Skill UI

Engineers minimalist, scalable vector logos using geometric primitives, negative space, and strict flat-style constraints to translate brand briefs into iconic, professional marks for modern identities.

Codified expertise for sequencing work orders, balancing discrete and batch lines, reducing changeover time, and shielding bottlenecks using FCS, DBR, and SMED so manufacturing meets commitments despite disruptions.

FluidSim is a Python-based CFD framework offering pseudospectral solvers (2D/3D Navier-Stokes, shallow water, stratified flows) with FFT, MPI, Pythran/Transonic acceleration, and rich output analysis for turbulence or geophysical studies.

Connect to NCBI's GEO repository, search series/samples/platforms via Entrez queries, fetch profiles, and download raw/processed matrices using GEOparse for transcriptomics and expression analysis workflows.

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.

Access RCSB PDB to search biomolecular structures via text, sequence, or geometry queries, download coordinate files in PDB/mmCIF/Binary formats, retrieve metadata, and batch-process entries for drug discovery, protein engineering, and structural biology pipelines.

Guides symbolic mathematics work in Python, covering algebraic simplification, calculus, equation solving, linear algebra, physics, number theory, geometry, and code generation to deliver exact symbolic results instead of numeric approximations.

Reference for building Graph Neural Networks with PyTorch Geometric, covering data objects, datasets, transforms, convolution layers, lazy initialization, and heterogeneous support so you can quickly tackle node, link, and graph tasks.

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.

Guides product teams through Geoffrey Moore-style positioning statements to clarify target customer, underserved need, category, benefit, and differentiation before messaging or launch planning.

Master the creation and manipulation of 3D geometry within the Three.js framework. This guide covers built-in primitive shapes (Box, Sphere, Cylinder), advanced procedural geometries (Extrude, Tube, TorusKnot), and text visualization. Crucially, it details the use of BufferGeometry, allowing developers to store vertex, normal, UV, and color data in optimized typed arrays for high-performance rendering and custom mesh construction.

Simulates the persona of Geoffrey Hinton, a Turing Award winner and pioneer of deep learning. This skill adopts his first-person voice, combining deep technical knowledge (including backpropagation, deep belief networks, and Boltzmann machines) with academic rigor, epistemic humility, and characteristic British humor. It is ideal for in-depth discussions on the theoretical foundations, history, and principles of complex system learning in AI.