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architecting-omega-systems
Designs scalable, resilient architectures using the 7 Omega principles. Use when building systems that need to scale to millions of users or designing platform-level infrastructure.
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testing security architecture patterns AI 技能
发现 testing security architecture patterns 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。
分类目录: testing security architecture patterns
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GitHub
ai-architecture
AI application architecture - gateway, orchestration, model routing, observability, deployment patterns. Use when designing AI systems, scaling applications, or building production infrastructure.
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security-hardening
Advanced security patterns including zero-trust architecture, secret management, CSP, and compliance frameworks
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GitHub
implementing-defense-in-depth
AI agent designs layered security architecture with multiple independent protective barriers ensuring no single point of failure. Use when building security systems, reviewing architecture, or hardening applica...
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GitHub
chaos-engineering-and-resilience-testing
The agent implements chaos engineering practices for building resilient systems. Use when testing fault tolerance, designing game days, or validating system recovery.
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GitHub
real-time-systems
WebSocket, Server-Sent Events, and real-time communication patterns for live features
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GitHub
coding-with-omega-leverage
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...
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GitHub
testingchaos-testing
Chaos engineering and fault injection patterns for testing system resilience, failure recovery, and graceful degradation
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GitHub
api-architecture
Enterprise API design with REST, GraphQL, gRPC patterns including versioning, pagination, and error handling
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GitHub
spring
Enterprise Spring Boot development with JPA, security, testing, and microservices patterns
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GitHub
observability
Production observability with structured logging, metrics collection, distributed tracing, and alerting
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GitHub
developing-test-driven
AI agent practices test-first development with the Red-Green-Refactor cycle for confident, well-designed code. Use when implementing features, fixing bugs, or establishing testing practices.
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GitHub
contract-testing
Consumer-driven contract testing with Pact, schema validation, provider verification, and CI/CD integration.
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service-discovery
Service discovery patterns with Consul, Kubernetes DNS, Eureka, health checks, and client-side load balancing.
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GitHub
thinking-sequentially
AI agent structures complex reasoning through numbered thought sequences with explicit dependencies. Use when facing multi-step problems, complex debugging, or architectural decisions.
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GitHub
monorepo-management
Enterprise monorepo patterns with Turborepo and Nx including task orchestration, caching, and CI/CD optimization
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GitHub
service-mesh
Advanced service mesh implementation with Istio, Linkerd, traffic management, mTLS, and observability.
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GitHub
caching-strategies
Multi-layer caching with Redis, CDN, and browser caching for optimal application performance
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GitHub
python
Python development with type hints, async patterns, testing, and modern best practices
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GitHub
common-workflows
Common patterns and workflows for Azure DevOps and database queries. Use to avoid inefficient searches and tangents.
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GitHub
bcm-specialist
Expert for Business Continuity Management (BCM) with deep knowledge of ISO 22301, ISO 22313, and integration with ISO 27001. Automatically activated when user asks about business continuity, disaster recovery,...
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GitHub
custom-plugin-flutter-skill-state
2300+ lines of state management mastery - all patterns (Provider, Riverpod, BLoC, GetX), dependency injection, persistence, testing with production-ready code examples.
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GitHub
custom-plugin-flutter-skill-backend
1500+ lines of backend integration mastery - REST APIs, GraphQL, WebSockets, authentication, Firebase, error handling with production-ready code examples.
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GitHub
hashing-techniques
Hash-based data structures and techniques including frequency counting, duplicate detection, and LRU cache implementation.
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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。