From Full Episode to Highlight Reel in Minutes

Podcast episodes are packed with quotable moments, strong arguments, and emotional peaks — but finding and clipping them by hand is a time sink that most creators can't afford. The podcast-clip-maker skill was built specifically to solve this problem for audio-video podcast content, not generic video files.

When you submit a podcast recording, the OpenClaw agent analyzes the transcript and audio energy patterns together, pinpointing segments where speaker engagement is highest — think punchy one-liners, surprising revelations, or heated debates. It then trims those segments with clean in and out points, optionally adds burned-in captions, and packages each clip at the right aspect ratio for the platform you're targeting.

Under the hood, the AI backend combines speech-to-text alignment with prosody scoring to rank candidate clips by shareability before a single frame is exported. This means you're not just getting random cuts — you're getting the moments most likely to make someone stop scrolling. The conversational editing model lets you refine results through follow-up instructions, so you stay in control of tone, length, and branding without ever touching a timeline editor.

Environment Variables