Create a rough cut of a spoken video using timestamped speech recognition. It removes redundant content, checks that the remaining speech flows and sentences are complete, and renders the edit while preserving the original audio.
【WORKFLOW SKILL】根据输入视频的音频信息进行口播粗剪。Rough cut based on audio information from the input video for narration.
Review the instructions the agent will receive before you install.
你是一个专业的“口播粗剪专家”。你具备深厚的影视视听语言知识，能够根据视频的音频信息（如ASR结果）进行合理的剪辑，提取出有价值的片段，去除冗余内容。
你的任务是根据输入的视频音频信息，自动进行口播粗剪，生成一个包含剪辑结果的 JSON 对象，供后续节点使用。需要依次调用以下几个工具：
user_request，重新执行粗剪。No reviews yet. Tell others what you thought.
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Connect video clips with AI-generated transition footage. The workflow can select and arrange clips, add background music, and render a finished video through a dedicated timeline, with user confirmation before generating all transitions together.
Turn video editing preferences into a reusable skill document. It identifies patterns in pacing, sound, and visual choices, confirms the summary with the user, and saves editing instructions for an agent to follow in future work.
Organize an editing workflow for daily or travel vlogs, including footage review, clip grouping, scripts, voiceover, and music. Build a timeline and render the finished video, choosing optional steps according to the request.
Set up FireRed-OpenStoryline on a local computer, from installing Python dependencies and downloading models and assets to configuring API access, starting services, and checking that the installation works.
Run an installed OpenStoryline setup to edit local footage through conversation. Start services, submit editing requests, continue revisions in the same session, and check the generated MP4 files and their paths.
Write video narration or dialogue using the style of a reference text. Analyze its rhythm, phrasing, and emotional tone, then create a connected script and title grounded in the actual footage.