Agent skill · operations · github
automate-this
Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.
Why this skill is useful
Adds complex automation scripts that analyze video recordings and generate tailored automation workflows, which the AI cannot generate from existing knowledge alone.
What it needs
Requires ffmpeg, whisper installed locally. About 8k tokens when loaded. Last updated 2026-08-07. 37,534 stars on the source repository.
What this skill does
Automate This Analyze a screen recording of a manual process and build working automation for it. The user records themselves doing something repetitive or tedious, hands you the video file, and you figure out what they're doing, why, and how to script it away. Prerequisites Check Before analyzing any recording, verify the required tools are available. Run these checks silently and only surface problems: ffmpeg is required. If missing, tell the user: brew install ffmpeg (macOS) or the equivalent for their OS. Whisper is optional. Only needed if the recording has narration. If missing AND the recording has an audio track, suggest: pip install openai-whisper or brew install whisper-cpp. If the user declines, proceed with visual analysis only. Phase 1: Extract Content from the Recording Given a video file path (typically on ~/Desktop/), extract both visual frames and audio: Frame Extraction Extract frames at one frame every 2 seconds. This balances coverage with context window limits. Use $WORKDIR for all subsequent temp file paths in the session. The per-run directory with mode 0700 ensures extracted frames are only readable by the current user. If the recording is longer than 5 minutes (more than 150 frames), increase the interval to one frame every 4 seconds to stay within context limits. Tell the user you're sampling less frequently for longer recordings. Audio Extraction and Transcription Check if the video has an audio track: If audio exists: If neither whisper binary is available and the recording has audio, inform the user they're missing narration context and ask if they want to install Whisper (pip install openai-whisper or brew install whisper-cpp) or proceed with visual-only analysis. Phase 2: Reconstruct the Process Analyze the extracted frames (and transcript, if available) to build a structured understanding of what the user did. Work through the frames sequentially and identify: 1. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills github/automate-this