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Content Creation #python #image #ai #web

image-processing

Process images for web development — resize, crop, trim whitespace, convert formats (PNG/WebP/JPG), optimise file size, generate thumbnails, create OG card images. Uses Pillow (Python) — no ImageMagick needed. Trigger with 'resize image', 'convert to webp', 'trim logo', 'optimise images', 'make thumbnail', 'create OG image', 'crop whitespace', 'process image', or 'image too large'.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name image-processing description Process images for web development — resize, crop, trim whitespace, convert formats (PNG/WebP/JPG), optimise file size, generate thumbnails, create OG card images. Uses Pillow (Python) — no ImageMagick needed. Trigger with 'resize image', 'convert to webp', 'trim logo', 'optimise images', 'make thumbnail', 'create OG image', 'crop whitespace', 'process image', or 'image too large'. compatibility claude-code-only Image Processing Use img-process (shipped in bin/ ) for common operations. For complex or custom workflows, generate a Pillow script adapted to the user's environment. Quick Reference — img-process CLI img-process resize hero.png --width 1920 img-process convert logo.png --format webp img-process trim logo-raw.jpg -o logo-clean.png --padding 10 img-process thumbnail photo.jpg --size 200 img-process optimise hero.jpg --quality 85 --max-width 1920 img-process og-card -o og.png --title "My App" --subtitle "Built for speed" img-process batch ./images --action convert --format webp -o ./optimised Use img-process when : the operation is standard (resize, convert, trim, thumbnail, optimise, OG card, batch). This is faster and avoids generating a script each time. Generate a custom script when : the operation needs logic img-process doesn't cover (compositing multiple images, watermarks, complex text layouts, conditional processing). Prerequisites Pillow is required for both img-process and custom scripts: pip install Pillow If Pillow is unavailable, use alternatives: Alternative Platform Install Best for sips macOS (built-in) None Resize, convert (no trim/OG) sharp Node.js npm install sharp Full feature set, high performance ffmpeg Cross-platform brew install ffmpeg Resize, convert Output Format Guide Use case Format Why Photos, hero images WebP Best compression, wide browser support Logos, icons (need transparency) PNG Lossless, supports alpha Fallback for older browsers JPG Universal support Thumbnails WebP or JPG Small file size priority OG cards PNG Social platforms handle PNG best Core Patterns Save with Format-Specific Quality Different formats need different save parameters. Always handle RGBA-to-JPG compositing — JPG does not support transparency, so composite onto a white background first. from PIL import Image import os def save_image ( img, output_path, quality= None ): os.makedirs(os.path.dirname(output_path) or "." , exist_ok= True ) kwargs = {} ext = output_path.lower().rsplit( "." , 1 )[- 1 ] if ext == "webp" : kwargs = { "quality" : quality or 85 , "method" : 6 } elif ext in ( "jpg" , "jpeg" ): kwargs = { "quality" : quality or 90 , "optimize" : True } # RGBA → RGB: composite onto white background if img.mode == "RGBA" : bg = Image.new( "RGB" , img.size, ( 255 , 255 , 255 )) bg.paste(img, mask=img.split()[ 3 ]) img = bg elif ext == "png" : kwargs = { "optimize" : True } img.save(output_path, **kwargs) Resize with Aspect Ratio When only width or height is given, calculate the other from aspect ratio. Use Image.LANCZOS for high-quality downscaling. def resize_image ( img, width= None , height= None ): if width and height: return img.resize((width, height), Image.LANCZOS) elif width: ratio = width / img.width return img.resize((width, int (img.height * ratio)), Image.LANCZOS) elif height: ratio = height / img.height return img.resize(( int (img.width * ratio), height), Image.LANCZOS) return img Trim Whitespace (Auto-Crop) Remove surrounding whitespace from logos and icons. Convert to RGBA first, then use getbbox() to find content bounds. img = Image. open (input_path) if img.mode != "RGBA" : img = img.convert( "RGBA" ) bbox = img.getbbox() # Bounding box of non-zero pixels if bbox: img = img.crop(bbox) Thumbnail Fit within max dimensions while maintaining aspect ratio: img.thumbnail((size, size), Image.LANCZOS) Optimise for Web Resize + compress in one step. Convert to WebP for best compression. Typical settings: width 1920, quality 85. Cross-Platform Font Discovery System font paths differ by OS. Try multiple paths, fall back to Pillow's default. On Linux, fc-list can discover fonts dynamically. from PIL import ImageFont def get_font ( size ): font_paths = [ # macOS "/System/Library/Fonts/Helvetica.ttc" , "/System/Library/Fonts/SFNSText.ttf" , # Linux "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf" , "/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf" , # Windows "C:/Windows/Fonts/arial.ttf" , ] for path in font_paths: if os.path.exists(path): try : return ImageFont.truetype(path, size) except Exception: continue return ImageFont.load_default() OG Card Generation (1200x630) Composite text on a background image or solid colour. Apply semi-transparent overlay for text readability. Centre text horizontally. from PIL import Image, ImageDraw, ImageFont width, height = 1200 , 630 # Background: image or solid colour if background_path: img = Image. open (background_path).resize((width, height), Image.LANCZOS) else : img = Image.new( "RGB" , (width, height), bg_color or "#1a1a2e" ) # Semi-transparent overlay for text readability overlay = Image.new( "RGBA" , (width, height), ( 0 , 0 , 0 , 128 )) img = img.convert( "RGBA" ) img = Image.alpha_composite(img, overlay) draw = ImageDraw.Draw(img) font_title = get_font( 48 ) font_sub = get_font( 24 ) # Centre title if title: bbox = draw.textbbox(( 0 , 0 ), title, font=font_title) tw = bbox[ 2 ] - bbox[ 0 ] draw.text(((width - tw) // 2 , height // 2 - 60 ), title, fill= "white" , font=font_title) img = img.convert( "RGB" ) Common Workflows Logo Cleanup (client-supplied JPG with white background) img-process trim logo-raw.jpg -o logo-trimmed.png --padding 10 img-process thumbnail logo-trimmed.png --size 512 -o favicon-512.png Prepare Hero Image for Production img-process optimise hero.jpg --max-width 1920 --quality 85 # Outputs hero.webp — resized and compressed Batch Process img-process batch ./raw-images --action convert --format webp --quality 85 -o ./optimised img-process batch ./photos --action resize --width 800 -o ./thumbnails Pipeline with Gemini Image Gen Generate images with the gemini-image-gen skill, then process them: # After generating with Gemini (raw PNG output): img-process optimise generated-image.png --max-width 1920 --quality 85 # Or batch process all generated images: img-process batch ./generated --action optimise -o ./production
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
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exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
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