发现 测试与安全 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
Expert in building React 19 components with Next.js 15 App Router, TailwindCSS, and the project's theme system. Use when creating or modifying UI components, pages, layouts, client interactions, or styling. Alw...
Expert in building backend features with Next.js server actions, Drizzle ORM models, database operations, and the many-first design pattern. Use when creating or modifying server actions, database models, schem...
Train and fine-tune LLMs using HuggingFace TRL, Transformers, and cloud GPU infrastructure with SFT, DPO, GRPO methods
Automated skill for keeping AI knowledge bases current with latest model versions, framework updates, and best practices
Infrastructure as Code for AI workloads using Terraform across AWS, Azure, GCP, and OCI
Design and implement Model Context Protocol servers for standardized AI-to-data integration with resources, tools, prompts, and security best practices
Deploy and operate AI workloads on Kubernetes with GPU scheduling, model serving, and MLOps patterns
Enterprise AI security - OWASP LLM Top 10, prompt injection defense, guardrails, PII protection
Expert guidance on Oracle Cloud Infrastructure services, cloud architecture patterns, cost optimization, deployment strategies, and OCI best practices for enterprise solutions
Expert in Retrieval-Augmented Generation systems - knowledge bases, chunking strategies, embedding optimization, and production RAG architectures
Build production agentic applications on OCI using Oracle Agent Development Kit with multi-agent orchestration, function tools, and enterprise patterns
NVIDIA NIM inference microservices for deploying AI models with OpenAI-compatible APIs, self-hosted or cloud
Build AI applications on AWS using Bedrock, SageMaker, and AI/ML services with best practices for enterprise deployment
Build autonomous AI agents using Claude Agent SDK with computer use, tool calling, MCP integration, and production best practices
Build AI applications on Azure using Azure OpenAI, Cognitive Services, and ML services with enterprise patterns
Expert in OCI Generative AI Dedicated AI Clusters - deployment, fine-tuning, optimization, and production operations
Current best practices for Model Context Protocol server design, implementation, and integration. Updated patterns for 2026 MCP ecosystem including multi-server orchestration, security, and performance.
Cost optimization for AI workloads - model selection, GPU sizing, commitment strategies, and multi-cloud cost management
Build production-ready multi-agent systems using OpenAI AgentKit and Agents SDK with best practices for agent orchestration, handoffs, and routines
Design framework-agnostic AI agents using Oracle's Open Agent Specification for portable, interoperable agentic systems with JSON/YAML definitions
Production-grade AI architecture patterns for enterprise - security, governance, scalability, and operational excellence
Design and deploy AI workloads across AWS, Azure, GCP, and OCI with intelligent routing, cost optimization, and cross-cloud patterns
Build production-grade agentic workflows with LangGraph using graph-based orchestration, state machines, human-in-the-loop, and advanced control flow
Create professional architecture diagrams using D2, Draw.io, Mermaid, and OCI official icons for enterprise-grade visualizations
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。