---
name: video-editing-d67cca03f7d5
description: 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.
origin: ecc
---

# 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
  → Codex / 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 (Codex / Codex)

Use OpenAI Codex 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](https://www.remotion.dev/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(app_id: "fal-ai/nano-banana-pro", input_data: {
  "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:

| Platform | Aspect Ratio | Resolution |
|----------|-------------|------------|
| YouTube | 16:9 | 1920x1080 |
| TikTok / Reels | 9:16 | 1080x1920 |
| Instagram Feed | 1:1 | 1080x1080 |
| X / Twitter | 16:9 or 1:1 | 1280x720 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
from videodb import ReframeMode

# 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 Codex 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

| Tool | Strength | Weakness |
|------|----------|----------|
| Codex / Codex | Organization, planning, code generation | Not the creative taste layer |
| FFmpeg | Deterministic cuts, batch processing, format conversion | No visual editing UI |
| Remotion | Programmable overlays, composable scenes, reusable templates | Learning curve for non-devs |
| Screen Studio | Polished screen recordings immediately | Only screen capture |
| ElevenLabs | Voice, narration, music, SFX | Not the center of the workflow |
| Descript / CapCut | Final pacing, captions, polish | Manual, 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


---
Source attribution: mturac
Original project: https://github.com/mturac/everything-openai-codex/blob/b5057da5f42ed6b12cd3a59e89af0ccd12cff7c2/skills/video-editing/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Mehmet Turac

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


## Additional upstream notices

video-editing-d67cca03f7d5/DAVEAI-UPSTREAM-NOTICE.md

# Notices and Acknowledgements

Everything OpenAI Codex is a Codex-focused adaptation inspired by the public
[`affaan-m/everything-claude-code`](https://github.com/affaan-m/everything-claude-code)
project.

Respect to Affaan Mustafa and the contributors to that project for making the
multi-harness agent operating-system pattern visible in the open.

This repository adapts the public idea and workflow surface for OpenAI Codex:
names, defaults, install targets, docs, validators, and cross-harness guidance
are maintained here for the Codex-oriented project.


# Mega AI Hub resource metadata

Creator / publisher: mturac
Original project: https://github.com/mturac/everything-openai-codex/blob/b5057da5f42ed6b12cd3a59e89af0ccd12cff7c2/skills/video-editing/SKILL.md
Attribution basis: Source repository record

Fields of work: Content & Media, Marketing
Roles: Content Marketer, Copywriter, Influencer Marketer, Social Media Manager, Video Producer
Specialties: API
Tools: ElevenLabs, FFmpeg
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 274b5b97b44f78c08d0b4528afcb45edc5d4f7f6ed744f1271ae1c5204468c14
