3 019 media skills from 496 authors. They create and process images, video and sound. Half of them fit into 1 966 tokens or less — that is what one costs your context window when the agent loads it. 768 ship runnable scripts rather than instructions alone. 30 of them cannot work without an MCP server, most often rube. We also found 321 copies of these same skills sitting in other people's repositories — counted once here, not 321 times.
3 019 unique 496 authors 1 925 updated this month 160 from vendors
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.
Count objects in an image using the command-line interface of the object detection script.
Use ffmpeg to extract keyframes from a video file into a target directory.
Guide for generating technical exploded-view posters using Python (PIL/Pillow). Use this skill when creating engineering diagrams, hardware breakdowns, or product teardowns that require precise layer visualization, annotation leader lines, and technical accuracy. Includes methods for drawing components, layering, annotation, and exporting high-quality images.
Count specific objects in images using template matching with reference object images. Use this skill when you need to detect and count game elements, sprites, or recurring visual patterns in screenshots or game frames using a template image as reference.
Extract keyframes from MP4 video files and convert them to grayscale. Use this skill when you need to process video files for analysis by extracting I-frames (keyframes) and converting them to grayscale images for computer vision tasks.
> Generate technical exploded-view posters of hardware devices using Python Pillow. Use this skill when creating engineering diagrams, exploded-view illustrations, hardware layer breakdowns, or technical documentation posters programmatically.
Convert RGB images to grayscale using OpenCV (cv2) in Python. Use this skill when the user needs to convert color images to grayscale for image processing, template matching, or analysis.
Count occurrences of objects in images using OpenCV template matching. Use this skill when the user needs to detect and count specific objects (coins, enemies, items) in game screenshots or similar images using a reference template image.
Extract key frames (I-frames) from video files using FFmpeg. Use this skill when the user needs to pull out keyframes from MP4, MKV, AVI, or other video formats for analysis or processing.
> How to generate a technical exploded-view hardware poster as a PNG using Python (matplotlib + Pillow). Use this skill whenever the user asks for an exploded-view diagram, hardware layer diagram, technical product poster, or engineering teardown "PCB diagram", "technical poster", "engineering poster", "teardown illustration".
Convert RGB color images to grayscale and save them in-place, overriding the original files. Use this skill whenever the user asks to convert images to gray-scale, desaturate photos, or prepare images for grayscale processing pipelines using OpenCV or Pillow.
Extract key frames (I-frames) from video files using FFmpeg. Use this skill whenever the user needs to pull keyframes, thumbnails, or important frames from MP4, MKV, AVI, or other video formats. Outputs PNG image files named with zero-padded indices (e.g., keyframes_001.png).
Techniques and Python script patterns for generating technical exploded-view illustrations, including component layering, annotation leader lines, and isometric projection basics. Use this skill when generating hardware diagrams or exploded views.
Use this skill to convert RGB images to grayscale. It provides methods using common libraries like OpenCV or PIL.
Use this skill to count occurrences of a template image within a larger target image using template matching techniques.
Use this skill to extract keyframes from video files using FFmpeg. It covers selecting the right extraction frequency and naming conventions for image sequences.
Use this skill for image conversion, such as grayscale conversion, to prepare images for analysis.
Use this skill for counting specific objects (coins, enemies, turtles) in images using template matching.
Use this skill to extract key frames from MP4 video files into a target directory.
Extract key frames (I-frames) from video files using FFmpeg CLI. Use this skill whenever you need to pull out keyframes, thumbnails, or important frames from MP4, MKV, AVI, or other video formats for analysis, previews, or processing.