
    </AbsoluteFill>
  );
};

Render output

bash
npx remotion render src/index.ts VlogComposition output.mp4

See the Remotion docs for detailed patterns and API reference.

Layer 5: Generated Assets (ElevenLabs / fal.ai)

Generate only what you need. Do not generate the whole video.

Voiceover with ElevenLabs

python
import os
import requests

resp = requests.post(
    f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}",
    headers={
        "xi-api-key": os.environ["ELEVENLABS_API_KEY"],
        "Content-Type": "application/json"
    },
    json={
        "text": "Your narration text here",
        "model_id": "eleven_turbo_v2_5",
        "voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
    }
)
with open("voiceover.mp3", "wb") as f:
    f.write(resp.content)

Music and SFX with fal.ai

Use the fal-ai-media skill for:

  • Background music generation
  • Sound effects (ThinkSound model for video-to-audio)
  • Transition sounds

Generated visuals with fal.ai

Use for insert shots, thumbnails, or b-roll that doesn't exist:

generate(model_name: "fal-ai/nano-banana-pro", input: {
  "prompt": "professional thumbnail for tech vlog, dark background, code on screen",
  "image_size": "landscape_16_9"
})

VideoDB generative audio

If VideoDB is configured:

python
voiceover = coll.generate_voice(text="Narration here", voice="alloy")
music = coll.generate_music(prompt="lo-fi background for coding vlog", duration=120)
sfx = coll.generate_sound_effect(prompt="subtle whoosh transition")

Layer 6: Final Polish (Descript / CapCut)

The last layer is human. Use a traditional editor for:

  • Pacing: adjust cuts that feel too fast or slow
  • Captions: auto-generated, then manually cleaned
  • Color grading: basic correction and mood
  • Final audio mix: balance voice, music, and SFX levels
  • Export: platform-specific formats and quality settings

This is where taste lives. AI clears the repetitive work. You make the final calls.

Social Media Reframing

Different platforms need different aspect ratios:

PlatformAspect RatioResolution
YouTube16:91920x1080
TikTok / Reels9:161080x1920
Instagram Feed1:11080x1080
X / Twitter16:9 or 1:11280x720 or 720x720

Reframe with FFmpeg

bash
# 16:9 to 9:16 (center crop)
ffmpeg -i input.mp4 -vf "crop=ih*9/16:ih,scale=1080:1920" vertical.mp4

# 16:9 to 1:1 (center crop)
ffmpeg -i input.mp4 -vf "crop=ih:ih,scale=1080:1080" square.mp4

Reframe with VideoDB

python
# Smart reframe (AI-guided subject tracking)
reframed = video.reframe(start=0, end=60, target="vertical", mode=ReframeMode.smart)

Scene Detection and Auto-Cut

FFmpeg scene detection

bash
# Detect scene changes (threshold 0.3 = moderate sensitivity)
ffmpeg -i input.mp4 -vf "select='gt(scene,0.3)',showinfo" -vsync vfr -f null - 2>&1 | grep showinfo

Silence detection for auto-cut

bash
# Find silent segments (useful for cutting dead air)
ffmpeg -i input.mp4 -af silencedetect=noise=-30dB:d=2 -f null - 2>&1 | grep silence

Highlight extraction

Use Claude to analyze transcript + scene timestamps:

"Given this transcript with timestamps and these scene change points,
identify the 5 most engaging 30-second clips for social media."

What Each Tool Does Best

ToolStrengthWeakness
Claude / CodexOrganization, planning, code generationNot the creative taste layer
FFmpegDeterministic cuts, batch processing, format conversionNo visual editing UI
RemotionProgrammable overlays, composable scenes, reusable templatesLearning curve for non-devs
Screen StudioPolished screen recordings immediatelyOnly screen capture
ElevenLabsVoice, narration, music, SFXNot the center of the workflow
Descript / CapCutFinal pacing, captions, polishManual, not automatable

Key Principles

  1. Edit, don't generate. This workflow is for cutting real footage, not creating from prompts.
  2. Structure before style. Get the story right in Layer 2 before touching anything visual.
  3. FFmpeg is the backbone. Boring but critical. Where long footage becomes manageable.
  4. Remotion for repeatability. If you'll do it more than once, make it a Remotion component.
  5. Generate selectively. Only use AI generation for assets that don't exist, not for everything.
  6. Taste is the last layer. AI clears repetitive work. You make the final creative calls.

Related Skills

  • fal-ai-media — AI image, video, and audio generation
  • videodb — Server-side video processing, indexing, and streaming
  • content-engine — Platform-native content distribution

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 Video Editing AI skill do?

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

Why use Video Editing on TypingMind?

Because you install it once and use it with any model. Video Editing 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 Video Editing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/affaan-m/ECC/tree/main/.agents/skills/video-editing. 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 Video Editing?

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 Video Editing?

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

Is the Video Editing AI skill free?

Yes. It is published on GitHub by affaan-m under the MIT license. 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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