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affaan-m/video-editing

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.

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origin:ECC
New~2.4k
v1.2Saved Jul 14, 2026

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

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:

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

# 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

Tool Strength Weakness
Claude / 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.
  • fal-ai-media — AI image, video, and audio generation
  • videodb — Server-side video processing, indexing, and streaming
  • content-engine — Platform-native content distribution
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Overall Score

78/100

Grade

B

Good

Safety

76

Quality

75

Clarity

85

Completeness

70

Summary

This skill provides a comprehensive 6-layer pipeline for AI-assisted video editing, guiding agents through capturing, organizing, cutting, composing, generating assets, and polishing real footage. It covers the full workflow from FFmpeg batch processing through Remotion code generation, ElevenLabs voiceover, and final human polish in Descript/CapCut, emphasizing editing existing video rather than generating from scratch.

Detected Capabilities

file read (FFmpeg, Remotion, ElevenLabs code examples)file write (FFmpeg output, Remotion render, asset generation)shell execution (ffmpeg commands, bash scripts, remotion CLI)HTTP requests (ElevenLabs API, fal.ai, VideoDB)environment variable access (ELEVENLABS_API_KEY)code generation (FFmpeg commands, Remotion TSX, Python scripts)

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

cut video footageedit vlogffmpeg batch processingremotion overlayvideo pipelinereframe for tiktokvoiceover generationscene detection

Risk Signals

WARNING

ElevenLabs API key accessed via os.environ

Layer 5: Generated Assets code block
INFO

HTTP requests to external API (api.elevenlabs.io) without explicit URL validation or allowed-list documentation

Layer 5 Python example
INFO

Shell command execution via FFmpeg and bash with user-supplied timestamps and file paths

Layer 3: Deterministic Cuts, batch cut example

Referenced Domains

External domains referenced in skill content, detected by static analysis.

api.elevenlabs.iowww.remotion.dev

Use Cases

  • Cut long recordings into short-form social media content (YouTube Shorts, TikTok, Reels)
  • Convert screen recordings and tutorials into edited demos with overlays and captions
  • Generate edit decision lists (timestamps and segments) from transcripts using Claude
  • Create reusable Remotion compositions for branded templates across multiple videos
  • Reframe and export video in platform-specific aspect ratios (16:9, 9:16, 1:1)
  • Automatically detect scenes and silence to identify cutting opportunities
  • Generate voiceovers and background music for silent footage using ElevenLabs and fal.ai
  • Build vlogs and event recordings from raw multi-hour footage

Quality Notes

  • Excellent scope definition: skill explicitly focuses on editing existing footage, not generation — this boundary is clear and well-justified
  • Well-structured 6-layer pipeline with clear responsibilities for each tool; avoids monolithic 'do everything' approach
  • Strong documentation with concrete code examples for FFmpeg, Remotion, and ElevenLabs across multiple scenarios
  • Practical guidance on social media reframing with specific aspect ratios and FFmpeg recipes
  • Good error prevention via structured planning (Layer 2 with Claude) before deterministic execution (Layer 3 FFmpeg)
  • Missing: no explicit error handling guidance for failed FFmpeg cuts, network timeouts with ElevenLabs, or Remotion render failures
  • Missing: security best practices for storing ELEVENLABS_API_KEY (no mention of `.env.local`, vault, or CI/CD secrets patterns)
  • Missing: edge case coverage (corrupted video input, timeout handling, disk space checks, quota management for paid APIs)
  • Skill assumes agent has access to external APIs and understands API key management — could benefit from setup instructions
  • Related skills referenced but not explained (fal-ai-media, videodb, content-engine) — users may not know how to integrate them
Model: claude-haiku-4-5-20251001Analyzed: Jul 14, 2026

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Version History

v1.2

Content updated

2026-07-14

Latest
v1.1

Content updated

2026-04-20

v1.0

Seeded from github.com/affaan-m/everything-claude-code

2026-03-16

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