Progressive Web Apps with offline support and installability
Skills in this repository
ffsshhttiikk/opencode-agents-skills - Page 6
SkillsMP has collected 579 skills from ffsshhttiikk/opencode-agents-skills. Open a skill to review its source and details.
ffsshhttiikk/opencode-agents-skillsShowing 40 of 579 collected skills.
JavaScript programming language for web development
Visual workflow management method for optimizing value delivery through continuous flow
Key-value data model
Source text: Undetermined
Key-value database stores
Knowledge representation in AI
Kubernetes container orchestration for deployment, scaling, and management
Large language models
Network latency optimization techniques
Network latency fundamentals
Vector spaces and linear transformations
Linguistics fundamentals
Large language models basics
Practical application and coding skills for Load Balancing
Load testing and performance testing best practices
Centralized logging and analysis
Logging best practices and patterns
Machine learning best practices and patterns
Materials science fundamentals including crystal structures, mechanical properties, phase diagrams, polymers, ceramics, and composites for materials engineering applications.
Formal logic and proof systems
Creating mathematical representations
Differential and integral calculus including derivatives, integrals, series expansions, differential equations, and multivariable calculus for scientific computing.
Counting principles, permutations, combinations, generating functions, partition theory, and combinatorial algorithms for enumeration and optimization.
Ordinary and partial differential equations including analytical solutions, numerical methods, stability analysis, and applications in physics and engineering.
Discrete math fundamentals including combinatorics, graph theory, logic, set theory, algorithms, and number theory for computer science and cryptography.
Graph algorithms including shortest paths, network flow, matching, connectivity, coloring, and community detection for network analysis.
Master linear algebra operations including matrix manipulation, vector spaces, eigenvalues, and linear transformations for scientific computing and machine learning applications.
Number theory fundamentals including divisibility, prime numbers, modular arithmetic, Diophantine equations, and cryptographic applications.
Mathematical optimization including linear programming, convex optimization, gradient descent, and constrained optimization for machine learning and engineering.
Probability theory fundamentals including distributions, conditional probability, Bayes' theorem, random variables, and stochastic processes for modeling uncertainty.
Statistical analysis fundamentals including hypothesis testing, regression analysis, ANOVA, and probability distributions for data analysis.
Mechanical engineering design and analysis
Mechanical systems and applications
Forces and motion principles
Mechatronic systems integration
Service mesh implementation and management
Message queue best practices and patterns
System metrics collection and analysis
Study of microorganisms
Design patterns and architectural approaches for Microservices