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

For measured reference-driven work, chain taste-distillation into taste-application, then return here for the editor and final-output review. The standalone taste skills can use existing footage; generation is optional.

Before live editor or DAW changes, save a versioned project checkpoint and verify the file exists. Save and verify another checkpoint after the changes. An API readback proves the current in-memory state, not that it was saved. Keep rendered media, editable projects, and creative approval as separate states in the handoff.

For MIDI-driven audio, check pitches against the receiving rack's note mapping and audition the result; successful clip creation can still produce silence. For reconstructed projects, validate through native load and save, sort events in timeline order, verify sample links and mute states, then check and audition the exact exported audio for unintended silence. XML parsing alone does not prove that the DAW accepted every clip or produced audible output. Check a bridge's capability handshake before invoking newer commands. Do not enable upload or training-data telemetry as a side effect of a creative task; use a supported local control path when consent or capability is absent.

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

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

Batch cut from edit decision list

#!/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

# 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

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

Extract audio for transcription

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

Normalize audio levels

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

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

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

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:

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:

Reframe with FFmpeg

# 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

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

# 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

# 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

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.

Native Fusion Presets

ITO Production v1 provides restrained highlight bloom, opposing RGB spatial offsets and a luminance/edge halo. The exact files passed prior native import, save/reopen and short motion-render checks after two-source visual review. These are starting values requiring shot-specific review; the halo does not detect or track subjects.

ITO V28 contains preserved, native-verified Fusion graph snippets and an idempotent Lua installer. These are technical compatibility examples, not recommended production defaults: their documented visual limitations require tuning and taste review before use. See the bundle provenance for the scope of prior import and render checks.

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