Annuaire de skills

Découvrez des skills réutilisables pour les AI agents.

Recherchez de vrais skills GitHub par tâche et vérifiez Stars, confiance, audit, catégorie et chemin d’installation avant de les utiliser.

Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.

Résultats de recherche: computational-physics

Annuaire en anglais

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
Confiance
Catégorie: design-creativeAudit

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
Confiance
Catégorie: design-creativeAudit

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

4.6K
Stars
85/100
Confiance
Catégorie: ml-automationAudit

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

4.3K
Stars
85/100
Confiance
Catégorie: document-processingAudit

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

34K
Stars
84/100
Confiance
Catégorie: ml-automationAudit

A DSL for data-driven computational pipelines

3.4K
Stars
77/100
Confiance
Catégorie: geo-scienceAudit

NMA Computational Neuroscience course

3.1K
Stars
80/100
Confiance
Catégorie: ml-automationAudit

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
Confiance
Catégorie: ml-automationAudit

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

2.8K
Stars
75/100
Confiance
Catégorie: educationAudit
C74

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

22K
Stars
74/100
Confiance
Catégorie: ml-automationAudit

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
Confiance
Catégorie: researchAudit

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

11K
Stars
71/100
Confiance
Catégorie: ml-automationAudit