Skill UI

Master the LangChain framework to build sophisticated LLM applications. Learn to implement agents, chains, memory management, and tool integration. This skill covers core concepts like ReAct agents, retrieval chains, and document processing pipelines. Ideal for creating autonomous AI agents and production-grade applications using Python.

Senior Laravel Engineer skill for production-grade, maintainable, and idiomatic Laravel solutions. Covers architecture, validation, Eloquent optimization, API design, authentication, caching, queues, and code review.

Reviews Bitcoin Lightning Network protocol designs, compares channel factory approaches, and analyzes Layer 2 scaling tradeoffs including trust models, on-chain footprint, HTLC/PTLC compatibility, liveness and watchtower support.

Technical reference for Lightning Network channel factories, multi-party channels, LSP architectures, and Bitcoin Layer 2 scaling without soft forks, covering Decker-Wattenhofer, timeout trees, MuSig2, HTLC/PTLC, and watchtower breach detection.

Architecture and integration sketches for LLM applications, covering RAG retrieval, tool dispatch, agent loops, caching, privacy boundaries and verification requirements before production use.

Expert skill for building production-grade AI systems using LangChain 0.1+ and LangGraph. Covers agent architecture, RAG pipelines, memory systems, and deployment strategies. Ideal for developing sophisticated LLM applications with observability and scalability.

Framework-agnostic long-term project memory for AI agents. Persists architecture decisions, conventions, and context as plain Markdown files in .lore/, enabling any agent to record, recall, audit, sync, and query project knowledge.

A comprehensive architectural guide for building and maintaining macOS menubar utilities using SwiftUI and Tuist. It enforces strict separation of concerns by guiding developers to keep networking, state management, and UI presentation in distinct, testable layers, ensuring robust and scalable application development.

This skill acts as an ultra-advanced mathematician inspired by Terence Tao. It performs rigorous code and architecture analysis using deep mathematical theories such as information theory, graph theory, computational complexity, linear algebra, stochastic analysis, category theory, Bayesian probability, and formal logic. Ideal for complex algorithmic verification and architectural design review.

This skill provides methodologies for designing sophisticated, layered memory architectures for AI agents. It moves beyond simple context windows and basic vector stores by incorporating short-term, long-term, and graph-based memory systems. Implementing this is crucial for agents that require persistence across sessions, maintaining complex entity consistency, and performing advanced, relationship-driven reasoning over accumulated knowledge bases, including time-aware fact tracking.

Expert in creating Mermaid diagrams for flowcharts, sequence diagrams, ERDs, and architectures. Proficient in syntax for all diagram types and styling, ensuring clear and professional visualizations.

This skill provides a comprehensive framework for mastering microservices architecture patterns. It covers critical aspects of building robust, distributed systems, including defining service boundaries (Domain-Driven Design), managing inter-service communication, handling distributed data transactions, and implementing various resilience patterns (e.g., circuit breaker, circuit breaker). It is essential for large-scale system decomposition.