Directorio de skills

Descubre skills reutilizables para AI agents.

Busca skills reales de GitHub por tarea y revisa stars, confianza, auditoría, categoría y ruta de instalación antes de utilizarlos.

Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.

Resultados de búsqueda: computational-physics

Directorio en inglés

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

17K
Stars
87/100
Confianza
Categoría: design-creativeAuditoría

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
Confianza
Categoría: design-creativeAuditoría

Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

4.6K
Stars
85/100
Confianza
Categoría: ml-automationAuditoría

Create beautiful, publication-quality books and documents from computational content.

4.3K
Stars
85/100
Confianza
Categoría: document-processingAuditoría

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

34K
Stars
84/100
Confianza
Categoría: ml-automationAuditoría

A DSL for data-driven computational pipelines

3.4K
Stars
77/100
Confianza
Categoría: geo-scienceAuditoría

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

3.0K
Stars
85/100
Confianza
Categoría: ml-automationAuditoría

Course 18.S191 at MIT, Fall 2022 - Introduction to computational thinking with Julia

2.8K
Stars
75/100
Confianza
Categoría: educationAuditoría
C74

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

22K
Stars
74/100
Confianza
Categoría: ml-automationAuditoría

A collection of 34 installable agent skills for running computational-chemistry workflows in OpenClaw, with clear documentation and a DOI citation.

128
Stars
80/100
Confianza
Categoría: researchAuditoría

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

11K
Stars
71/100
Confianza
Categoría: ml-automationAuditoría