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Found 70 Skills
基于 FFmpeg 的视频处理技能，提供最实用的日常视频处理命令示例
Guide for video analysis and frame-level event detection tasks using OpenCV and similar libraries. This skill should be used when detecting events in videos (jumps, movements, gestures), extracting frames, analyzing motion patterns, or implementing computer vision algorithms on video data. It provides verification strategies and helps avoid common pitfalls in video processing workflows.
Post-process raw screen recordings by removing silent segments and applying speed adjustments. Uses FFmpeg-based Python scripts to optimize video pacing automatically.
Process video files with ffmpeg automation. Use when: compressing videos for upload; extracting audio from video; resizing for social formats; clipping segments; merging multiple videos; generating thumbnails
FFmpeg automation for cutting, trimming, concatenating videos. Audio mixing, timeline editing, transitions, effects. Export optimization for YouTube, social media. Subtitle handling, color grading, batch processing. Use for videogen projects, content creation, automated video production. Activate on "video editing", "FFmpeg", "trim video", "concatenate", "transitions", "export optimization". NOT for real-time video editing UI, 3D compositing, or motion graphics.
Expert guidance for computer vision development using OpenCV, PyTorch, and modern deep learning techniques for image and video processing.
Use when the user asks to generate, remix, poll, list, download, or delete Sora videos via OpenAI’s video API using the bundled CLI (`scripts/sora.py`), including requests like “generate AI video,” “Sora,” “video remix,” “download video/thumbnail/spritesheet,” and batch video generation; requires `OPENAI_API_KEY` and Sora API access.
Route audio, video, transcript, subtitle, and edit-prep requests into the right media-understanding workflow before execution. Use this when the user wants transcription, subtitle generation, beat mapping, B-roll planning, or edit-ready outputs and the first question is which skill and model chain should run.
Read, watch, and listen to video/audio files. Extract key frames to "see" videos, extract audio to "hear" them via Whisper transcription. Use when a user sends a video/audio and asks about its content, what's in it, what someone said, etc.
Extract, transcribe, and translate YouTube video transcripts using the YouTubeTranscript.dev V2 API. Supports captions, ASR audio transcription, batch processing (up to 100 videos), translation to 100+ languages, and multiple output formats. Use when working with YouTube videos, subtitles, captions, or video-to-text conversion.
Internal utility skill for media assembly operations. NOT called directly by users. Used by producer skills (video-producer, podcast-producer, audio-producer, social-producer) to stitch, mix, and assemble final media outputs.
Video understanding for any model — native passthrough for small files, frame extraction + audio transcription fallback for large files. Use when the user asks to analyze, describe, or understand a video file (e.g. "what's in this video", "summarize this clip", "transcribe this recording").