Media Claude Skills
3 032 media skills from 496 authors. They create and process images, video and sound. Half of them fit into 1 962 tokens or less — that is what one costs your context window when the agent loads it. 771 ship runnable scripts rather than instructions alone. 30 of them cannot work without an MCP server, most often rube. We also found 347 copies of these same skills sitting in other people's repositories — counted once here, not 347 times.
3 032 unique 496 authors 13 updated this month 173 from vendors
Count occurrences of a template object in an image using OpenCV template matching with non-maximum suppression.
Techniques for drawing isometric or orthographic exploded-view hardware diagrams programmatically using Pillow, with annotation leader lines and layer separation.
Create technical poster and diagram images using Pillow (PIL), including shapes, text, lines, and layered composition.
Extract I-frame keyframes from video files using FFmpeg command line, saving them as numbered PNG images.
Count occurrences of an object in an image using OpenCV template matching (cv2.matchTemplate). Use this skill whenever the user needs to detect and count how many times a small reference image (template) appears in a larger image, such as counting coins, enemies, or other game sprites. Works on both grayscale and color images.
Convert images to grayscale in-place using Pillow (PIL), overwriting original RGB files.
Technical image generation using Python's Pillow library. Use this when you need to programmatically create diagrams, posters, or technical drawings.
Techniques for image preprocessing and template matching to count objects in images.
Tools and techniques for extracting keyframes and processing video files using FFmpeg.
Guidelines for applying strict brand color palettes and minimalist technical design standards to generated imagery.
Use ffmpeg to extract key frames (I-frames) from a video file into a directory.
Use ImageMagick to convert an image to grayscale inplace.
Detect and count occurrences of template images within a larger target image.
Convert images to grayscale in-place.
Extract key frames (I-frames) from video files using FFmpeg.
Compute and aggregate F1 score and delta from clustering evaluation across images
Advanced OpenCV template matching with dynamic threshold tuning, robust NMS filtering, and multi-scale detection for object counting in images.
Robust FFmpeg video frame extraction with error handling, alternative methods, and comprehensive frame selection strategies.
Robust image processing with format conversion, in-place modification, and comprehensive verification of image properties.
Extract I-frame keyframes from video files using FFmpeg, with output verification and naming conventions.
Convert images to grayscale in-place using OpenCV, including both keyframes and template images.
Extract I-frame keyframes from video files using FFmpeg CLI, saving as zero-padded PNG sequences starting at 001.
Convert PNG images to grayscale inplace using ImageMagick; covers both keyframes and template images for consistent matching.
A skill for advanced technical illustration with Pillow, including complex hardware shapes, cooling fins, and annotation shelf-lines.
A skill for managing and applying Anthropic's specific brand identity, including color tokens, typography fallbacks, and technical illustration standards.
Advanced FFmpeg techniques for keyframe extraction with quality control.
Efficient inplace image processing using ImageMagick's mogrify.
Enhanced skill for programmatic design, incorporating system-level dependency management for image generation libraries.
Performs image format conversion and color space modification using ImageMagick tools.
Counts object occurrences in an image using OpenCV template matching with non-maximum suppression.
Extracts all key frames from a video file into a specified output directory using FFmpeg.
Extract key frames (I-frames) from a video file into a sequence of images using FFmpeg.
Convert a batch of images to grayscale in-place using ImageMagick's mogrify command.
Count the number of object occurrences in an image using OpenCV template matching in Python.
Implement DBSCAN clustering with a custom weighted Euclidean distance metric controlled by shape_weight parameter. Use this skill to cluster citizen science point annotations on Mars cloud images.
Load citizen science and expert annotation datasets, match them by image using file_rad column, handle missing data, and prepare data for clustering evaluation.
Execute grid search over DBSCAN hyperparameters, evaluate each combination across all images, filter by F1 threshold, and identify Pareto-optimal solutions balancing F1 score and delta metric.
Converts an MP4 video file into individual keyframe PNG images. Use this to decompose a video into analyzable still frames. Extracts one keyframe per scene and stores them in the root directory with sequential naming.
Use this skill to convert extracted keyframe PNG images to grayscale in-place using Python3 and PIL/Pillow. Only convert keyframe images, NOT template images (coin.png, enemy.png, turtle.png).
Use this skill to count coins, enemies, and turtles in grayscale keyframe images using OpenCV template matching with a provided count_objects.py script. Includes robust output parsing and fallback to direct template matching if the script is unavailable.
Use this skill to extract keyframes (I-frames) from an MP4 video file using ffmpeg. This produces numbered PNG files in a specified output directory.
Convert all extracted keyframe PNG images from RGB to grayscale inplace, overwriting the original files. Also convert template images (coin.png, enemy.png, turtle.png) to grayscale. Use this before running object counting.
Extract key frames from an MP4 video file and save them as PNG images in a target directory. Use this skill when you need to convert a video into individual frame images for further analysis.
Organizing annotation data by image identifiers to prepare for image-by-image clustering analysis.
Converts all extracted keyframe images in a directory from RGB to grayscale and overwrites the original files.
Converts a video file into a series of keyframe images using FFmpeg with specific frame selection filters.
Provides the workflow for creating minimalist, low-saturation technical illustrations using the Nova device as a template.
Convert images to grayscale in-place using OpenCV.