Docker

hugging-face-jobs

huggingface

This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.

fal-generate

fal-ai-community

Generate images and videos using fal.ai AI models with queue support. Use when the user requests "Generate image", "Create video", "Make a picture of...", "Text to image", "Image to video", "Search models", or similar generation tasks.

Architecture

HoangNguyen0403

Standards for Angular project structure, feature modules, and lazy loading.

Android Jetpack Compose

HoangNguyen0403

Standards for high-performance Declarative UI and State Hoisting.

Directives & Pipes

HoangNguyen0403

Composition patterns using HostDirectives and Pure Pipes.

omero-integration

jaechang-hits

"OMERO is an open-source platform for biological image data management. Use the omero-py Python client to connect to an OMERO server, search and retrieve images as numpy arrays, annotate images with tags and key-value pairs, manage ROIs, and integrate OMERO image data into downstream analysis pipelines — all programmatically without the OMERO desktop GUI."

cellpose-cell-segmentation

jaechang-hits

"Deep learning cell and nucleus segmentation from fluorescence and brightfield microscopy images. Uses pre-trained models (cyto3, nuclei, tissuenet) and a generalist flow-based algorithm that segments cells without requiring retraining on new image types. Outputs label masks for downstream morphology measurement and tracking. Use scikit-image watershed for rule-based segmentation; use Cellpose when deep learning generalization across staining conditions is needed."

pyimagej-fiji-bridge

jaechang-hits

"Python bridge to ImageJ2/Fiji enabling macro execution, plugin calls (Bio-Formats, TrackMate, Analyze Particles), bidirectional NumPy↔ImagePlus/ImgLib2 data exchange, and ImageJ Ops from Python. Use for automating Fiji-specific workflows headlessly from Python scripts. Use scikit-image instead for pure Python pipelines that do not require Fiji plugins; use napari for interactive visualization."

napari-image-viewer

jaechang-hits

"Interactive multi-dimensional image viewer for scientific microscopy data. Napari displays 2D/3D/4D arrays as Image, Labels, Points, Shapes, and Tracks layers; supports real-time annotation, plugin-based analysis, and headless screenshot export. Core visualization tool for bioimage analysis workflows. Use ImageJ/FIJI for macro-based processing; use napari for Python-native interactive visualization and plugin-based deep learning segmentation review."

pydicom-medical-imaging

jaechang-hits

"Pure Python DICOM library for medical imaging (CT, MRI, X-ray, ultrasound). Read/write DICOM files, extract pixel data as NumPy arrays, access/modify metadata tags, apply windowing (VOI LUT), anonymize PHI, build DICOM from scratch, process series into 3D volumes. For whole-slide pathology images use histolab; for NIfTI neuroimaging use nibabel."

imagen

sanjay3290

Generate images using Google Gemini's image generation capabilities. Use this skill when the user needs to create, generate, or produce images for any purpose including UI mockups, icons, illustrations, diagrams, concept art, placeholder images, or visual representations.

perf-astro

tech-leads-club

"Astro-specific performance optimizations for 95+ Lighthouse scores. Covers critical CSS inlining, compression, font loading, and LCP optimization. Triggers on: astro performance, astro lighthouse, astro optimization, astro-critters."

figma

tech-leads-club

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

1k-patching-native-modules

OneKeyHQ

Patches native modules (expo-image, react-native, etc.) to fix native crashes or bugs.

flux-best-practices

black-forest-labs

Comprehensive guide for BFL FLUX image generation models. Covers prompting, T2I, I2I, structured JSON, hex colors, typography, multi-reference editing, and model-specific best practices for FLUX.2 and FLUX.1 families.

core-web-vitals

tech-leads-club

Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".

perf-web-optimization

tech-leads-club

"Optimize web performance: Core Web Vitals (LCP, CLS, INP), bundle size, images, caching. Use when site is slow, optimizing for Lighthouse scores, reducing bundle size, fixing layout shifts, or improving Time to Interactive. Triggers on: web performance, Core Web Vitals, LCP, CLS, INP, FID, bundle size, page speed, slow site."

capture-environment

pedrohcgs

Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt / environment.yml / uv.lock, Stata version + ado package list), records seeds and RNG kind, optionally writes a pinning Dockerfile, and produces a paste-ready "Computational requirements" block. Use when user says "capture the environment", "snapshot my dependencies", "pin the versions", "make a renv.lock / requirements.txt", "make this byte-reproducible", or before releasing a replication package to openICPSR / the AEA Data Editor.

openai-image-gen

steipete

Batch-generate images via OpenAI Images API. Random prompt sampler + index.html gallery.

docker-deployment

aAAaqwq

Docker container deployment with Nginx HTTPS configuration and Cloudflare Tunnel integration. Use when deploying web applications with Docker, configuring SSL/TLS certificates, setting up Nginx reverse proxy, or integrating with Cloudflare Tunnel for secure external access.

invokeai-image-gen

sammcj

Generate images using InvokeAI's local API. Use when asked to generate, create, or make images with InvokeAI, FLUX.2 Klein, Z-Image Turbo, FLUX, or SDXL models. Supports text-to-image generation, automatic model detection, image download, and parameter selection based on model architecture.

Ai Image Generation

omer-metin

recommend-image

RHEcosystemAppEng

Intelligently recommend the optimal S2I builder image or container base image for a project based on detected language/framework, use-case requirements, security posture, and deployment target. Supports GitHub URLs for remote project analysis (delegates to /detect-project). Use this skill when the user needs a container image recommendation, wants to compare image options, or asks about production vs development images. Triggers on /recommend-image command, or when advanced image selection beyond basic version matching is needed. Supports Node.js, Python, Java, Go, Ruby, .NET, PHP, and Perl on Red Hat UBI.

s2i-build

RHEcosystemAppEng

Create BuildConfig and ImageStream resources on OpenShift and trigger a Source-to-Image (S2I) build. Use this skill after /detect-project to build container images from source code on the cluster. Handles namespace verification, resource creation with user confirmation, build monitoring with log streaming, and failure recovery. Triggers on /s2i-build command. Run before /deploy.