Extract frames and OCR text from MP4 videos
Extracts key frames from MP4 videos at configurable intervals, performs OCR text recognition on each frame, and generates structured Markdown reports
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Why it matters
Automatically process video files to extract visual frames at set intervals and recognize all text content, delivering a comprehensive Markdown report with metadata, timestamps, and frame-by-frame transcripts for analysis and documentation.
Outcomes
What it gets done
Extract key frames from MP4 files at configurable time intervals
Perform OCR text recognition on each extracted video frame
Capture video metadata including duration, resolution, and codecs
Generate structured Markdown reports with timestamped OCR transcripts
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-video-content-extractor | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
Video Content Extractor
Video Content Extractor automatically extracts key frames from MP4 video files at configurable time intervals and performs OCR text recognition on each frame. It generates a structured Markdown report that includes video metadata (duration, resolution, codecs) and frame-by-frame OCR transcripts with timestamp references. Use this skill when you need to extract and index visible text content from video files, such as screen recordings, tutorial videos, or presentation captures. It's designed for scenarios where you need searchable transcripts of visual content or documentation of text displayed in videos.
What it does
Video Content Extractor automatically processes MP4 video files by extracting key frames at configurable time intervals and performing OCR text recognition on each captured frame. It generates a comprehensive structured Markdown report that includes video metadata (duration, resolution, codecs) and frame-by-frame OCR transcripts with precise timestamp references.
When to use - and when NOT to
Use this skill when you need to extract and index text content from video files, such as analyzing screen recordings, tutorial videos, presentation captures, or any video containing readable text. It's ideal for creating searchable transcripts of visual content, documenting software demonstrations, or archiving information displayed in video format.
Do not use this skill if your videos lack visible text content, as OCR will produce minimal useful output. This is not suitable for audio transcription - it only extracts visible text from video frames, not spoken words.
Inputs and outputs
You provide MP4 video files and configure the time interval for frame extraction. The skill outputs a structured Markdown report containing video metadata (duration, resolution, codecs) and OCR-recognized text from each frame with corresponding timestamp references.
Integrations
This skill is designed for Codex CLI and requires two local dependencies: FFmpeg for video frame extraction and processing, and Tesseract OCR for optical character recognition on the extracted frames. Both tools must be installed on your local machine before using this skill.
Who it's for
This skill serves developers, technical writers, QA engineers, and content creators who work with video content containing text. It's particularly valuable for teams documenting software interfaces, analyzing screen recordings, or building searchable archives of video tutorials and presentations where visual text content needs to be extracted and indexed.
Source README
Automatically extracts key frames from MP4 video files at configurable time intervals, performs OCR text recognition on each frame, and generates a structured Markdown report. The report includes video metadata (duration, resolution, codecs) and frame-by-frame OCR transcripts with timestamp references.
This skill is designed for Codex CLI and requires FFmpeg and Tesseract OCR installed on the local machine.
Discussion
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