watch-cli-video-agent

To analyze a YouTube video using frames and transcripts, the Skill decomposes the video into extracted image frames and an audio transcript. This allows an AI agent to consume both modalities for cheaper, deeper video understanding and summarization.

Yes, you can extract code architecture from a tutorial video. By analyzing code-relevant frames alongside the step-by-step transcript guidance, an AI agent can generate an implementation based on the visual and audio content of the video.

Yes, the video analysis pipeline supports login-walled social media platforms. It works across YouTube, X/Twitter, LinkedIn, TikTok, Reddit, Vimeo, and Facebook, allowing you to access login-walled pages via cookies for content extraction.

Extracting frames and transcribing audio requires downloading videos with yt-dlp, extracting frames and audio with ffmpeg, and transcribing audio via a Kyma-backed workflow. You need an API key, with optional support for bring-your-own model keys.

Decomposing a video into frames and transcripts makes multimodal video understanding cheaper and faster. It produces a structured result that an AI agent can directly consume for tasks like UI cloning, architecture extraction, and audio scene Q&A.