# Send Image Utils by Bria.ai to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "image-utils", "name": "Image Utils by Bria.ai", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/galbria/image-utils", "canonicalUrl": "https://clawhub.ai/galbria/image-utils", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/image-utils", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=image-utils", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "references/code-examples/image_utils.py" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "image-utils", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-04T07:53:21.141Z", "expiresAt": "2026-05-11T07:53:21.141Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=image-utils", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=image-utils", "contentDisposition": "attachment; filename=\"image-utils-1.3.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "image-utils" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/image-utils" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/image-utils", "downloadUrl": "https://openagent3.xyz/downloads/image-utils", "agentUrl": "https://openagent3.xyz/skills/image-utils/agent", "manifestUrl": "https://openagent3.xyz/skills/image-utils/agent.json", "briefUrl": "https://openagent3.xyz/skills/image-utils/agent.md" } } ``` ## Documentation ### Image Utilities Pillow-based utilities for deterministic pixel-level image operations. Use for resize, crop, composite, format conversion, watermarks, and other standard image processing tasks. ### When to Use This Skill Post-processing AI-generated images: Resize, crop, optimize for web after generation Format conversion: PNG ↔ JPEG ↔ WEBP with quality control Compositing: Overlay images, paste subjects onto backgrounds Batch processing: Resize to multiple sizes, add watermarks Web optimization: Compress and resize for fast delivery Social media preparation: Crop to platform-specific aspect ratios ### Quick Reference OperationMethodDescriptionLoadingload(source)Load from URL, path, bytes, or base64load_from_url(url)Download image from URLSavingsave(image, path)Save with format auto-detectionto_bytes(image, format)Convert to bytesto_base64(image, format)Convert to base64 stringResizingresize(image, width, height)Resize to exact dimensionsscale(image, factor)Scale by factor (0.5 = half)thumbnail(image, size)Fit within size, maintain aspectCroppingcrop(image, left, top, right, bottom)Crop to regioncrop_center(image, width, height)Crop from centercrop_to_aspect(image, ratio)Crop to aspect ratioCompositingpaste(bg, fg, position)Overlay at coordinatescomposite(bg, fg, mask)Alpha compositefit_to_canvas(image, w, h)Fit onto canvas sizeBordersadd_border(image, width, color)Add solid borderadd_padding(image, padding)Add whitespace paddingTransformsrotate(image, angle)Rotate by degreesflip_horizontal(image)Mirror horizontallyflip_vertical(image)Flip verticallyWatermarksadd_text_watermark(image, text)Add text overlayadd_image_watermark(image, logo)Add logo watermarkAdjustmentsadjust_brightness(image, factor)Lighten/darkenadjust_contrast(image, factor)Adjust contrastadjust_saturation(image, factor)Adjust color saturationblur(image, radius)Apply Gaussian blurWeboptimize_for_web(image, max_size)Optimize for deliveryInfoget_info(image)Get dimensions, format, mode ### Requirements pip install Pillow requests ### Basic Usage from image_utils import ImageUtils # Load from URL image = ImageUtils.load_from_url("https://example.com/image.jpg") # Or load from various sources image = ImageUtils.load("/path/to/image.png") # File path image = ImageUtils.load(image_bytes) # Bytes image = ImageUtils.load("data:image/png;base64,...") # Base64 # Resize and save resized = ImageUtils.resize(image, width=800, height=600) ImageUtils.save(resized, "output.webp", quality=90) # Get image info info = ImageUtils.get_info(image) print(f"{info['width']}x{info['height']} {info['mode']}") ### Resizing & Scaling # Resize to exact dimensions resized = ImageUtils.resize(image, width=800, height=600) # Resize maintaining aspect ratio (fit within bounds) fitted = ImageUtils.resize(image, width=800, height=600, maintain_aspect=True) # Resize by width only (height auto-calculated) resized = ImageUtils.resize(image, width=800) # Scale by factor half = ImageUtils.scale(image, 0.5) # 50% size double = ImageUtils.scale(image, 2.0) # 200% size # Create thumbnail thumb = ImageUtils.thumbnail(image, (150, 150)) ### Cropping # Crop to specific region cropped = ImageUtils.crop(image, left=100, top=50, right=500, bottom=350) # Crop from center center = ImageUtils.crop_center(image, width=400, height=400) # Crop to aspect ratio (for social media) square = ImageUtils.crop_to_aspect(image, "1:1") # Instagram wide = ImageUtils.crop_to_aspect(image, "16:9") # YouTube thumbnail story = ImageUtils.crop_to_aspect(image, "9:16") # Stories/Reels # Control crop anchor top_crop = ImageUtils.crop_to_aspect(image, "16:9", anchor="top") bottom_crop = ImageUtils.crop_to_aspect(image, "16:9", anchor="bottom") ### Compositing # Paste foreground onto background result = ImageUtils.paste(background, foreground, position=(100, 50)) # Alpha composite (foreground must have transparency) result = ImageUtils.composite(background, foreground) # Fit image onto canvas with letterboxing canvas = ImageUtils.fit_to_canvas( image, width=1200, height=800, background_color=(255, 255, 255, 255), # White position="center" # or "top", "bottom" ) ### Format Conversion # Convert to different formats png_bytes = ImageUtils.to_bytes(image, "PNG") jpeg_bytes = ImageUtils.to_bytes(image, "JPEG", quality=85) webp_bytes = ImageUtils.to_bytes(image, "WEBP", quality=90) # Get base64 for data URLs base64_str = ImageUtils.to_base64(image, "PNG") data_url = ImageUtils.to_base64(image, "PNG", include_data_url=True) # Returns: "data:image/png;base64,..." # Save with format auto-detected from extension ImageUtils.save(image, "output.png") ImageUtils.save(image, "output.jpg", quality=85) ImageUtils.save(image, "output.webp", quality=90) ### Watermarks # Text watermark watermarked = ImageUtils.add_text_watermark( image, text="© 2024 My Company", position="bottom-right", # bottom-left, top-right, top-left, center font_size=24, color=(255, 255, 255, 128), # Semi-transparent white margin=20 ) # Logo/image watermark logo = ImageUtils.load("logo.png") watermarked = ImageUtils.add_image_watermark( image, watermark=logo, position="bottom-right", opacity=0.5, scale=0.15, # 15% of image width margin=20 ) ### Adjustments # Brightness (1.0 = original, <1 darker, >1 lighter) bright = ImageUtils.adjust_brightness(image, 1.3) dark = ImageUtils.adjust_brightness(image, 0.7) # Contrast (1.0 = original) high_contrast = ImageUtils.adjust_contrast(image, 1.5) # Saturation (0 = grayscale, 1.0 = original, >1 more vivid) vivid = ImageUtils.adjust_saturation(image, 1.3) grayscale = ImageUtils.adjust_saturation(image, 0) # Sharpness sharp = ImageUtils.adjust_sharpness(image, 2.0) # Blur blurred = ImageUtils.blur(image, radius=5) ### Transforms # Rotate (counter-clockwise, degrees) rotated = ImageUtils.rotate(image, 45) rotated = ImageUtils.rotate(image, 90, expand=False) # Don't expand canvas # Flip mirrored = ImageUtils.flip_horizontal(image) flipped = ImageUtils.flip_vertical(image) ### Borders & Padding # Add solid border bordered = ImageUtils.add_border(image, width=5, color=(0, 0, 0)) # Add padding (whitespace) padded = ImageUtils.add_padding(image, padding=20) # Uniform padded = ImageUtils.add_padding(image, padding=(10, 20, 10, 20)) # left, top, right, bottom ### Web Optimization # Optimize for web delivery optimized_bytes = ImageUtils.optimize_for_web( image, max_dimension=1920, # Resize if larger format="WEBP", # Best compression quality=85 ) # Save optimized with open("optimized.webp", "wb") as f: f.write(optimized_bytes) ### Integration with AI Image Generation Use with Bria AI or other image generation APIs: from bria_client import BriaClient from image_utils import ImageUtils client = BriaClient() # Generate with AI result = client.generate("product photo of headphones", aspect_ratio="1:1") image_url = result['result']['image_url'] # Download and post-process image = ImageUtils.load_from_url(image_url) # Create multiple sizes for responsive images sizes = { "large": ImageUtils.resize(image, width=1200), "medium": ImageUtils.resize(image, width=600), "thumb": ImageUtils.thumbnail(image, (150, 150)) } # Save all as optimized WebP for name, img in sizes.items(): ImageUtils.save(img, f"product_{name}.webp", quality=85) ### Batch Processing Example from pathlib import Path from image_utils import ImageUtils def process_catalog(input_dir, output_dir): """Process all images in a directory.""" output_path = Path(output_dir) output_path.mkdir(exist_ok=True) for image_file in Path(input_dir).glob("*.{jpg,png,webp}"): image = ImageUtils.load(image_file) # Crop to square square = ImageUtils.crop_to_aspect(image, "1:1") # Resize to standard size resized = ImageUtils.resize(square, width=800, height=800) # Add watermark final = ImageUtils.add_text_watermark(resized, "© My Brand") # Save optimized output_file = output_path / f"{image_file.stem}.webp" ImageUtils.save(final, output_file, quality=85) process_catalog("./raw_images", "./processed") ### API Reference See image_utils.py for complete implementation with docstrings. ## Trust - Source: tencent - Verification: Indexed source record - Publisher: galbria - Version: 1.2.3 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-04T07:53:21.141Z - Expires at: 2026-05-11T07:53:21.141Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/image-utils) - [Send to Agent page](https://openagent3.xyz/skills/image-utils/agent) - [JSON manifest](https://openagent3.xyz/skills/image-utils/agent.json) - [Markdown brief](https://openagent3.xyz/skills/image-utils/agent.md) - [Download page](https://openagent3.xyz/downloads/image-utils)