Skill UI

FluidSim is a high-performance, object-oriented Python framework for Computational Fluid Dynamics (CFD). It enables users to simulate complex physical flows, including 2D/3D Navier-Stokes equations, shallow water dynamics, and stratified flows. Utilizing pseudospectral methods with FFT and MPI parallelization, it delivers scientific accuracy comparable to compiled languages while maintaining the ease of Python development. Ideal for academic research, industrial flow analysis, and geophysical modeling.

Generate or edit high-quality photos, illustrations, and visual assets using OpenRouter models like Gemini 3.1 Flash and Flux 2 Pro; configure the API key once, then run the scripts for prompts, edits, or batch outputs for presentations, marketing, or general creative needs.

Geniml is a comprehensive Python package designed for applying machine learning techniques to genomic interval data stored in BED files. It provides advanced methods like Region2Vec, BEDspace, and scEmbed to learn embeddings for genomic regions, single cells, and metadata. Use it for dimension reduction, clustering, similarity searches, and sophisticated bioinformatic analyses in genomics. Core functionalities include: learning region embeddings (Region2Vec), joint embeddings of regions and metadata (BEDspace), single-cell chromatin accessibility embedding (scEmbed), and building consensus...

GeoMaster is a comprehensive geospatial science skill that guides remote sensing, GIS, spatial analysis, and machine learning workflows for Earth observation and planetary data projects, covering satellite imagery, vector/raster math, point clouds, terrain, hydrology, and cloud-native data stacks.

GeoPandas extends pandas for geospatial vector data, enabling reading/writing shapefiles, GeoJSON, GeoPackage and PostGIS, performing CRS management, spatial joins, overlays, buffering, area/distance calculations, and producing static or interactive choropleth maps.

Detects system CPU, GPU, memory, and disk availability before heavy scientific tasks, writing `.claude_resources.json` with strategic recommendations (parallelism, out-of-core, GPU acceleration) so analysts choose appropriate compute approaches.

gget is a CLI/Python client that unifies querying over 20+ bioinformatics databases, letting researchers fetch gene info, sequences, BLAST results, structures, and enrichment data interactively or within scripts.

Submit and manage autonomous lab protocols on Ginkgo Cloud Lab, leveraging RACs for cell-free protein expression validation/optimization, fluorescent pixel art, EstiMate AI assessments, and guided ordering of sample inputs through the web interface.

Analyzes protein sequences to locate canonical N-glycosylation sequons, predict O-glycosylation hotspots, and mutate or design glycosylation sites for therapeutic proteins, vaccines, and biosimilar comparisons using curated glycoengineering resources.

Gtars is a high-performance toolkit written in Rust with Python bindings, specialized for computational genomics. It provides advanced functionality for manipulating genomic interval data, including overlap detection (IGD), coverage track generation (BigWig), and genomic tokenization for machine learning preprocessing. Ideal for researchers working with BED files, single-cell data, and ML-driven biological models.

Histolab streamlines whole-slide microscopy by automating tissue detection, tile extraction, and stain normalization for H&E scans, making it ideal for lightweight dataset prep and quick tile-based analysis.

Hypogenic automates LLM-driven hypothesis generation and testing over tabular datasets, blending literature insights with empirical analysis to accelerate discovery in domains like deception detection or AI content evaluation.