Validate design systems for accessibility (WCAG), responsive design, and component consistency with design token analysis.
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Build event-driven architectures on AWS serverless infrastructure. Designs event flows, integrates Lambda with event sources, and manages distributed systems.
A reasoning pattern for diagnosing and fixing bugs that span multiple abstraction layers in complex systems.
Verify operating system hardening using CIS benchmarks with patch management, kernel hardening, and host-based firewall validation.
Create System Requirements (SYS) - Layer 6 artifact defining functional requirements and quality attributes
memory-systems
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Design short-term, long-term, and graph-based memory architectures
memory-systems
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This skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal...
memory-systems
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This skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal...
memory-systems
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This skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal...
system-overview
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Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination
rag-engineer
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Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when "building RAG,...
Build collaborative and content-based recommendation engines for product recommendations, personalization, and improving user engagement
semantic-search
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Build production-ready semantic search systems using vector databases, embeddings, and retrieval-augmented generation (RAG). Covers vector DB selection (Pinecone/Qdrant/Weaviate), embedding models...
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RAG Implementer
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Implement retrieval-augmented generation systems. Use when building knowledge-intensive applications, document search, Q&A systems, or need to ground LLM responses in external data. Covers...
langchain_patterns
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Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use...
langchain_patterns
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Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use...
building-rag-systems
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