automate-this

npx skills add github/awesome-copilot --skill automate-this --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

# 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: ```bash command -v ffmpeg >/dev/null 2>&1 && ffmpeg -version 2>/dev/null | head -1 || echo "NO_FFMPEG" command -v whisper >/dev/null 2>&1 || command -v whisper-cpp >/dev/null 2>&1 || echo "NO_WHISPER" ``` - **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 cov

command -v ffmpeg >/dev/null 2>&1 && ffmpeg -version 2>/dev/null | head -1 || echo "NO_FFMPEG"
command -v whisper >/dev/null 2>&1 || command -v whisper-cpp >/dev/null 2>&1 || echo "NO_WHISPER"
chmod 700 "$WORK_DIR"
mkdir -p "$WORK_DIR/frames"
ffmpeg -y -i "<VIDEO_PATH>" -vf "fps=0.5" -q:v 2 -loglevel warning "$WORK_DIR/frames/frame_%04d.jpg"
ls "$WORK_DIR/frames/" | wc -l
ffprobe -i "<VIDEO_PATH>" -show_streams -select_streams a -loglevel error | head -5
ffmpeg -y -i "<VIDEO_PATH>" -ac 1 -ar 16000 -loglevel warning "$WORK_DIR/audio.wav"
Use whichever whisper binary is available
if command -v whisper >/dev/null 2>&1; then