extract-illustrations

name: extract-illustrations description: Extract frames from video around a timestamp, verify content matches expected description, crop browser chrome, and save as illustration. Use when creating article illustrations from video content.

Extract Illustration from Video

Extract keyframes around a timestamp, verify each one, select the best match, crop if needed, and save as JPEG. Falls back to step-based extraction if keyframes don't yield matches.

Required Arguments

When using this skill, you need:

• video - Path to video file
• timestamp - Timestamp in MM:SS or HH:MM:SS format (estimated)
• name - Illustration name (for filename: name.jpg)
• description - What content we're looking for (for verification)
• context - Article text around the illustration

Process

1. Try keyframes first (natural scene changes)

Extract I-frames from ±10 seconds around the target timestamp:

mkdir -p "_temp/frames/$name" _temp/illustrations

cd "$(dirname "$video")" && ffmpeg -ss $timestamp -i "$(basename "$video")" \
  -ss -00:00:10 -t 00:00:20 \
  -vf "select=eq(pict_type\,I)" -vsync 0 \
  "C:/Users/alexe/git/notes/_temp/frames/$name/keyframe_%{pts:hms}.png" -y 2>&1 | tail -3

Check if keyframes were extracted:

ls "_temp/frames/$name/" | wc -l

1b. Remove duplicate keyframes by file size

python .claude/skills/extract-illustrations/scripts/dedup_by_size.py "_temp/frames/$name"

2. Verify keyframes (content match)

Starting with the keyframe closest to the target timestamp, use analyze_image:

We expect: $description
Context: $context

What does this image actually show? Does it match what we expect?

3. Select best match

• If frame matches: Proceed to step 4.
• If frame doesn't match: Check the next closest keyframe.
• If NO keyframes match after checking all candidates: Go to step 3b (fallback).

3b. Fallback: Extract frames at 1-second intervals

If keyframes didn't yield a match, extract specific frames:

cd "$(dirname "$video")" && for offset in -5 -4 -3 -2 -1 0 1 2 3 4 5; do
  ffmpeg -ss $timestamp -i "$(basename "$video")" -ss "00:00:$offset" -vframes 1 \
    "C:/Users/alexe/git/notes/_temp/frames/$name/frame_${offset}.png" -y 2>&1 | tail -1
done

Then verify each frame starting from offset 0.

4. Remove visually similar frames (optional)

If many frames remain, use the deduplication script:

python .claude/skills/extract-illustrations/scripts/dedup_frames.py "_temp/frames/$name"

5. Assess cropping needs

Now that a matching frame is found, use analyze_image to determine crop dimensions:

Please assess cropping needs for this image:
1. Is there browser chrome at the top? If yes, exactly how many pixels should be removed?
2. Are there sidebars on left/right edges? If yes, exactly how many pixels to crop from each side?
3. What are the original image dimensions?

Provide the final crop dimensions in the format: widthxheight+x+y

6. Crop and save

Use the dimensions from analyze_image:

# Example: analyze_image reports crop dimensions "1180x630+50+90"
convert "_temp/frames/$name/best_frame.png" -crop {width}x{height}+{x}+{y} +repage "_temp/illustrations/$name.jpg"

7. Cleanup

rm -rf "_temp/frames/$name"

Output

Saved to: _temp/illustrations/$name.jpg

Selection Guidelines

Example

video=C:/Users/alexe/Downloads/video.mp4
timestamp=00:24:44
name=leaderboard
description="leaderboard showing student points for homework"
context="The Leaderboard gamified element where students earn points"

Scripts

• scripts/dedup_frames.py - Remove visually similar frames based on pixel difference