video-analyser
SolidAnalyse a video file — primarily a screen recording of a bug — to extract errors, UI state, and reproduction steps. Resolves input from a Linear ticket URL, a local file path, or a direct video URL. Extracts keyframes with ffmpeg, runs optional Tesseract OCR and Whisper audio transcription, then delivers structured findings. Trigger phrases: "analyse this video", "analyze this recording", "what does this video show", "extract bugs from this recording", "analyse this screen recording", "investigate this mp4", "investigate this mov", "analyse this clip", "look at this screen capture", "what is happening in this video", "analyse this screen capture", "video-analyser", "/video-analyser".
Install
Quality Score: 84/100
Skill Content
Details
- Author
- mthines
- Repository
- mthines/agent-skills
- Created
- 3 months ago
- Last Updated
- 2 days ago
- Language
- TypeScript
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
video-bug-analysis
Extract frames from a screen recording or video and reason over them — to diagnose a UI/rendering bug (glitch, flicker, crash, freeze, wrong render) OR to read and inventory on-screen text/UI (catalog a site's features, transcribe a demo, describe what's shown). Use whenever the user shares a video or screen recording (.mov/.mp4/.webm) and wants it analyzed or read, especially with an approximate timestamp.
video-analysis
Understand what is actually in a video, fully locally and for free. Use this skill whenever the user wants to summarise, describe, transcribe, caption, chapter, or answer questions about a video or its audio — "what happens in this video", "summarise this screen recording", "transcribe this meeting", "what does the speaker say", "find the moment X happens", "read the text on screen", "turn this call into notes", "describe this clip for accessibility", "make chapters", "who says what". It samples timestamped frames with ffmpeg, transcribes speech with a local Whisper backend (whisper.cpp / whisperx / faster-whisper / openai-whisper), then reads the frames and transcript to answer — no cloud APIs, no keys, no per-minute cost, nothing leaves the machine. This is the understanding counterpart to ffmpeg-workbench, which transforms/encodes media (convert, compress, clip, GIF, burn subtitles). If the user wants to CHANGE a file rather than understand it, use ffmpeg-workbench instead.
analyze-video
Use when the user wants to analyze one or more videos (URLs or local files) and produce a Word document with embedded frames and a written timestamp-based analysis. Triggers on "analyze this video", "make a report from this video", "write up this YouTube link", "document what's in these videos", "analyze these clips", "video analysis", or any request that includes video URLs or local video paths and asks for a written deliverable.