video-editing
affaan-m/ECC · Agent Skill
人工智慧輔助的影片素材編輯和結構化,包括剪輯、新增字幕和配音,用於內容創作。
前往安裝 ↓總覽
| 發布者 | |
|---|---|
| 儲存庫 | affaan-m/ECC ↗ |
| 技能資料夾 | video-editing |
| 星 | 257,549 |
| 分支 | 38,524 |
| 附帶檔案 | 2 |
| 授權 | MIT |
| 最近更新 | 2026年9月12日 |
| 連結 | 技能原始碼 ↗ · 儲存庫 ↗ |
Mozgi 檢查
我們在技能檔案中發現的內容。詳細資訊需訂閱。
安裝
技能就是一個含 SKILL.md 的資料夾。選擇你的代理,在專案根目錄的終端機(macOS、Linux 或 Windows 的 Git Bash)執行指令。
把提示貼到 Claude、Codex 或其他助理:它會自行檢查並安裝技能。
Install the “video-editing” skill from mozgi.io (https://mozgi.io/skills/video-editing/) for me. 1. Download the archive: https://mozgi.io/skills/video-editing/download If it fails, take the skill folder from the source: https://github.com/affaan-m/ECC/tree/main/.agents/skills/video-editing 2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me. 3. Put the “video-editing” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.). 4. Make sure <skills folder>/video-editing/SKILL.md exists. 5. Briefly tell me what this skill does and offer to try it on my task. If you cannot do a step yourself, tell me what to click or type.
git clone --depth 1 --branch main 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
重新啟動 Claude Code — 技能就會出現在清單中,手動呼叫:/video-editing。要套用到所有專案,請放在 ~/.claude/skills。
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .agents/skills cp -r /tmp/ECC/.agents/skills/video-editing .agents/skills/video-editing
Codex 會從目前資料夾往上到儲存庫根目錄,在 .agents/skills 中尋找技能;用 /skills 或 $video-editing 呼叫。所有專案:~/.agents/skills。
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .cursor/skills cp -r /tmp/ECC/.agents/skills/video-editing .cursor/skills/video-editing
Cursor 啟動時會載入技能;在 Agent 聊天輸入「/」呼叫。Cursor 也會讀取 .claude/skills 與 .agents/skills。所有專案:~/.cursor/skills。
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .gemini/skills cp -r /tmp/ECC/.agents/skills/video-editing .gemini/skills/video-editing
任務符合時,Gemini CLI 會提議啟用技能,由你確認。所有專案:~/.gemini/skills。
安裝前請先檢視 SKILL.md 與相關檔案。點擊檔案即可預覽。
SKILL.md 內容
作者原文 · 唯讀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
videodbskill)
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(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:
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
# 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.
Related Skills
fal-ai-media— AI image, video, and audio generationvideodb— Server-side video processing, indexing, and streamingcontent-engine— Platform-native content distribution
常見問題
video-editing 技能有什麼用途?
人工智慧輔助的影片素材編輯和結構化,包括剪輯、新增字幕和配音,用於內容創作。
如何安裝 video-editing?
打開本頁的「安裝」區塊並選擇你的代理 — Claude Code、Codex、Cursor 或 Gemini CLI:那裡有把技能資料夾複製到正確位置的現成指令。也可以複製「透過助理」分頁中的提示,讓助理自行檢查並安裝技能。
video-editing 適用哪些 AI 模型?
技能是純 Markdown 指示(Agent Skills 格式),因此 video-editing 適用任何讀取 SKILL.md 的代理:Claude Code、Codex、Cursor、Gemini CLI、GitHub Copilot、OpenCode 等。只有在任務符合技能描述時,模型才會載入指示。
video-editing 是免費的嗎?
此技能由 affaan-m 公開發布,採用 MIT 授權。技能本身免費 — 你只需向 AI 供應商支付實際使用的 token 費用。
安裝技能安全嗎?
技能是代理會遵循的指示,安裝前請閱讀 SKILL.md 及相關檔案。技能資料夾中的腳本只有在代理執行時才會運行 — 留意它的動作,不要授予多餘權限。
技能和 MCP 伺服器或外掛有何不同?
MCP 伺服器或外掛為模型提供新工具 — 會執行並回傳結果的程式碼。技能提供的是知識與流程:如何處理任務、要遵循哪些步驟、好的成果長什麼樣子。它不需要伺服器或 API 金鑰。