Edit any video into a captioned showcase — transcribe (any language, defaults to large-v3), present a transcript_review.txt for the user to fix mishears BEFORE rendering, then build a HyperFrames composition with liquid-glass caption pills, liquid blob background, liquid morph wipes, optional behind-subject text via background removal, and render the final video. Use whenever the user provides a video file and asks to edit it, caption it, add subtitles, fix existing captions, make a reel/promo/captioned tutorial, or "do the same" pattern as a prior captioned video. Supports English, Hebrew, and any Whisper-supported language. Renders both 16:9 (YouTube / horizontal) and 9:16 (TikTok / Instagram Reels / YouTube Shorts) from the SAME 16:9 source — vertical mode uses a centered footage strip with a blurred backdrop + liquid blobs and a vertical-tuned caption pill, no need to re-shoot. THE PIPELINE PAUSES FOR USER APPROVAL on the transcript before final render — this is the support mechanism for getting captions perfect (especially Hebrew). Pairs with hyperframes, hyperframes-cli, hyperframes-registry, and yuv-design-system skills.
$npx -y skills add hoodini/ai-agents-skills --skill video-editInstalls into the current project.
Run `npx skills use "https://github.com/hoodini/ai-agents-skills" --skill "hoodini/ai-agents-skills/video-edit"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/hoodini/ai-agents-skills" that are relevant to the current task. Run `npx skills add "https://github.com/hoodini/ai-agents-skills"` and select the relevant skills, then follow their instructions.