據 AlphaMoat 統計,截至 2026-09,Clips Machine 累計下載 3,427 次、獲 10 個星標,在全部 5,078 個 AI 技能中排名第 3,252 位,在「設計創意」分類(512 個)中排名第 301 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 106 | 3427 | 9 | - |
| SkillHub ↗ | 350 | 3405 | 10 | — |
各平台的計數口徑不同,統計時間不一致。
說明帶時間戳轉寫、按文字記錄選擇亮點、剪輯、字幕樣式和影片匯出,並輸出 JSON 中繼資料和 Markdown 摘要。需 ffmpeg、yt-dlp 與 whisper-cpp。審閱命令,使用獲授權媒體和可信輸出路徑並檢查結果;亮點評分不保證傳播效果。 來源資料標示的版本不一致;依賴實作細節前應核對實際綁定的修訂。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3427 | — | 10 |
| 2026-08 | 3268 | +5.7% | 10 |
| 2026-07 | 3092 | +10.6% | 9 |
| 2026-06 | 2795 | +5.0% | 9 |
| 2026-05 | 2662 | — | 8 |
| 2026-03 | 2287 | — | 7 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
---
name: clips-machine
description: Transform long videos into viral short-form clips. Auto-detect best moments, add trendy captions, export for TikTok/Reels/Shorts. Self-contained, no external modules. 100% free tools.
version: 1.1.0
author: Mayank8290
homepage: https://github.com/Mayank8290/openclaw-video-skills
tags: video, clips, tiktok, reels, shorts, viral, captions, transcription
metadata: { "openclaw": { "requires": { "bins": ["ffmpeg", "yt-dlp", "whisper-cpp"] } } }
---
# Clips Machine Transform long videos into viral short-form clips. Auto-detect the best moments, add trendy captions, export for TikTok/Reels/Shorts. **100% FREE tools** - Runs entirely on your machine. > **Love this skill?** Support the creator and help keep it free: **[Buy Me a Coffee](https://buymeacoffee.com/mayank8290)** ## What This Skill Does 1. **Input** any long video (YouTube URL, podcast, stream, local file) 2. **Transcribe** with timestamps using Whisper (free, local) 3. **Detect** viral-worthy moments using AI analysis 4. **Cut** the best 30-60 second segments 5. **Caption** with animated, trendy text styles 6. **Export** in vertical 9:16 format ready for upload ## Quick Start ``` Turn this podcast into viral clips: https://youtube.com/watch?v=xyz ``` ``` Extract the 5 best moments from my-interview.mp4 and add captions ``` ## Commands ### From YouTube URL ``` /clips-machine https://youtube.com/watch?v=VIDEO_ID ``` ### From Local File ``` /clips-machine /path/to/video.mp4 ``` ### Custom Number of Clips ``` /clips-machine VIDEO --clips 10 ``` ### Caption Styles ``` /clips-machine VIDEO --style [style] ``` Available styles: - `hormozi` - Alex Hormozi style (bold, word-by-word highlight) - **Most Viral** - `minimal` - Clean white text - `karaoke` - Word-by-word color change - `news` - Lower third style - `meme` - Impact font, top/bottom ## How Viral Detection Works The AI analyzes the transcript looking for: 1. **Hook Potential** - Strong opening statements 2. **Emotional Peaks** - Passion, excitement, surprise 3. **Quotable Lines** - Memorable one-liners 4. **Controversial Takes** - Debate-worthy opinions 5. **Surprising Facts** - "Did you know" moments 6. **Actionable Advice** - Clear takeaways Each moment gets a "virality score" from 1-100. ## Output Structure ``` ~/Videos/OpenClaw/clips-[video-name]/ ├── transcript.json # Full transcript with timestamps ├── viral_moments.json # Detected moments with scores ├── clip_001.mp4 # First viral clip (vertical, captioned) ├── clip_002.mp4 # Second viral clip ├── clip_003.mp4 # ... └── summary.md # Overview of all clips ``` ## Supported Sources | Source | Example | |--------|---------| | YouTube | `https://youtube.com/watch?v=...` | | TikTok | `https://tiktok.com/@user/video/...` | | Twitter/X | `https://twitter.com/user/status/...` | | Twitch VOD | `https://twitch.tv/videos/...` | | Local MP4 | `/path/to/file.mp4` | ## Requirements - FFmpeg (`brew install ffmpeg`) - yt-dlp (`brew install yt-dlp`) - Whisper.cpp (`brew install whisper-cpp`) ## Setup ```bash # Install dependencies brew install ffmpeg yt-dlp whisper-cpp # Or on Linux sudo apt install ffmpeg pip install yt-dlp # Build whisper.cpp from source ``` ## Monetization | Method | Potential | |--------|-----------| | Clip service for creators | $50-150/video | | Monthly retainer | $500-2,000/client | | Podcast clipping agency | $2,000-5,000/mo | | Sell this skill | $100-300 on ClawHub | ## Examples ### Podcast to Clips ``` Take this 2-hour podcast and find the 10 best moments: https://youtube.com/watch?v=PODCAST_ID Make them Hormozi-style with bold captions. ``` ### Interview Highlights ``` /clips-machine interview.mp4 --clips 5 --style minimal ``` ### Gaming Stream ``` Extract funny moments from my Twitch VOD: https://twitch.tv/videos/12345 Add meme-style captions ``` --- ## Support This Project If this skill saved you time or made you money, consider buying me a coffee! **[Buy Me a Coffee](https://buymeacoffee.com/mayank8290)** Every coffee helps me build more free tools for the community. --- Built for OpenClaw | Powered by Whisper + FFmpeg | [Support the Creator](https://buymeacoffee.com/mayank8290)
ContextWeave 架構圖一鍵生成
用 Nano Banana Pro 生成或編輯圖片的指令碼技能。
用 whisper 命令列工具在本機將音訊轉成文字或進行翻譯。
透過 MCP 服務生成與編輯圖表的技能。
面向介面設計的思路與落地建議技能,覆蓋佈局、互動流程、設計令牌與前端改動。
面向多家影片模型 API 的 AI 影片生成與編排技能。
用 ffmpeg 從影片裡取出畫面幀,或生成便於快速檢視的縮圖。
用本地 Whisper 把音訊檔案轉成文字,模型下載完成後可完全離線執行。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。