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Video Editing

Community
notque
video-editing

Video editing pipeline: cut footage, assemble clips via FFmpeg and Remotion.

Overview

Publishernotque
Repositoryvexjoy-agent
Skill namevideo-editing
Stars
443
Forks
50
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

    Published by notque 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/notque/vexjoy-agent/tree/main/skills/content/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/notque/vexjoy-agent.git /tmp/vexjoy-agent
mkdir -p .claude/skills
cp -r /tmp/vexjoy-agent/skills/content/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 Skill

Overview

This skill implements a 6-layer pipeline where AI handles judgment tasks (what to keep, what to cut, highlight selection) and FFmpeg/Remotion handle mechanical execution deterministically.

LayerNameMechanismPrimary Tool
1CAPTUREInventory source footageBash + Glob
2AI STRUCTURETranscript to EDLLLM judgment
3FFMPEG CUTSEDL to segment filesFFmpeg (deterministic)
4REMOTION COMPOSITIONSegments to TSX compositionRemotion + TypeScript
5AI GENERATIONFill gaps with generated assetsElevenLabs / fal.ai (conditional)
6FINAL POLISHHuman taste layerHuman + NLE

Deep References

SignalLoadContent
Shell commands for each phase, gate checksreferences/phase-commands.mdFull command blocks for Phases 1-6
FFmpeg recipes: cutting, concat, proxy, detectionreferences/ffmpeg-commands.mdTimestamp extraction, batch cutting, audio normalization, scene/silence detection
Remotion composition scaffoldreferences/remotion-scaffold.mdTSX composition template, render command, reuse patterns
Image-to-video pipelinereferences/image-to-video.mdValidate, prepare, encode, verify workflow
FFmpeg filter graphs for visualizationreferences/ffmpeg-filters.mdScale/pad, showwaves, showspectrum, overlay, complete filter graphs

Instructions

Preflight (Run before Phase 1)

Hard requirements (BLOCK if missing): ffmpeg (all phases), node (Remotion / npx). Soft requirements (WARN if missing): remotion (only required for Phase 4).

bash
which ffmpeg >/dev/null 2>&1 || { echo "ERROR: ffmpeg not found. Install: brew install ffmpeg (macOS) | apt install ffmpeg (Linux)"; exit 1; }
which node >/dev/null 2>&1 || { echo "ERROR: node not found. Install: https://nodejs.org or via nvm"; exit 1; }
npx remotion --version >/dev/null 2>&1 || echo "WARNING: remotion CLI not found. Phase 4 unavailable. Install: npm install @remotion/cli"

Phase 1: CAPTURE

Goal: Inventory all source footage and confirm files exist on disk before any processing.

Constraint: Source files are read-only. All FFmpeg commands write to new files only. Never overwrite source footage.

Steps: locate source files (find), inspect each with ffprobe, generate proxies for files >10 min (see references/ffmpeg-commands.md -> Proxy Generation), create working directories (segments/, assembled/). Full command block: references/phase-commands.md -> Phase 1.

Gate: Source files confirmed on disk. File list written to source-inventory.txt. Proceed only when gate passes.


Phase 2: AI STRUCTURE

Goal: Analyze content and produce a written EDL (cuts.txt) that drives all downstream cutting.

Constraint: cuts.txt is the contract. The EDL file is the only source of truth for downstream phases. Do not hand-edit FFmpeg commands — generate them from the EDL.

Constraint: Before writing the EDL manually, run FFmpeg scene/silence detection. Detection output informs judgment, not replaces it.

Steps: transcribe with whisper/AssemblyAI, run scene/silence detection, apply judgment (what advances narrative, what is filler, target duration), write cuts.txt in EDL format START_TIME,END_TIME,LABEL, review for overlap and total duration. Full command block and EDL format example: references/phase-commands.md -> Phase 2.

Gate: transcript.txt exists. cuts.txt written to disk. Proceed only when both files exist.


Phase 3: FFMPEG CUTS

Goal: Execute the EDL deterministically — one FFmpeg cut per segment in cuts.txt.

Constraint: Batch-cut from EDL using a loop. Do not create individual FFmpeg commands per cut. This ensures reproducibility and review capability as a list.

Constraint: Always generate concat-list.txt from cuts.txt order, not from shell glob. Shell glob (segments/*.mp4) sorts alphabetically, not by EDL order.

