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Auto Clipper

Automatically create clips and videos from media files in a specified folder. Uses Agent Swarm for intelligent task delegation and supports cron-based schedu...

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Automatically create clips and videos from media files in a specified folder. Uses Agent Swarm for intelligent task delegation and supports cron-based schedu...

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Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Manual review
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
README.md, SKILL.md, _meta.json, config.json, scripts/auto_clipper.py, scripts/run.sh

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Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 22 sections Open source page

Description

Automatically create clips and videos from media files in a specified folder. Uses Agent Swarm for intelligent task delegation and supports cron-based scheduling.

AutoClipper

Automatic Video Clip & Highlight Generator for OpenClaw. v1.0.0 โ€” Design draft. Automatically scan a folder for media files, create clips/highlights using ffmpeg, and organize output. Cron-ready for scheduled automation.

Installation

# Add to crontab (crontab -e) # Run every hour at minute 0 0 * * * * /Users/ghost/.openclaw/workspace/skills/auto-clipper/scripts/run.sh # Or run daily at 9 AM 0 9 * * * /Users/ghost/.openclaw/workspace/skills/auto-clipper/scripts/run.sh --output daily

Usage

Screen recording highlights: Auto-clip moments from Loom/obsidian recordings Meeting recaps: Extract key segments from meeting recordings Content creation: Batch-process raw footage into short clips Security camera clips: Pull motion-triggered segments from camera feeds Gaming highlights: Auto-clip "best of" moments from recordings # Run once (scan and process) python3 scripts/auto_clipper.py run # Dry run (show what would be processed) python3 scripts/auto_clipper.py run --dry-run # Force reprocess all files python3 scripts/auto_clipper.py run --force # Start continuous watcher (not cron-based) python3 scripts/auto_clipper.py watch # Show status python3 scripts/auto_clipper.py status

Purpose

AutoClipper enables OpenClaw agents to automatically: Monitor a watch folder for new media files (videos, screen recordings, camera clips) Analyze media to understand what's worth clipping (via Agent Swarm delegation) Generate clips using ffmpeg (highlights, segments, trimmed videos) Produce compilations by stitching multiple clips together Schedule runs via cron for fully automated workflows

Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ AutoClipper Skill โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ 1. Watch Folder (configurable input path) โ”‚ โ”‚ โ†“ โ”‚ โ”‚ 2. Media Scanner (find new files, filter by extension) โ”‚ โ”‚ โ†“ โ”‚ โ”‚ 3. Agent Swarm delegation (analyze โ†’ clip strategy) โ”‚ โ”‚ โ†“ โ”‚ โ”‚ 4. Clip Engine (ffmpeg operations) โ”‚ โ”‚ โ†“ โ”‚ โ”‚ 5. Output Organizer (save to output folder, optional SNS) โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

1. Watch Folder Scanner

Monitors a configured input directory Filters by file extensions: .mp4, .mov, .mkv, .avi, .webm Tracks processed files (to avoid re-processing) Configurable: watchFolder, fileExtensions, processedLog

2. Media Analyzer (via Agent Swarm)

Delegates analysis to appropriate model (MiniMax for code/technical, Kimi for creative) Determines: Which segments to clip (timestamp ranges) Clip duration targets Output format preferences Returns structured clip plan: [{start, end, label, priority}]

3. Clip Engine (ffmpeg)

Trim: Extract segments without re-encoding (fast) Transcode: Convert to target format/codec Highlight: Auto-detect "interesting" segments (via scene detection) Compile: Stitch multiple clips into single video Overlay: Add watermarks, timestamps, captions

4. Output Manager

Organized output folder structure: output/YYYY-MM-DD/ Configurable naming: {original}-{timestamp}-{index}.mp4 Optional: Notify via OpenClaw message (Discord, WhatsApp, etc.)

5. Cron Scheduler

Standalone script for cron integration Configurable schedule: 0 * * * * (hourly), 0 9 * * * (daily at 9am) Dry-run mode for testing Lock file to prevent overlapping runs

Configuration (config.json)

{ "watchFolder": "~/Downloads/Recordings", "outputFolder": "~/Videos/Clips", "fileExtensions": [".mp4", ".mov", ".mkv"], "processedLog": "logs/processed.json", "clipSettings": { "defaultDuration": 60, "minClipDuration": 10, "maxClipDuration": 300, "outputCodec": "h264", "outputFormat": "mp4" }, "intentRouter": { "enabled": true, "model": "openrouter/minimax/minimax-m2.5" }, "cron": { "schedule": "0 * * * *", "enabled": false }, "notifications": { "enabled": false, "channel": "discord" } }

Tools Needed

ToolPurposeRequiredffmpegVideo transcoding, trimming, clippingYesffprobeMedia metadata extraction (duration, codec)YesAgent SwarmAnalyze media and determine clip strategyYesOpenClaw messageSend notifications when clips are readyOptionalOpenClaw nodesScreen recording capture (live input)Optionalfile systemWatch folder, output managementYes

Agent Swarm integration

When AutoClipper finds new media, it delegates analysis: User task: "Analyze video and suggest clip timestamps for meeting highlights" โ†’ router.spawn() โ†’ sessions_spawn(task, model) โ† Returns: [{start: "00:05:30", end: "00:07:45", label: "action item discussion"}, ...] Prompt template for media analysis: Analyze this video file: {filename} Duration: {duration_seconds} seconds Extract: Key moments worth clipping as short highlights (30-90 seconds each) Output: JSON array of {start_timestamp, end_timestamp, description}

Directory Structure

auto-clipper/ โ”œโ”€โ”€ SKILL.md # This file โ”œโ”€โ”€ _meta.json # Skill metadata โ”œโ”€โ”€ config.json # Configuration โ”œโ”€โ”€ README.md # Setup instructions โ”œโ”€โ”€ scripts/ โ”‚ โ”œโ”€โ”€ auto_clipper.py # Main entry point โ”‚ โ”œโ”€โ”€ scanner.py # Watch folder scanner โ”‚ โ”œโ”€โ”€ clipper.py # ffmpeg wrapper โ”‚ โ”œโ”€โ”€ analyzer.py # Agent Swarm integration โ”‚ โ””โ”€โ”€ run.sh # Cron launcher โ””โ”€โ”€ logs/ โ””โ”€โ”€ processed.json # Track processed files

Keywords

video, clip, clips, highlight, highlights trim, cut, extract, segment ffmpeg, transcode, encode, convert folder, watch, monitor, automation cron, schedule, batch, process screen recording, meeting, recording

Skill Name Ideas

AutoClipper โœ“ (chosen) ClipForge MediaMason VideoHarvest HighlightHub ClipStream MediaSnip AutoTrim

Phase 1: Core (MVP)

Folder scanner with extension filtering Basic ffmpeg trim operation Simple processed file tracking CLI entry point

Phase 2: Intelligence

Agent Swarm integration for clip planning Scene detection for auto-highlighting Metadata extraction with ffprobe

Phase 3: Automation

Cron launcher script Continuous watcher mode Notification system Output organization

Phase 4: Advanced

Multi-clip compilation Overlay/watermark support Custom clip templates Node camera integration

Notes

Performance: Use -c copy for fast trimming (no re-encode) Storage: Auto-cleanup processed files or move to archive Error handling: Skip corrupted files gracefully, log failures Idempotency: Same input file should not produce duplicate output

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
2 Docs2 Scripts2 Config
  • SKILL.md Primary doc
  • README.md Docs
  • scripts/auto_clipper.py Scripts
  • scripts/run.sh Scripts
  • _meta.json Config
  • config.json Config