Product Reel Generator

You are a video production skill that takes an e-commerce product page URL and produces an Instagram-ready reel. The reel features AI-animated model clips (or Ken Burns product showcases), text overlays, and background music.

Requirements

• FFmpeg installed and available in PATH (brew install ffmpeg on macOS, apt install ffmpeg on Linux)
• Python 3 with Pillow and python-dotenv packages (pip install Pillow python-dotenv)
• Higgsfield API credentials — HIGGSFIELD_API_KEY_ID and HIGGSFIELD_API_KEY_SECRET in a .env file (project root or any parent directory)

Before starting: Verify dependencies are available. If FFmpeg or Python packages are missing, instruct the user to install them before proceeding.

Input

The user provides:

1. Product page URL (required) — any e-commerce product page (Shopify, Zara, DaMENSCH, etc.)
2. Music file (optional) — path to an MP3. If not provided, use a royalty-free track.
3. Style preset (optional) — one of: minimal, luxury, bold, editorial, clean. Defaults to auto-detect based on brand.
4. Brand name (optional) — for watermark. If not provided, extract from the page.

Pipeline

Step 1: Scrape Product Images

Try these methods in order until one works:

1. Shopify JSON — append .json to the product URL and extract images from the response
2. HTML scraping with referrer — curl with -H "Referer: <site-domain>" and a browser user-agent
3. Chrome DevTools — navigate to page, extract image URLs via JavaScript, download

For each image, download at the highest available resolution.

Step 2: Classify Images (Heuristic)

Use image position on the product page as the primary signal:

Model detection heuristic: If image height > 1.5× width AND file size > 100KB → likely a model photo → use AI animation pipeline. Otherwise → product-only → use Ken Burns pipeline.

Step 3: Generate AI Video Clips

Use the Higgsfield API via this skill's scripts/higgsfield_video.py script or direct curl calls.

API details:

• Base URL: https://platform.higgsfield.ai
• Auth header: Authorization: Key {HIGGSFIELD_API_KEY_ID}:{HIGGSFIELD_API_KEY_SECRET}
• Always set "aspect_ratio": "9:16" for Instagram Reels

Model selection:

• Seedance (bytedance/seedance/v1/pro/image-to-video) — for hero/walk scenes. Higher quality, ~45 credits. Use for the most important clip.
• Kling (kling-video/v2.1/pro/image-to-video) — for secondary scenes. Good quality, ~6 credits. Use for turns, side angles.

Prompt guidelines:

• Always mention the clothing color and type in the prompt
• Specify direction of motion ("walks forward", "turns from front to side")
• Add "clean studio background" or describe the actual background
• Add "smooth cinematic motion" at the end
• For walk prompts, add "does not stop or turn around" to prevent reversal

Duration: Use "duration": 5 for each clip. Kling only supports 5 or 10.

Polling: After submission, poll GET /requests/{request_id}/status every 15 seconds until status: "completed". Then download the video from response.video.url.

Step 4: Create Ken Burns Scenes

For detail/texture shots where AI animation adds no value, use FFmpeg Ken Burns:

ffmpeg -y -loop 1 -i "detail.jpg" \
  -vf "scale=2160:3840,zoompan=z='1+0.06*in/75':x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)':d=75:s=1080x1920:fps=25" \
  -t 3 -c:v libx264 -pix_fmt yuv420p -r 25 "scene-detail.mp4"

Vary the zoom type: zoom-in, zoom-out, pan-left, pan-right, pan-up, pan-down.

Step 5: Create Text Overlays

Use Python Pillow to generate transparent PNG overlays, then composite with FFmpeg.

IMPORTANT: Many FFmpeg installations do NOT have the drawtext filter. Always use Pillow to create PNG text images, then overlay with:

ffmpeg -y -i video.mp4 -loop 1 -t <duration> -i overlay.png \
  -filter_complex "[1:v]format=rgba[txt];[0:v][txt]overlay=0:0" \
  -t <duration> -c:v libx264 -pix_fmt yuv420p -r 25 output.mp4

Style Presets

Fonts are provided as shared files in the pack's fonts/ directory (copied into each skill on install). Fall back to system fonts if custom fonts are not found.

Overlays to create:

1. Brand watermark — small text, top-right corner, persistent on all video scenes
2. Product info card — product name, price, CTA ("Shop now → website"), placed on the final scene with gradient background

Step 6: Compose the Reel

Model Reel Structure (when model photos detected)

Target: 80% video, 20% static. The product card at the end is fine as static.

If a generated AI clip looks bad (distortion, wrong face, backward motion), replace with Ken Burns from the same source image.

Product-Only Reel Structure (no model photos)

Stitching

Concatenate all scenes with FFmpeg:

cat > concat.txt << EOF
file 'scene1.mp4'
file 'scene2.mp4'
...
EOF
ffmpeg -y -f concat -safe 0 -i concat.txt -c:v libx264 -pix_fmt yuv420p -r 25 reel-silent.mp4

Step 7: Add Audio

Mix background music with the silent reel:

ffmpeg -y -i reel-silent.mp4 -i music.mp3 \
  -filter_complex "[1:a]atrim=<start>:<end>,asetpts=PTS-STARTPTS,afade=t=in:st=0:d=1.5,afade=t=out:st=<fade_start>:d=2,volume=0.5[aud]" \
  -map 0:v -map "[aud]" -c:v copy -c:a aac -shortest output.mp4

If no music file is provided, ask the user to supply one or search for a royalty-free track (e.g., Kevin MacLeod's library at incompetech.com). The user should provide a local file path or URL.

Output

Save the final reel to a user-specified directory (or the current working directory).

Output specs:

• Format: MP4 (H.264)
• Resolution: 1080×1920 (9:16 portrait)
• Frame rate: 25fps
• Duration: 15-20 seconds
• Audio: AAC

Known Limitations

1. Multi-clip cohesion — independently generated AI clips may have slightly different faces or clothing details. Mitigate by using different source images (not same image with different prompts) and keeping clips short (3-5s each).
2. AI motion reversal — Kling sometimes reverses motion (walk forward then