Steps: batch-cut from EDL with while loop (libx264/aac, -avoid_negative_ts make_zero), verify segments, generate concat-list.txt in EDL order, concat with -f concat -safe 0 -c copy. Full command block: references/phase-commands.md -> Phase 3. See also references/ffmpeg-commands.md -> Batch Cutting.

Gate: All segment files exist. assembled/rough-cut.mp4 written to disk. Proceed only when gate passes.


Phase 4: REMOTION COMPOSITION

Goal: Wrap segments in a Remotion TSX composition for programmatic overlays, titles, or transitions.

When to use: Only when rough-cut.mp4 requires programmatic elements (animated titles, lower thirds, caption tracks, brand overlays). If rough-cut.mp4 is sufficient, skip to Phase 6.

Constraint: Layer 4 requires TypeScript/React. Hand off to typescript-frontend-engineer for TSX work; return to python-general-engineer for Phase 5 onward.

Steps: initialize Remotion (npm create video@latest first time; otherwise npm install @remotion/cli @remotion/player remotion), scaffold composition (see references/remotion-scaffold.md), render with npx remotion render. Full command block: references/phase-commands.md -> Phase 4.

Gate: assembled/remotion-output.mp4 exists. Proceed only when gate passes.


Phase 5: AI GENERATION

Goal: Fill genuine gaps in source material with generated assets — only when needed.

Constraint: Check whether existing footage covers the gap before generating anything. Generate only what doesn't exist.

Decision tree: cut around the gap → update cuts.txt and re-run Phase 3; voiceover → ElevenLabs (authorization required); music → fal.ai (defer to fal-ai-media); b-roll → fal.ai (defer to fal-ai-media). ElevenLabs Python helper, authorization pattern, and save-to-disk flow: references/phase-commands.md -> Phase 5.

Gate: All required generated assets saved to assets/ directory before proceeding.


Phase 6: FINAL POLISH

Goal: Deliver assembled output and hand off taste-layer work to human.

Constraint: Layer 6 is human territory. The skill assembles; the human finishes. The following require human judgment and should not be attempted programmatically:

  • Color grading and color matching between clips
  • Music timing and volume ducking
  • Caption style, font, positioning
  • Transition timing and style
  • Final audio mix levels

Handoff template (handoff-notes.txt with source list, EDL, rough-cut path, remaining-for-human checklist): references/phase-commands.md -> Phase 6.

Gate: assembled/rough-cut.mp4 (or assembled/remotion-output.mp4) exists. handoff-notes.txt written to disk.


Video Transcript Extraction

Pull a video's transcript as readable paragraphs. Prefer uploader subtitles; fall back to auto-generated.

bash
# Path 1: uploader subtitles (accurate)
yt-dlp --skip-download --write-subs --sub-langs en --sub-format vtt -o '<work-dir>/%(id)s' '<URL>'
# Path 2: auto-generated (fallback when path 1 writes no file)
yt-dlp --skip-download --write-auto-subs --sub-langs en --sub-format vtt -o '<work-dir>/%(id)s' '<URL>'
# Clean VTT to paragraphs
python3 skills/research/video-transcript/scripts/vtt_to_paragraph.py <work-dir>/<id>.en.vtt

Options: --timestamps for [mm:ss] markers, --keep-brackets for cue tags, -o FILE for file output. Other languages: change --sub-langs. List available: yt-dlp --list-subs '<URL>'.

Error Handling

ErrorCauseSolution
"No such file or directory" on sourcePath in cuts.txt doesn't match filenameRun cat source-inventory.txt. Quote paths with spaces.
FFmpeg "Invalid option" or codec errorsCodec unavailable or flag syntax errorffmpeg -codecs | grep libx264. Fall back to -c:v copy.
Remotion "Could not find composition"Composition ID mismatchCheck src/index.ts for registered ID. Match exactly in render command.
Segments concat in wrong orderShell glob sorts alphabetically, not by EDLGenerate concat-list.txt from cuts.txt order, not from glob.
ElevenLabs 401ELEVENLABS_API_KEY not setexport ELEVENLABS_API_KEY=your_key before Phase 5.
No .vtt file from transcript extractionVideo has no subtitles in requested languageyt-dlp --list-subs '<URL>' and pick an available language.

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?

Video editing pipeline: cut footage, assemble clips via FFmpeg and Remotion.

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/notque/vexjoy-agent/tree/main/skills/content/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 notque 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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