Video Edit Skill

Edit long videos into concise, story-driven clips by analyzing the transcript, selecting key moments, and assembling them with ffmpeg.

Workflow

Phase 1: Discover & Transcribe

Find the video — locate file, get duration/format with ffprobe

Extract audio — convert to 16kHz mono WAV for transcription:

ffmpeg -y -i INPUT -vn -acodec pcm_s16le -ar 16000 -ac 1 /tmp/audio.wav

Transcribe with Whisper — use whisper Python library (install via pip3 install openai-whisper if needed):

import whisper, json
model = whisper.load_model("base")
result = model.transcribe("/tmp/audio.wav", language="en", word_timestamps=True)
# Save full result for reference
with open("/tmp/transcript.json", "w") as f:
    json.dump(result, f)
# Print timestamped segments
for seg in result["segments"]:
    print(f'[{seg["start"]:.1f}-{seg["end"]:.1f}] {seg["text"].strip()}')

Phase 2: Analyze & Select Moments

Read the full transcript and identify the story arc. Look for:

Setup: Where the task/prompt is clearly stated
Progress beats: AI working, intermediate results appearing
Positive reactions: "wow", "that's great", "it worked", "cool", "upgraded", excitement
Key insights: Moments where approach changes or something clever happens
Resolution: Final confirmation that it worked, "thank you", wrap-up

Selection rules:

Skip duplicate/repeated prompts (e.g., if there was a reset and the same prompt was given twice, use only the second clean attempt)
Skip troubleshooting tangents, debugging, off-topic conversations, bathroom breaks, silence
Skip filler ("uh", "hmm", long pauses) — but these are fine within a selected segment
Keep segments long enough for context (15-75s each) — don't micro-cut
Aim for 10-20% of original duration as a starting point
Preserve the chronological order — never rearrange

Present the plan to the user before cutting — list each segment with timestamp range and what it captures.

Phase 3: Extract & Assemble

Extract each segment as a separate file with re-encoding for clean cuts:

ffmpeg -y -ss START -t DURATION -i INPUT \
  -c:v libx264 -preset fast -crf 23 \
  -c:a aac -b:a 128k \
  /tmp/segments/segNN.mp4

Create concat file and merge:

for f in /tmp/segments/seg*.mp4; do
  echo "file '$f'" >> /tmp/segments/filelist.txt
done
ffmpeg -y -f concat -safe 0 -i /tmp/segments/filelist.txt \
  -c:v libx264 -preset fast -crf 23 \
  -c:a aac -b:a 128k \
  OUTPUT.mp4

Verify — check duration, file size, playback.

Phase 4: Save

Save to the same directory as the source with _edited suffix, or as specified by user.

Common Mistakes & Fixes

Mistake	Fix
Including the first attempt when there was a reset/retry	Only include the clean second attempt — watch for repeated prompts
Cutting segments too short (<10s)	Keep 15-75s per segment for natural flow
Including long silences or "uh/hmm" segments	Skip segments that are mostly filler, but filler within a good segment is fine
Using `-c copy` for segment extraction	Always re-encode (`-c:v libx264`) — copy mode causes keyframe alignment issues and glitchy cuts
Forgetting `-safe 0` in concat	Required when using absolute paths in the file list
Rearranging chronological order	Never do this — the story must flow naturally in time
Over-compressing (too few segments)	The edit should still tell the complete story — don't skip important transitions
Including debugging/troubleshooting tangents	Skip unless the debugging itself is the story

What Makes a Good Edit

Tells a story: setup → progress → "wow it worked" → done
Highlights positive outcomes: reactions of surprise, satisfaction, confirmation
Shows the AI being smart: clever approaches, autonomous decisions, learning
No dead time: every second earns its place
Natural transitions: segments should feel like they flow, even with jumps
User can follow along: enough context in each segment to understand what's happening

Dependencies

ffmpeg / ffprobe (install via brew install ffmpeg)
whisper Python library (install via pip3 install openai-whisper)
Sufficient disk space for extracted audio + segments (rough guide: 2x source file size)

video-edit