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From antigravity-awesome-skills
Extracts key frames from MP4 videos at configurable intervals, runs Tesseract OCR, and generates structured Markdown reports with video metadata and timestamped text transcripts.
npx claudepluginhub sickn33/antigravity-awesome-skills --plugin antigravity-bundle-aas-mobile-app-builderHow this skill is triggered — by the user, by Claude, or both
Slash command
/antigravity-awesome-skills:video-content-extractorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
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.
Extracts key frames from videos and animated images (GIF, APNG, WebP) into a viewable timeline using peepshow (ffmpeg). Also reads audio transcripts and metadata.
Decomposes videos into meaningful keyframes using ffmpeg scene detection filter. Extracts images on scene changes (threshold 0.01), timestamps from logs, supports MP4/MOV/WEBM/AVI/MKV. Adjusts sensitivity; warns on low frame counts indicating static videos.
Analyzes video files by extracting frames, describing segments, and burning captions as PNG overlays using PIL and ffmpeg. Useful for adding visual descriptions or evidence annotations.
Share bugs, ideas, or general feedback.
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.
The skill uses ffprobe to extract video metadata: duration, resolution, frame rate, codec information, and file size.
Using FFmpeg, the skill captures frames at the configured interval (default: every 30 seconds). Each frame is saved as a timestamped JPEG image.
Each extracted frame is processed by Tesseract OCR. If the default PSM mode returns no meaningful text, it falls back to fully automatic page segmentation.
All extracted data is assembled into a structured Markdown document.
Agent prompt: Use the video-content-extractor skill to extract content from lecture.mp4
Output generates lecture.md and lecture_frames/ directory.
Parameters: video_path, output_dir, interval(seconds), lang Extract every 60 seconds with English-only OCR: python scripts/extract_video.py recording.mp4 ./output 60 eng
Extract with default Chinese + English OCR: python scripts/extract_video.py lecture.mp4 . 15 chi_sim+eng
Problem: Tesseract returns garbled text Solution: Ensure the correct language pack is installed. Run tesseract --list-langs to verify.
Problem: FFmpeg fails with "not found" Solution: Make sure FFmpeg is on PATH. Run ffmpeg -version to verify.
Problem: OCR is slow on large videos Solution: Increase the interval parameter to reduce frames processed.