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数据库 AI 技能

发现 数据库 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。

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显示第 39,673–39,696 个,共 85,283 个

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GitHub

ml-workflow

doanchienthangdev

ML development workflow covering experiment design, baseline establishment, iterative improvement, and experiment tracking best practices.

GitHub

requesting-code-reviews

doanchienthangdev

AI agent requests effective code reviews through proper preparation, clear descriptions, and appropriate reviewer selection. Use when creating PRs, requesting feedback, or submitting for review.

GitHub

verifying-before-completion

doanchienthangdev

AI agent validates work through evidence-based verification with comprehensive checklists, automated validation, and proof-of-work documentation. Use when completing tasks, preparing for review, or ensuring qua...

GitHub

ai-engineering

doanchienthangdev

Building production AI applications with Foundation Models. Covers prompt engineering, RAG, agents, finetuning, evaluation, and deployment. Use when working with LLMs, building AI features, or architecting AI s...

GitHub

inference-optimization

doanchienthangdev

Optimizing AI inference - quantization, speculative decoding, KV cache, batching, caching strategies. Use when reducing latency, lowering costs, or scaling AI serving.

GitHub

deployment-paradigms

doanchienthangdev

ML deployment paradigms including batch vs real-time inference, online vs offline serving, edge deployment, and serverless ML.

GitHub

testing-omega-quality

doanchienthangdev

Implements comprehensive testing across all quality dimensions - accuracy, performance, security, and accessibility. Use when building test strategies or ensuring production-grade quality assurance.

GitHub

coding-with-omega-leverage

doanchienthangdev

Applies AI-first development patterns for 10-100x productivity through specification-driven generation and leverage multiplication. Use when developing features with AI assistance or optimizing development work...

GitHub

testingchaos-testing

doanchienthangdev

Chaos engineering and fault injection patterns for testing system resilience, failure recovery, and graceful degradation

GitHub

api-architecture

doanchienthangdev

Enterprise API design with REST, GraphQL, gRPC patterns including versioning, pagination, and error handling

GitHub

research-validation

doanchienthangdev

Multi-source validation framework for technology decisions, best practices verification, and evidence-based implementation

GitHub

tracing-root-causes

doanchienthangdev

AI agent performs systematic root cause analysis using 5 Whys, Fishbone diagrams, and evidence-based investigation. Use when debugging, conducting post-mortems, or investigating incidents.

GitHub

building-with-shadcn

doanchienthangdev

Claude builds accessible React UIs using shadcn/ui components with Radix primitives and React Hook Form integration. Use when creating forms, dialogs, or composable UI systems.

GitHub

debugging-systematically

doanchienthangdev

AI agent follows a 5-phase debugging process with reproduction, isolation, hypothesis testing, and root cause resolution. Use when investigating bugs, troubleshooting issues, or hunting errors.

GitHub

building-laravel-apis

doanchienthangdev

Builds enterprise Laravel applications with Eloquent, API Resources, Sanctum auth, and queue processing. Use when creating PHP backends, REST APIs, or full-stack Laravel applications.

GitHub

ai-agents

doanchienthangdev

Building AI agents - tool use, planning strategies (ReAct, Plan-and-Execute), memory systems, agent evaluation. Use when building autonomous AI systems, tool-augmented apps, or multi-step workflows.

GitHub

dnn-architectures

doanchienthangdev

Deep neural network architectures including CNNs, RNNs, Transformers, and modern architectures for vision, NLP, and multimodal tasks.

GitHub

finetuning

doanchienthangdev

Finetuning Foundation Models - when to finetune, LoRA, QLoRA, PEFT techniques, memory optimization, model merging. Use when adapting models to specific domains, reducing costs, or improving performance.

GitHub

ml-systems-fundamentals

doanchienthangdev

Core ML systems concepts including ML lifecycle, system architecture, requirements, and design principles for production ML.

GitHub

spring

doanchienthangdev

Enterprise Spring Boot development with JPA, security, testing, and microservices patterns

GitHub

managing-omega-sprints

doanchienthangdev

Orchestrates AI-native sprint management with autonomous agent coordination and continuous delivery. Use when running development sprints with AI agent teams or coordinating parallel task execution.

GitHub

guardrails-safety

doanchienthangdev

Protecting AI applications - input/output guards, toxicity detection, PII protection, injection defense, constitutional AI. Use when securing AI systems, preventing misuse, or ensuring compliance.

GitHub

test-task-generation

doanchienthangdev

The agent automatically generates comprehensive test tasks from feature requirements, ensuring every implementation task has corresponding test coverage with proper acceptance criteria.

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。

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