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:

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 coverage with context window limits.

WORK_DIR=$(mktemp -d "${TMPDIR:-/tmp}/automate-this-XXXXXX")
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

Use $WORK_DIR 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: