What are the prerequisites for using the rip-video skill?

You must have the MCP 'rip-video' service configured and running, and ffmpeg/ffprobe must be installed on your system path.

Can I customize the extraction quality?

Extraction settings like MP3 bitrate (default 192kbps) and cover timestamp (00:00:01) are handled by the MCP service configuration.

How does the skill identify which videos to process?

The skill scans your local todolist.md file for MP4 entries that are marked as completed [x] but have missing associated assets like .mp3 or .srt files.

Does this skill support non-embedded subtitles?

Currently, the skill focuses on extracting embedded SRT tracks from the MP4 container. If no embedded subtitles are found, it will log the status without failing the task.

Will it overwrite my existing audio or image files?

No, the skill includes a safety check that automatically skips any assets that already exist on disk to save time and prevent data loss.

Video Asset Extractor

Name: Video Asset Extractor
Author: mojito-llm

bymojito-llm

Content Management

Extracts audio, subtitles, and cover images from MP4 video files based on automated task checklists.

About

The Video Asset Extractor skill automates the post-processing of video files by stripping essential resources like MP3 audio, SRT subtitles, and high-quality cover images. Designed to work within a structured workflow, it reads from a todolist.md file to identify pending tasks, utilizes an MCP service powered by ffmpeg for precise extraction, and updates the task status upon completion. This skill is ideal for users who need to repurpose video content for podcasts, transcripts, or organized media libraries without manual intervention.

Key Features

Smart file checking to skip already processed resources
Markdown-driven task management via todolist.md integration
Detailed status reporting with success and failure metrics
Automated extraction of MP3 audio, SRT subtitles, and JPG covers
Seamless integration with ffmpeg-based MCP services
0 GitHub stars

Use Cases

Repurposing downloaded social media videos into audio-only podcasts
Batch processing video archives to generate subtitles and thumbnails
Automating content pipelines that require structured media assets

About

Key Features

Smart file checking to skip already processed resources
Markdown-driven task management via todolist.md integration
Detailed status reporting with success and failure metrics
Automated extraction of MP3 audio, SRT subtitles, and JPG covers
Seamless integration with ffmpeg-based MCP services
0 GitHub stars

Use Cases

Repurposing downloaded social media videos into audio-only podcasts
Batch processing video archives to generate subtitles and thumbnails
Automating content pipelines that require structured media assets