Build a deliberate final-image pipeline for advanced Three.js scenes. Use for depth, normal, albedo, and history ownership; GTAO or bent normals; bloom; eye adaptation; tone mapping; 3D LUT grading; effect-local render targets; and pass diagnostics.
npx skills add https://github.com/scottstts/Threejs-Awesome-Graphics-Agent-Skills --skill threejs-image-pipeline
Use this skill only when composing several image-space systems or defining shared buffers. For one effect, load its atomic skill instead.
Load:
$threejs-screen-space-ambient-occlusion for GTAO, bent normals, denoising, or AO application;$threejs-bloom for HDR extraction and bloom;$threejs-exposure-color-grading for metering, adaptation, tone mapping, LUTs, and output conversion.The pipeline must expose its signals and ordering. Do not install a pile of effects and tune the final frame blindly.
scene HDR color + depth + normals + albedo where required
→ lighting-related screen effects
→ atmosphere/transparency composition
→ bloom
→ exposure
→ tone mapping
→ grading
→ lens/presentation effects
→ output conversion
Read references/production-image-pipeline.md
for four production pass graphs, their buffer/resolution contracts, and the
ownership boundaries between whole-scene and effect-local graphs.
Use this skill when multiple image-space systems must share buffers, ordering,
or output ownership. For one isolated effect, use its atomic skill without
loading this coordinator.
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take scottstts/threejs-image-pipeline from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.