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Platform-specific video ad dimensions, durations, and creative frameworks for TikTok, Instagram, YouTube, Facebook, and LinkedIn. \n \n Covers exact specs for five platforms: TikTok and Instagram (9:16 vertical), YouTube (6s bumper to skippable formats), Facebook (1:1 or 4:5 square), and LinkedIn (1:1 or 16:9) \n Includes AIDA framework (Attention, Interest, Desire, Action) with timing breakdowns and hook techniques for the critical first 3 seconds \n Provides caption requirements and safe-zone

Complete guide for scripting, producing, and assembling explainer videos via inference.sh CLI. \n \n Provides three script formulas (Problem-Agitate-Solve, Before-After-Bridge, Feature Spotlight) with timing breakdowns, word counts, and pacing rules for 30–120 second videos \n Covers scene generation via video AI models, voiceover production with TTS, music ducking, and caption integration through a multi-step assembly pipeline \n Includes practical tables for pacing (120–170 wpm by content type

Perception + memory + actions for video, live streams, and desktop sessions.

使用字节跳动 Seedance-1.5-pro 模型 (doubao-seedance-1-5-pro-251215) 根据文本或图片生成视频。

Orchestrates video generation across three engines, selecting the best one based on requirements and available resources.

Core Remotion knowledge lives in .claude/skills/remotion-official/ (synced from the official remotion-dev/skills repo). This file covers toolkit-specific patterns only.

This skill provides guidance for video processing tasks involving frame-level analysis, event detection, and motion tracking using computer vision libraries like OpenCV. It emphasizes verification-first approaches and guards against common pitfalls in video analysis workflows.

Generate talking head and avatar videos from images and audio using OmniHuman, Fabric, and PixVerse models. \n \n Four model options: OmniHuman 1.5 (multi-character), OmniHuman 1.0 (single character), Fabric 1.0 (image lipsync), and PixVerse Lipsync (highly realistic) \n Audio-driven workflow: pair portrait images with speech files to generate realistic avatar videos with synchronized lip movement \n Composable with text-to-speech and video transcription for end-to-end pipelines: generate speech

Create AI avatar videos with full control over avatars, voices, scripts, and backgrounds using POST /v3/videos. Two creation modes via discriminated union on type:

Convert React/Remotion component code directly to MP4 videos via CLI. \n \n Accepts TSX code with full Remotion API support: useCurrentFrame , useVideoConfig , spring , interpolate , AbsoluteFill , Sequence , and media components \n Configurable output: resolution, FPS, duration, codec, and component props passed as JSON \n Supports streaming progress updates and Python SDK integration for programmatic video generation \n Ideal for animated graphics, motion design, data-driven videos, and React