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Found 1,732 Skills
Performance optimization specialist for profiling, caching, and latency optimizationUse when "performance, latency, slow query, profiling, caching, optimization, N+1, connection pool, p99, performance, profiling, caching, latency, optimization, async, database, load-testing, ml-memory" mentioned.
Retrieval-Augmented Generation patterns including chunking, embeddings, vector stores, and retrieval optimizationUse when "rag, retrieval augmented, vector search, embeddings, semantic search, document qa, rag, retrieval, embeddings, vector, search, llm" mentioned.
The meta-skill that powers all other AI tools. Prompt engineering for creative applications is the art and science of communicating with AI models to produce exactly what you envision—in images, video, audio, and text. This isn't just "write better prompts." It's understanding how different models interpret language, how to structure requests for different modalities, how to iterate systematically, and how to build prompt libraries that encode your creative vision. The best prompt engineers have developed intuition for what words trigger what responses in each model. This skill is foundational—it amplifies the effectiveness of every other AI creative skill. Master this, and you master the interface to all AI creation. Use when "prompt, prompting, prompt engineering, better prompts, prompt optimization, how to prompt, prompt strategy, prompt library, prompt template, make AI understand, prompt-engineering, prompting, meta-skill, ai-creative, foundational, optimization, iteration" mentioned.
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when "building RAG, vector search, embeddings, semantic search, document retrieval, context retrieval, knowledge base, LLM with documents, chunking strategy, pinecone, weaviate, chromadb, pgvector, rag, embeddings, vector-database, retrieval, semantic-search, llm, ai, langchain, llamaindex" mentioned.
Apply SEO best practices for web applications including metadata, performance optimization, and search engine optimization techniques.
Julia development guidelines covering multiple dispatch, type system, performance optimization, and scientific computing best practices.
PostCSS best practices and configuration guidelines for modern CSS processing and optimization
SQL query optimization and database performance specialist. Use when optimizing slow queries, fixing N+1 problems, designing indexes, implementing caching, or improving database performance. Works with PostgreSQL, MySQL, and other databases.
Analyze dividend investment opportunities, evaluate dividend safety, growth potential and yield rate. Use this when users inquire about dividends, dividend investment or dividend yield. Supports quick screening, in-depth analysis and portfolio optimization.
Expert performance decisions for iOS/tvOS: when to optimize vs premature optimization, profiling tool selection, SwiftUI view identity trade-offs, and memory management strategies. Use when debugging performance issues, optimizing slow screens, or reducing memory usage. Trigger keywords: performance, Instruments, Time Profiler, Allocations, memory leak, view identity, lazy loading, @StateObject, retain cycle, image caching, faulting, batch operations
Expert real-time VFX artist specializing in particle systems, shader effects, and the invisible craft that makes games feel satisfying. Masters Niagara, VFX Graph, Godot GPU particles, and understands the AAA principles that make effects read clearly at 60fps. Use when "particle system, visual effects, vfx, particles, niagara, vfx graph, flipbook, sprite sheet, explosion effect, magic effect, trail effect, beam effect, dissolve, distortion, force field, hit effect, muzzle flash, impact effect, smoke particles, fire effect, soft particles, game juice, screen shake, particle overdraw, effect optimization, vfx, particles, effects, niagara, vfx-graph, game-juice, visual-effects, shaders, flipbook, trails, beams, explosions, optimization, gpu-particles" mentioned.
Optimize Kubernetes costs through resource right-sizing, unused resource detection, and cluster efficiency analysis. Use for cost optimization, resource analysis, and capacity planning.