aws-vpc-design
Design and implement production-grade VPC architectures
发现 工具与集成 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。
Design and implement production-grade VPC architectures
Launch, configure, and manage EC2 instances with best practices
Configure AWS IAM users, roles, policies, and identity federation
Optimize AWS costs through resource rightsizing and savings strategies
Configure S3 buckets with security, lifecycle, and replication policies
Infrastructure as Code with CloudFormation templates and stacks
Implement monitoring, alerting, and observability with CloudWatch
Deploy and manage containerized applications on ECS/Fargate
Build optimized serverless functions with Lambda
Build automated CI/CD pipelines with CodePipeline and CodeBuild
Retrieval Augmented Generation systems with vector search, document processing, and hybrid retrieval.
LLM evaluation frameworks, benchmarks, and quality metrics for production systems.
AI agent development with LangChain, CrewAI, AutoGen, and tool integration patterns.
LLM architecture, tokenization, transformers, and inference optimization. Use for understanding and working with language models.
Vector database selection, indexing strategies, and semantic search optimization.
LLM deployment strategies including vLLM, TGI, and cloud inference endpoints.
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
Prompt design, optimization, few-shot learning, and chain of thought techniques for LLM applications.
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Run Codex CLI, Claude Code, OpenCode, or Pi Coding Agent via background process for programmatic control.
Activate expert reasoning and systematic problem-solving mindset for technical and code-related tasks.
AI-native session continuity through shape anchors rather than linear logs. Use when beginning a session to orient from prior state, or when ending to crystallize state for future instances.
Personal research backlog. Quick-capture ideas for later exploration. Check when you have unstructured time.
Quality-first Zig 0.15.1 code generation. Loads stdlib context, generates small pieces, tests, reviews for idioms and slop, refactors. Use for any Zig coding task.
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。